kopia lustrzana https://github.com/thinkst/zippy
4207 wiersze
2.8 MiB
4207 wiersze
2.8 MiB
<?xml version="1.0" encoding="utf-8"?><testsuites><testsuite name="pytest" errors="0" failures="1402" skipped="0" tests="4218" time="1762.463" timestamp="2023-05-31T11:28:59.976709" hostname="FALCON-PUNCH"><testcase classname="test_openai_detect" name="test_training_file" time="6.351"><properties><property name="score" value="0.29978469289" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[IFAW1.txt]" time="0.294"><properties><property name="score" value="0.05344405" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[cdc_covid.txt]" time="0.812"><properties><property name="score" value="0.0184051828" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[How_soon-Fans.txt]" time="0.282"><properties><property name="score" value="0.0027909067" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[hsus4.txt]" time="0.677"><properties><property name="score" value="0.0029219983" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[pg_robinson_crusoe.txt]" time="2.001"><properties><property name="score" value="0.2143783323857143" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[How_soon-Lebron-James.txt]" time="0.368"><properties><property name="score" value="0.0008030889" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Ohio_Steel.txt]" time="1.576"><properties><property name="score" value="0.00403165024" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[chapter-10.txt]" time="2.961"><properties><property name="score" value="0.0189166679" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Env_Prot_Agency-nov1.txt]" time="2.584"><properties><property name="score" value="0.011816757725" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[ch5.txt]" time="2.024"><properties><property name="score" value="0.10169709514285716" /></properties><failure message="AssertionError: ch5.txt is a human-generated file, misclassified as AI-generated with confidence 0.1016971 assert 'AI' == 'Human' - Human + AI">E AssertionError: ch5.txt is a human-generated file, misclassified as AI-generated with confidence 0.1016971
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[lw1.txt]" time="0.297"><properties><property name="score" value="0.321209" /></properties><failure message="AssertionError: lw1.txt is a human-generated file, misclassified as AI-generated with confidence 0.321209 assert 'AI' == 'Human' - Human + AI">E AssertionError: lw1.txt is a human-generated file, misclassified as AI-generated with confidence 0.321209
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[Madame_White_Snake.txt]" time="0.835"><properties><property name="score" value="0.014767393733333335" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[110CYL070.txt]" time="0.273"><properties><property name="score" value="0.24556607" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[audubon1.txt]" time="0.591"><properties><property name="score" value="0.06538683605000001" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[littleshelter2.txt]" time="0.278"><properties><property name="score" value="0.007518992" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[guidedogs1.txt]" time="0.473"><properties><property name="score" value="0.0010390421" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[anth_essay_4.txt]" time="1.366"><properties><property name="score" value="0.008240242683333334" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[113CWL018.txt]" time="0.242"><properties><property name="score" value="0.02204461" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[blog-monastery.txt]" time="0.529"><properties><property name="score" value="0.691094675" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[115CVL037.txt]" time="0.260"><properties><property name="score" value="0.0007671188" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[115CVL036.txt]" time="0.268"><properties><property name="score" value="1.0165573" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[A_defense_of_Michael_Moore.txt]" time="2.032"><properties><property name="score" value="0.0072790699125" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[captured_moments.txt]" time="2.512"><properties><property name="score" value="0.0070851038750000105" /></properties><failure message="AssertionError: captured_moments.txt is a human-generated file, misclassified as AI-generated with confidence 0.0070851 assert 'AI' == 'Human' - Human + AI">E AssertionError: captured_moments.txt is a human-generated file, misclassified as AI-generated with confidence 0.0070851
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[115CVL035.txt]" time="0.276"><properties><property name="score" value="1.2781626" /></properties><failure message="AssertionError: 115CVL035.txt is a human-generated file, misclassified as AI-generated with confidence 1.2781626 assert 'AI' == 'Human' - Human + AI">E AssertionError: 115CVL035.txt is a human-generated file, misclassified as AI-generated with confidence 1.2781626
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[NWF1.txt]" time="0.274"><properties><property name="score" value="0.0120113025" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[WhereToHongKong.txt]" time="4.428"><properties><property name="score" value="0.11388835228933332" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[att2.txt]" time="0.275"><properties><property name="score" value="0.0010946554" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[c4_GOD.txt]" time="0.287"><properties><property name="score" value="0.0326505" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[cdc_covid_asthma.txt]" time="0.272"><properties><property name="score" value="0.0030465834" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[fcic_final_report_conclusions.txt]" time="3.337"><properties><property name="score" value="0.007364960385454546" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[118CWL050.txt]" time="0.323"><properties><property name="score" value="0.05735386" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[116CUL033.txt]" time="0.286"><properties><property name="score" value="0.50825274" /></properties><failure message="AssertionError: 116CUL033.txt is a human-generated file, misclassified as AI-generated with confidence 0.50825274 assert 'AI' == 'Human' - Human + AI">E AssertionError: 116CUL033.txt is a human-generated file, misclassified as AI-generated with confidence 0.50825274
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[112C-L012.txt]" time="0.239"><properties><property name="score" value="0.024406457" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[appalachian1.txt]" time="0.605"><properties><property name="score" value="0.003754575833333333" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[united1.txt]" time="0.299"><properties><property name="score" value="0.0011339772" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[117CWL009.txt]" time="0.244"><properties><property name="score" value="0.68130136" /></properties><failure message="AssertionError: 117CWL009.txt is a human-generated file, misclassified as AI-generated with confidence 0.68130136 assert 'AI' == 'Human' - Human + AI">E AssertionError: 117CWL009.txt is a human-generated file, misclassified as AI-generated with confidence 0.68130136
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[marine1.txt]" time="0.460"><properties><property name="score" value="0.0293355135" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Ant_Robot.txt]" time="3.673"><properties><property name="score" value="0.056557139750000006" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[110CYL069.txt]" time="0.333"><properties><property name="score" value="0.00039282523" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[CUP2.txt]" time="3.044"><properties><property name="score" value="0.016932493166666663" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Tupelo-Honey-Cafe.txt]" time="0.277"><properties><property name="score" value="0.0027538477" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[119CWL041.txt]" time="0.239"><properties><property name="score" value="1.3696835" /></properties><failure message="AssertionError: 119CWL041.txt is a human-generated file, misclassified as AI-generated with confidence 1.3696835 assert 'AI' == 'Human' - Human + AI">E AssertionError: 119CWL041.txt is a human-generated file, misclassified as AI-generated with confidence 1.3696835
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[lzma_readme.txt]" time="0.305"><properties><property name="score" value="0.20062155" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Homosexuality.txt]" time="1.144"><properties><property name="score" value="0.01748147345" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[116CUL032.txt]" time="0.260"><properties><property name="score" value="0.19387838" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[112C-L014.txt]" time="0.258"><properties><property name="score" value="0.02341995" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Fermentation_HR5034.txt]" time="1.162"><properties><property name="score" value="0.04014095155" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Acephalous-Internet.txt]" time="0.314"><properties><property name="score" value="0.004258367" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Effing-Idiot.txt]" time="2.534"><properties><property name="score" value="0.1123282899375" /></properties><failure message="AssertionError: Effing-Idiot.txt is a human-generated file, misclassified as AI-generated with confidence 0.11232829 assert 'AI' == 'Human' - Human + AI">E AssertionError: Effing-Idiot.txt is a human-generated file, misclassified as AI-generated with confidence 0.11232829
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[114CUL059.txt]" time="0.300"><properties><property name="score" value="0.0008551662" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[sucker.txt]" time="0.297"><properties><property name="score" value="0.0023791653" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[c4_denver.txt]" time="0.250"><properties><property name="score" value="0.017132564" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[blog-jet-lag.txt]" time="0.607"><properties><property name="score" value="0.022457973000000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[warner1.txt]" time="0.298"><properties><property name="score" value="0.00060882105" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Fermentation_Eminent-Domain.txt]" time="1.200"><properties><property name="score" value="0.048683041649999995" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[113CWL017.txt]" time="0.275"><properties><property name="score" value="0.018876841" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[112C-L015.txt]" time="0.241"><properties><property name="score" value="0.76102227" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[blog-new-year's-resolutions.txt]" time="0.549"><properties><property name="score" value="0.21544119650000002" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[audubon2.txt]" time="1.297"><properties><property name="score" value="0.016049655" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[The_Black_Willow.txt]" time="3.540"><properties><property name="score" value="0.08677107616666667" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Postal_Rate_Comm-ReportToCongress2002WEB.txt]" time="2.291"><properties><property name="score" value="0.0052109437374999994" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[alumnifund1.txt]" time="0.242"><properties><property name="score" value="0.0010339124" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[112C-L016.txt]" time="0.242"><properties><property name="score" value="0.21132182" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[114CUL057.txt]" time="0.260"><properties><property name="score" value="0.07189497" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[110CYL067.txt]" time="0.310"><properties><property name="score" value="0.010399726" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[hs_keyescrow.txt]" time="1.060"><properties><property name="score" value="0.02401955766" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[lessig_blog-carbon.txt]" time="1.529"><properties><property name="score" value="0.006020881433333333" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[114CUL060.txt]" time="1.020"><properties><property name="score" value="0.0435789" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[vampires.txt]" time="0.559"><properties><property name="score" value="0.249644725" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[chZ.txt]" time="0.555"><properties><property name="score" value="0.00759284735" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[ts_theme_intro.txt]" time="0.263"><properties><property name="score" value="0.0077093816" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[wildelifewatch1.txt]" time="0.280"><properties><property name="score" value="0.0008736013" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[aspca1.txt]" time="0.298"><properties><property name="score" value="0.000635122" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[reuters_santos.txt]" time="0.251"><properties><property name="score" value="0.007153447" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[110CYL071.txt]" time="0.255"><properties><property name="score" value="0.010144273" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Uprooted_Bike.txt]" time="0.538"><properties><property name="score" value="0.0484092125" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Black_and_white.txt]" time="1.064"><properties><property name="score" value="0.11881842484" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[110CYL200.txt]" time="0.276"><properties><property name="score" value="0.005993393" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[A_Wasted_Day.txt]" time="1.898"><properties><property name="score" value="0.0156540446" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[HistoryGreek.txt]" time="1.145"><properties><property name="score" value="0.021857170000000002" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[HistoryLasVegas.txt]" time="1.157"><properties><property name="score" value="0.0863476506" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[cnn_santos.txt]" time="0.260"><properties><property name="score" value="0.0005615252" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[detroit.txt]" time="1.460"><properties><property name="score" value="0.5107537337399999" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[118CWL049.txt]" time="0.294"><properties><property name="score" value="0.07096244" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[hotel-california.txt]" time="2.501"><properties><property name="score" value="0.16528847922222226" /></properties><failure message="AssertionError: hotel-california.txt is a human-generated file, misclassified as AI-generated with confidence 0.16528848 assert 'AI' == 'Human' - Human + AI">E AssertionError: hotel-california.txt is a human-generated file, misclassified as AI-generated with confidence 0.16528848
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[602CZL285.txt]" time="0.268"><properties><property name="score" value="0.005824011" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[WhatToHongKong.txt]" time="1.825"><properties><property name="score" value="0.039608627433333335" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Bartok.txt]" time="2.094"><properties><property name="score" value="0.15070234217714282" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Uprooted_Farming-on-Sand.txt]" time="0.549"><properties><property name="score" value="0.0171321656" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[116CUL034.txt]" time="0.289"><properties><property name="score" value="0.03167346" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[114CUL058.txt]" time="0.275"><properties><property name="score" value="0.08275843" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[IntroDublin.txt]" time="0.583"><properties><property name="score" value="0.02920888908" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[defenders5.txt]" time="0.601"><properties><property name="score" value="0.00751226675" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Acephalous-Cant-believe.txt]" time="0.263"><properties><property name="score" value="0.008920663" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[118CWL048.txt]" time="0.251"><properties><property name="score" value="0.0165241" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[110CYL068.txt]" time="0.294"><properties><property name="score" value="0.0005746466" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[HistoryJerusalem.txt]" time="1.175"><properties><property name="score" value="0.01368474615" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[rybczynski-ch3.txt]" time="3.751"><properties><property name="score" value="0.02294348087692308" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[117CWL008.txt]" time="0.254"><properties><property name="score" value="0.0045487825" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Italy.txt]" time="0.572"><properties><property name="score" value="0.0246767925" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[CUP1.txt]" time="3.758"><properties><property name="score" value="0.015513439729999998" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Seedbombing.txt]" time="0.581"><properties><property name="score" value="0.044083305" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Nathans_Bylichka.txt]" time="4.436"><properties><property name="score" value="0.06469702557142858" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Anti-Terrorist.txt]" time="0.537"><properties><property name="score" value="0.031813759500000004" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[Protocol_Regarding_Access.txt]" time="1.169"><properties><property name="score" value="0.01185575925" /></properties><failure message="AssertionError: Protocol_Regarding_Access.txt is a human-generated file, misclassified as AI-generated with confidence 0.01185576 assert 'AI' == 'Human' - Human + AI">E AssertionError: Protocol_Regarding_Access.txt is a human-generated file, misclassified as AI-generated with confidence 0.01185576
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[IntroHongKong.txt]" time="0.304"><properties><property name="score" value="0.03393609" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[wwf12.txt]" time="0.280"><properties><property name="score" value="0.0110121595" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[112C-L013.txt]" time="0.337"><properties><property name="score" value="0.07344776" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_samples[blog-varsity-athletics.txt]" time="0.569"><properties><property name="score" value="0.49355546450000004" /></properties><failure message="AssertionError: blog-varsity-athletics.txt is a human-generated file, misclassified as AI-generated with confidence 0.49355546 assert 'AI' == 'Human' - Human + AI">E AssertionError: blog-varsity-athletics.txt is a human-generated file, misclassified as AI-generated with confidence 0.49355546
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_samples[AMC2.txt]" time="0.325"><properties><property name="score" value="0.0012100624" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00667_generated.txt]" time="0.577"><properties><property name="score" value="0.11011182" /></properties><failure message="AssertionError: 2111.00667_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.11011182 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00667_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.11011182
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.13472_generated.txt]" time="0.632"><properties><property name="score" value="0.021518702" /></properties><failure message="AssertionError: 2110.13472_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0215187 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.13472_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0215187
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03612_generated.txt]" time="0.888"><properties><property name="score" value="0.055625297500000004" /></properties><failure message="AssertionError: 2111.03612_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0556253 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.03612_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0556253
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00310_generated.txt]" time="0.566"><properties><property name="score" value="0.3509441553" /></properties><failure message="AssertionError: 2111.00310_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.35094416 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00310_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.35094416
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.06230_generated.txt]" time="1.001"><properties><property name="score" value="0.22204800375" /></properties><failure message="AssertionError: 2111.06230_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.222048 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.06230_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.222048
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.06012_generated.txt]" time="0.866"><properties><property name="score" value="0.036736655666666666" /></properties><failure message="AssertionError: 2111.06012_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03673666 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.06012_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03673666
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01676_generated.txt]" time="0.593"><properties><property name="score" value="0.10944002800000001" /></properties><failure message="AssertionError: 2111.01676_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.10944003 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.01676_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.10944003
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2112.00405_generated.txt]" time="0.571"><properties><property name="score" value="0.30434084" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[gpt_exercise.txt]" time="0.280"><properties><property name="score" value="0.013640298" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.05241_generated.txt]" time="0.583"><properties><property name="score" value="0.10317413325" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.12645_generated.txt]" time="0.528"><properties><property name="score" value="0.705281035" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.07793_generated.txt]" time="1.275"><properties><property name="score" value="0.27326515149999997" /></properties><failure message="AssertionError: 2111.07793_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.27326515 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.07793_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.27326515
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[cleaned_2111.00086_generated.txt]" time="0.624"><properties><property name="score" value="0.00492936665" /></properties><failure message="AssertionError: cleaned_2111.00086_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00492937 assert 'Human' == 'AI' - AI + Human">E AssertionError: cleaned_2111.00086_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00492937
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10340_generated.txt]" time="2.080"><properties><property name="score" value="0.0010709305333333333" /></properties><failure message="AssertionError: 2110.10340_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00107093 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10340_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00107093
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.11115_generated.txt]" time="0.527"><properties><property name="score" value="0.09887177" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.15093_generated.txt]" time="0.657"><properties><property name="score" value="0.840663205" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01515_generated.txt]" time="2.773"><properties><property name="score" value="0.072964161" /></properties><failure message="AssertionError: 2111.01515_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07296416 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.01515_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07296416
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.12501_generated.txt]" time="0.624"><properties><property name="score" value="0.013567923666666667" /></properties><failure message="AssertionError: 2110.12501_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01356792 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.12501_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01356792
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02041_generated.txt]" time="1.158"><properties><property name="score" value="0.14138968000000002" /></properties><failure message="AssertionError: 2111.02041_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.14138968 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02041_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.14138968
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01023_generated.txt]" time="0.599"><properties><property name="score" value="0.071015122" /></properties><failure message="AssertionError: 2111.01023_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07101512 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.01023_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07101512
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03715_generated.txt]" time="0.585"><properties><property name="score" value="0.6565959165" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[cgpt_analysis_explosion.txt]" time="0.313"><properties><property name="score" value="0.010328911" /></properties><failure message="AssertionError: cgpt_analysis_explosion.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01032891 assert 'Human' == 'AI' - AI + Human">E AssertionError: cgpt_analysis_explosion.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01032891
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02760_generated.txt]" time="0.583"><properties><property name="score" value="0.5524110400000001" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02574_generated.txt]" time="1.119"><properties><property name="score" value="0.0064772728" /></properties><failure message="AssertionError: 2111.02574_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00647727 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02574_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00647727
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15023_generated.txt]" time="0.645"><properties><property name="score" value="0.01920905566666667" /></properties><failure message="AssertionError: 2110.15023_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01920906 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15023_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01920906
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03320_generated.txt]" time="1.196"><properties><property name="score" value="0.035060245000000004" /></properties><failure message="AssertionError: 2111.03320_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03506025 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.03320_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03506025
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[gpt_patient_narrative.txt]" time="0.295"><properties><property name="score" value="0.4703216" /></properties><failure message="AssertionError: gpt_patient_narrative.txt is an LLM-generated file, misclassified as human-generated with confidence 0.4703216 assert 'Human' == 'AI' - AI + Human">E AssertionError: gpt_patient_narrative.txt is an LLM-generated file, misclassified as human-generated with confidence 0.4703216
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15317_generated.txt]" time="0.585"><properties><property name="score" value="0.0134487305" /></properties><failure message="AssertionError: 2110.15317_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01344873 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15317_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01344873
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.06181_generated.txt]" time="0.809"><properties><property name="score" value="0.05541978333333333" /></properties><failure message="AssertionError: 2111.06181_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.05541978 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.06181_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.05541978
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03294_generated.txt]" time="0.574"><properties><property name="score" value="0.6515486175" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.15436_generated.txt]" time="1.058"><properties><property name="score" value="0.8698189113333333" /></properties><failure message="AssertionError: 2111.15436_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.86981891 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.15436_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.86981891
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00867_generated.txt]" time="0.632"><properties><property name="score" value="0.0053052056" /></properties><failure message="AssertionError: 2111.00867_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00530521 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00867_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00530521
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.05754_generated.txt]" time="0.568"><properties><property name="score" value="0.028684340000000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[dv_t1_aliens.txt]" time="0.400"><properties><property name="score" value="0.13538995" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.12341_generated.txt]" time="0.594"><properties><property name="score" value="0.154240047" /></properties><failure message="AssertionError: 2110.12341_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.15424005 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.12341_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.15424005
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00086_generated.txt]" time="0.641"><properties><property name="score" value="0.00295919065" /></properties><failure message="AssertionError: 2111.00086_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00295919 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00086_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00295919
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02326_generated.txt]" time="0.906"><properties><property name="score" value="0.016982728333333332" /></properties><failure message="AssertionError: 2111.02326_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01698273 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02326_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01698273
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00514_generated.txt]" time="0.498"><properties><property name="score" value="0.188510125" /></properties><failure message="AssertionError: 2111.00514_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.18851013 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00514_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.18851013
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.14532_generated.txt]" time="0.537"><properties><property name="score" value="0.004167286433333333" /></properties><failure message="AssertionError: 2110.14532_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00416729 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.14532_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00416729
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.07408_generated.txt]" time="0.509"><properties><property name="score" value="0.0771191495" /></properties><failure message="AssertionError: 2111.07408_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07711915 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.07408_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07711915
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00035_generated.txt]" time="0.888"><properties><property name="score" value="0.029852037999999997" /></properties><failure message="AssertionError: 2111.00035_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02985204 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00035_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02985204
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02687_generated.txt]" time="0.615"><properties><property name="score" value="0.040120995" /></properties><failure message="AssertionError: 2111.02687_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.04012099 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02687_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.04012099
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.05204_generated.txt]" time="0.668"><properties><property name="score" value="0.010864438099999998" /></properties><failure message="AssertionError: 2111.05204_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01086444 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.05204_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01086444
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10478_generated.txt]" time="0.317"><properties><property name="score" value="0.17298381" /></properties><failure message="AssertionError: 2110.10478_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.17298381 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10478_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.17298381
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02188_generated.txt]" time="1.255"><properties><property name="score" value="0.77014933625" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10575_generated.txt]" time="0.776"><properties><property name="score" value="0.001430481" /></properties><failure message="AssertionError: 2110.10575_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00143048 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10575_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00143048
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.07525_generated.txt]" time="0.605"><properties><property name="score" value="0.0023842172" /></properties><failure message="AssertionError: 2111.07525_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00238422 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.07525_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00238422
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10577_generated.txt]" time="0.573"><properties><property name="score" value="0.076736627" /></properties><failure message="AssertionError: 2110.10577_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07673663 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10577_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.07673663
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.15473_generated.txt]" time="0.564"><properties><property name="score" value="0.25686263365" /></properties><failure message="AssertionError: 2111.15473_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.25686263 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.15473_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.25686263
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10778_generated.txt]" time="0.595"><properties><property name="score" value="0.11058644" /></properties><failure message="AssertionError: 2110.10778_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.11058644 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10778_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.11058644
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.13900_generated.txt]" time="0.916"><properties><property name="score" value="0.355499501" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.04416_generated.txt]" time="0.852"><properties><property name="score" value="0.012649427333333333" /></properties><failure message="AssertionError: 2111.04416_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01264943 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.04416_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01264943
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03913_generated.txt]" time="0.598"><properties><property name="score" value="0.00472829155" /></properties><failure message="AssertionError: 2111.03913_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00472829 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.03913_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00472829
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01706_generated.txt]" time="0.829"><properties><property name="score" value="0.0324598543" /></properties><failure message="AssertionError: 2111.01706_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03245985 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.01706_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03245985
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01243_generated.txt]" time="0.585"><properties><property name="score" value="0.09889898" /></properties><failure message="AssertionError: 2111.01243_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.09889898 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.01243_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.09889898
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.11879_generated.txt]" time="0.550"><properties><property name="score" value="0.40018102499999997" /></properties><failure message="AssertionError: 2110.11879_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.40018102 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.11879_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.40018102
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10329_generated.txt]" time="0.599"><properties><property name="score" value="0.0038873672" /></properties><failure message="AssertionError: 2110.10329_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00388737 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10329_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00388737
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.04507_generated.txt]" time="0.603"><properties><property name="score" value="0.18360849333333332" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03837_generated.txt]" time="0.943"><properties><property name="score" value="0.4597122836666667" /></properties><failure message="AssertionError: 2111.03837_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.45971228 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.03837_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.45971228
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00572_generated.txt]" time="0.609"><properties><property name="score" value="0.00453551565" /></properties><failure message="AssertionError: 2111.00572_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00453552 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00572_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00453552
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.11984_generated.txt]" time="0.578"><properties><property name="score" value="0.7670269975" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.06464_generated.txt]" time="0.560"><properties><property name="score" value="0.55759087" /></properties><failure message="AssertionError: 2111.06464_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.55759087 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.06464_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.55759087
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[cgpt_hs_essay2.txt]" time="0.379"><properties><property name="score" value="0.20345044" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02110_generated.txt]" time="0.526"><properties><property name="score" value="0.9217342270000001" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[cgpt_hs_essay.txt]" time="0.352"><properties><property name="score" value="0.11243306" /></properties><failure message="AssertionError: cgpt_hs_essay.txt is an LLM-generated file, misclassified as human-generated with confidence 0.11243306 assert 'Human' == 'AI' - AI + Human">E AssertionError: cgpt_hs_essay.txt is an LLM-generated file, misclassified as human-generated with confidence 0.11243306
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15802_generated.txt]" time="0.612"><properties><property name="score" value="0.0026097926" /></properties><failure message="AssertionError: 2110.15802_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00260979 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15802_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00260979
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.11589_generated.txt]" time="0.617"><properties><property name="score" value="0.0133893753" /></properties><failure message="AssertionError: 2110.11589_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01338938 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.11589_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01338938
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15724_generated.txt]" time="0.674"><properties><property name="score" value="0.32608005" /></properties><failure message="AssertionError: 2110.15724_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.32608005 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15724_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.32608005
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15130_generated.txt]" time="1.333"><properties><property name="score" value="0.12808935200000002" /></properties><failure message="AssertionError: 2110.15130_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.12808935 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15130_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.12808935
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.06644_generated.txt]" time="0.529"><properties><property name="score" value="0.028277022333333336" /></properties><failure message="AssertionError: 2111.06644_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02827702 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.06644_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02827702
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[bard_news.txt]" time="0.277"><properties><property name="score" value="0.010302887" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01322_generated.txt]" time="0.572"><properties><property name="score" value="0.17217707799999998" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00526_generated.txt]" time="0.628"><properties><property name="score" value="0.015507944333333334" /></properties><failure message="AssertionError: 2111.00526_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01550794 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00526_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01550794
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.12010_generated.txt]" time="0.636"><properties><property name="score" value="0.034934033" /></properties><failure message="AssertionError: 2110.12010_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03493403 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.12010_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.03493403
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[cgpt_planet_abs.txt]" time="0.299"><properties><property name="score" value="0.2305916" /></properties><failure message="AssertionError: cgpt_planet_abs.txt is an LLM-generated file, misclassified as human-generated with confidence 0.2305916 assert 'Human' == 'AI' - AI + Human">E AssertionError: cgpt_planet_abs.txt is an LLM-generated file, misclassified as human-generated with confidence 0.2305916
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.13317_generated.txt]" time="1.039"><properties><property name="score" value="0.00554525175" /></properties><failure message="AssertionError: 2110.13317_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00554525 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.13317_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00554525
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[gpt_santos_long.txt]" time="0.369"><properties><property name="score" value="0.7558597" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02643_generated.txt]" time="1.039"><properties><property name="score" value="0.09290933366666666" /></properties><failure message="AssertionError: 2111.02643_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.09290933 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02643_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.09290933
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[about_me.txt]" time="0.250"><properties><property name="score" value="0.12622367" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15534_generated.txt]" time="0.752"><properties><property name="score" value="0.0347588965" /></properties><failure message="AssertionError: 2110.15534_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0347589 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15534_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0347589
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.07611_generated.txt]" time="0.596"><properties><property name="score" value="0.061398102999999996" /></properties><failure message="AssertionError: 2111.07611_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0613981 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.07611_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.0613981
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.13658_generated.txt]" time="0.871"><properties><property name="score" value="0.052508727666666664" /></properties><failure message="AssertionError: 2110.13658_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.05250873 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.13658_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.05250873
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15725_generated.txt]" time="0.626"><properties><property name="score" value="0.0169836635" /></properties><failure message="AssertionError: 2110.15725_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01698366 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15725_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01698366
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01231_generated.txt]" time="0.719"><properties><property name="score" value="0.010363292333333333" /></properties><failure message="AssertionError: 2111.01231_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01036329 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.01231_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01036329
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.10319_generated.txt]" time="0.827"><properties><property name="score" value="0.15127230325000002" /></properties><failure message="AssertionError: 2110.10319_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.1512723 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.10319_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.1512723
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.01340_generated.txt]" time="0.602"><properties><property name="score" value="0.8639276155" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.07699_generated.txt]" time="0.899"><properties><property name="score" value="0.06010468176666667" /></properties><failure message="AssertionError: 2111.07699_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.06010468 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.07699_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.06010468
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15705_generated.txt]" time="0.924"><properties><property name="score" value="0.08672001666666668" /></properties><failure message="AssertionError: 2110.15705_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.08672002 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15705_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.08672002
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02844_generated.txt]" time="0.594"><properties><property name="score" value="0.011772622" /></properties><failure message="AssertionError: 2111.02844_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01177262 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02844_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.01177262
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.04130_generated.txt]" time="0.947"><properties><property name="score" value="0.076640639" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02259_generated.txt]" time="0.603"><properties><property name="score" value="0.0017987490000000005" /></properties><failure message="AssertionError: 2111.02259_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00179875 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.02259_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.00179875
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00180_generated.txt]" time="0.809"><properties><property name="score" value="0.7569970433333335" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.04574_generated.txt]" time="0.591"><properties><property name="score" value="0.0224713585" /></properties><failure message="AssertionError: 2111.04574_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02247136 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.04574_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02247136
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00808_generated.txt]" time="0.594"><properties><property name="score" value="0.024298633150000002" /></properties><failure message="AssertionError: 2111.00808_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02429863 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00808_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02429863
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.12765_generated.txt]" time="0.585"><properties><property name="score" value="0.061283506" /></properties><failure message="AssertionError: 2110.12765_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.06128351 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.12765_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.06128351
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.13229_generated.txt]" time="0.558"><properties><property name="score" value="0.0499929915" /></properties><failure message="AssertionError: 2110.13229_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.04999299 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.13229_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.04999299
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00554_generated.txt]" time="0.590"><properties><property name="score" value="0.946718975" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.11207_generated.txt]" time="0.542"><properties><property name="score" value="0.9393186065" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.00607_generated.txt]" time="0.903"><properties><property name="score" value="0.026271642" /></properties><failure message="AssertionError: 2111.00607_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02627164 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.00607_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02627164
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.07267_generated.txt]" time="0.558"><properties><property name="score" value="0.0501786855" /></properties><failure message="AssertionError: 2111.07267_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.05017869 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.07267_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.05017869
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.11205_generated.txt]" time="1.162"><properties><property name="score" value="0.46520230933333334" /></properties><failure message="AssertionError: 2110.11205_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.46520231 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.11205_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.46520231
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[bard_internet_abstract.txt]" time="0.259"><properties><property name="score" value="0.0024926302" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.03945_generated.txt]" time="0.785"><properties><property name="score" value="0.02875165925" /></properties><failure message="AssertionError: 2111.03945_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02875166 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2111.03945_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.02875166
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.12383_generated.txt]" time="0.573"><properties><property name="score" value="0.06655878550000001" /></properties><failure message="AssertionError: 2110.12383_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.06655879 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.12383_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.06655879
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2111.02362_generated.txt]" time="0.846"><properties><property name="score" value="0.034206400000000005" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_sample[2110.15799_generated.txt]" time="31.294"><properties><property name="score" value="0.04661863" /></properties><failure message="AssertionError: 2110.15799_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.04661863 assert 'Human' == 'AI' - AI + Human">E AssertionError: 2110.15799_generated.txt is an LLM-generated file, misclassified as human-generated with confidence 0.04661863
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_sample[bard_abstract.txt]" time="0.345"><properties><property name="score" value="0.048614237" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i0]" time="0.303"><properties><property name="score" value="0.023145905" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i1]" time="0.279"><properties><property name="score" value="0.019263774" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i2]" time="0.271"><properties><property name="score" value="0.18528832" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i3]" time="0.295"><properties><property name="score" value="0.0068261456" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i4]" time="0.287"><properties><property name="score" value="0.16161005" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i5]" time="0.268"><properties><property name="score" value="0.0024968137" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i6]" time="0.280"><properties><property name="score" value="0.00041733152" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i7]" time="0.274"><properties><property name="score" value="0.0047277096" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i8]" time="0.292"><properties><property name="score" value="0.055262186" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i9]" time="0.940"><properties><property name="score" value="0.0020913442" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i10]" time="0.316"><properties><property name="score" value="0.0006395562" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i11]" time="0.345"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i12]" time="0.951"><properties><property name="score" value="0.19756594" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i13]" time="0.265"><properties><property name="score" value="0.0630976" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i14]" time="0.526"><properties><property name="score" value="0.026667291000000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i15]" time="0.272"><properties><property name="score" value="0.1099085" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255027 (len: 694) is a human-generated sample, misclassified as AI-generated with confidence 0.1099085 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255027 (len: 694) is a human-generated sample, misclassified as AI-generated with confidence 0.1099085
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i16]" time="0.266"><properties><property name="score" value="0.013629241" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i17]" time="0.258"><properties><property name="score" value="0.040510647" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i18]" time="0.250"><properties><property name="score" value="0.0066113826" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i19]" time="0.269"><properties><property name="score" value="0.0111308375" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i20]" time="0.310"><properties><property name="score" value="0.000813231" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i21]" time="0.285"><properties><property name="score" value="0.0006883472" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i22]" time="0.271"><properties><property name="score" value="0.08149141" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i23]" time="0.277"><properties><property name="score" value="1.0925279" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255037 (len: 505) is a human-generated sample, misclassified as AI-generated with confidence 1.0925279 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255037 (len: 505) is a human-generated sample, misclassified as AI-generated with confidence 1.0925279
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i24]" time="0.366"><properties><property name="score" value="0.012558271" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i25]" time="0.261"><properties><property name="score" value="0.1149714" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i26]" time="0.300"><properties><property name="score" value="0.0021769998" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i27]" time="0.242"><properties><property name="score" value="0.058521617" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i28]" time="0.316"><properties><property name="score" value="0.011329408" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i29]" time="0.307"><properties><property name="score" value="0.195082175" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i30]" time="0.266"><properties><property name="score" value="0.0031491157" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i31]" time="0.557"><properties><property name="score" value="0.01572575" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i32]" time="0.262"><properties><property name="score" value="0.2377757" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i33]" time="0.420"><properties><property name="score" value="0.00245722735" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i34]" time="0.272"><properties><property name="score" value="0.18201885" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i35]" time="0.306"><properties><property name="score" value="0.0047551394" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i36]" time="0.255"><properties><property name="score" value="0.0005475703" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i37]" time="0.285"><properties><property name="score" value="0.034572845" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i38]" time="0.298"><properties><property name="score" value="0.0025545433" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i39]" time="0.266"><properties><property name="score" value="0.00244246425" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i40]" time="0.270"><properties><property name="score" value="0.025508251" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i41]" time="0.282"><properties><property name="score" value="0.04990731" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i42]" time="0.310"><properties><property name="score" value="0.06870315" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i43]" time="0.282"><properties><property name="score" value="0.015067308" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i44]" time="0.318"><properties><property name="score" value="0.0052888934" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i45]" time="0.271"><properties><property name="score" value="0.00102711" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i46]" time="0.269"><properties><property name="score" value="0.017415404" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i47]" time="0.263"><properties><property name="score" value="1.5787563" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255069 (len: 281) is a human-generated sample, misclassified as AI-generated with confidence 1.5787563 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255069 (len: 281) is a human-generated sample, misclassified as AI-generated with confidence 1.5787563
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i48]" time="0.277"><properties><property name="score" value="0.059069492" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i49]" time="0.277"><properties><property name="score" value="0.013458378" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i50]" time="0.306"><properties><property name="score" value="0.018949736" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i51]" time="0.346"><properties><property name="score" value="0.12964292" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i52]" time="0.270"><properties><property name="score" value="1.7995664" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255075 (len: 441) is a human-generated sample, misclassified as AI-generated with confidence 1.7995664 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255075 (len: 441) is a human-generated sample, misclassified as AI-generated with confidence 1.7995664
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i53]" time="0.245"><properties><property name="score" value="0.015468616" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i54]" time="0.273"><properties><property name="score" value="0.029801687" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i55]" time="0.284"><properties><property name="score" value="0.012386186" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i56]" time="0.293"><properties><property name="score" value="0.063634915" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i57]" time="0.270"><properties><property name="score" value="0.0013016127" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i58]" time="0.336"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i59]" time="0.247"><properties><property name="score" value="1.580169" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i60]" time="0.259"><properties><property name="score" value="0.0008670992" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i61]" time="0.256"><properties><property name="score" value="0.0075581474" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i62]" time="0.274"><properties><property name="score" value="0.008632196" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i63]" time="0.292"><properties><property name="score" value="0.014913887" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i64]" time="0.307"><properties><property name="score" value="0.0010819461" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i65]" time="0.275"><properties><property name="score" value="0.13266227" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i66]" time="0.273"><properties><property name="score" value="0.028135825" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i67]" time="0.335"><properties><property name="score" value="0.0032639315" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255096 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.00326393 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255096 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.00326393
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i68]" time="0.232"><properties><property name="score" value="0.010241641" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i69]" time="0.280"><properties><property name="score" value="0.0062801163" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i70]" time="0.288"><properties><property name="score" value="0.006865468" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i71]" time="0.275"><properties><property name="score" value="0.0075782663" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i72]" time="0.304"><properties><property name="score" value="0.88034695" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i73]" time="0.250"><properties><property name="score" value="0.10710192" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i74]" time="1.637"><properties><property name="score" value="0.003801745" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i75]" time="0.285"><properties><property name="score" value="0.012036735" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i76]" time="0.268"><properties><property name="score" value="0.0045987796" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i77]" time="0.246"><properties><property name="score" value="1.1378" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255109 (len: 630) is a human-generated sample, misclassified as AI-generated with confidence 1.1378 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255109 (len: 630) is a human-generated sample, misclassified as AI-generated with confidence 1.1378
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i78]" time="0.781"><properties><property name="score" value="0.0007291232" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i79]" time="0.252"><properties><property name="score" value="0.05275475" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i80]" time="0.264"><properties><property name="score" value="0.3483168" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i81]" time="0.567"><properties><property name="score" value="2.4172443500000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i82]" time="0.285"><properties><property name="score" value="0.049139023" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i83]" time="0.309"><properties><property name="score" value="0.0044670515" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i84]" time="0.881"><properties><property name="score" value="0.0705223" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i85]" time="0.600"><properties><property name="score" value="0.07632468" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i86]" time="0.368"><properties><property name="score" value="0.70513344" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255120 (len: 233) is a human-generated sample, misclassified as AI-generated with confidence 0.70513344 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255120 (len: 233) is a human-generated sample, misclassified as AI-generated with confidence 0.70513344
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i87]" time="0.293"><properties><property name="score" value="0.0791944" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i88]" time="0.305"><properties><property name="score" value="0.03862152" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i89]" time="0.287"><properties><property name="score" value="0.0056886463" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i90]" time="0.276"><properties><property name="score" value="0.04388072" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i91]" time="0.290"><properties><property name="score" value="0.32051075" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i92]" time="0.241"><properties><property name="score" value="0.005550662" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i93]" time="0.279"><properties><property name="score" value="0.0049075675" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i94]" time="0.304"><properties><property name="score" value="0.01870013" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i95]" time="0.367"><properties><property name="score" value="0.00042281795" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i96]" time="0.268"><properties><property name="score" value="0.006452934" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i97]" time="0.308"><properties><property name="score" value="0.0012445232" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i98]" time="0.607"><properties><property name="score" value="0.0786090598" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i99]" time="0.265"><properties><property name="score" value="0.0077091414" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i100]" time="0.312"><properties><property name="score" value="0.31392413" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i101]" time="0.270"><properties><property name="score" value="0.8402884" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255141 (len: 568) is a human-generated sample, misclassified as AI-generated with confidence 0.8402884 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255141 (len: 568) is a human-generated sample, misclassified as AI-generated with confidence 0.8402884
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i102]" time="0.309"><properties><property name="score" value="0.00198481975" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i103]" time="0.474"><properties><property name="score" value="0.003188525" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i104]" time="0.274"><properties><property name="score" value="0.006688232" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i105]" time="0.446"><properties><property name="score" value="0.052557718" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i106]" time="0.263"><properties><property name="score" value="0.56033325" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255146 (len: 377) is a human-generated sample, misclassified as AI-generated with confidence 0.56033325 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255146 (len: 377) is a human-generated sample, misclassified as AI-generated with confidence 0.56033325
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i107]" time="0.280"><properties><property name="score" value="0.3464634" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i108]" time="0.295"><properties><property name="score" value="0.085065894" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i109]" time="0.245"><properties><property name="score" value="0.0014663468" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i110]" time="0.271"><properties><property name="score" value="0.0070839934" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i111]" time="0.271"><properties><property name="score" value="0.00075657445" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i112]" time="0.423"><properties><property name="score" value="0.005287232" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i113]" time="0.285"><properties><property name="score" value="0.02956627" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i114]" time="0.286"><properties><property name="score" value="0.40160042" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i115]" time="0.307"><properties><property name="score" value="0.08802737" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i116]" time="0.319"><properties><property name="score" value="0.0094963415" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i117]" time="0.249"><properties><property name="score" value="0.011038529" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i118]" time="0.263"><properties><property name="score" value="0.11785018" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i119]" time="0.265"><properties><property name="score" value="0.046021445" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i120]" time="0.316"><properties><property name="score" value="0.013959742" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i121]" time="0.296"><properties><property name="score" value="0.011562321" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i122]" time="0.272"><properties><property name="score" value="0.0045636305" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i123]" time="0.534"><properties><property name="score" value="0.0451094295" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i124]" time="0.263"><properties><property name="score" value="0.0028258744" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i125]" time="0.345"><properties><property name="score" value="0.002814097" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i126]" time="0.323"><properties><property name="score" value="0.37980118" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i127]" time="0.332"><properties><property name="score" value="0.42238045" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255173 (len: 651) is a human-generated sample, misclassified as AI-generated with confidence 0.42238045 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255173 (len: 651) is a human-generated sample, misclassified as AI-generated with confidence 0.42238045
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i128]" time="0.266"><properties><property name="score" value="0.011588972" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i129]" time="0.291"><properties><property name="score" value="0.0067292894" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i130]" time="0.282"><properties><property name="score" value="0.12249864" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255177 (len: 292) is a human-generated sample, misclassified as AI-generated with confidence 0.12249864 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255177 (len: 292) is a human-generated sample, misclassified as AI-generated with confidence 0.12249864
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i131]" time="0.283"><properties><property name="score" value="0.04794226" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i132]" time="0.301"><properties><property name="score" value="0.00040940178" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i133]" time="0.243"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i134]" time="0.619"><properties><property name="score" value="0.0650378974" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i135]" time="0.241"><properties><property name="score" value="0.17043628" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i136]" time="0.261"><properties><property name="score" value="0.00046105205" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i137]" time="0.264"><properties><property name="score" value="2.3550572" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255184 (len: 257) is a human-generated sample, misclassified as AI-generated with confidence 2.3550572 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255184 (len: 257) is a human-generated sample, misclassified as AI-generated with confidence 2.3550572
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i138]" time="0.265"><properties><property name="score" value="0.19546673" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i139]" time="0.302"><properties><property name="score" value="0.0008514707" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i140]" time="3.310"><properties><property name="score" value="0.0210658275" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i141]" time="0.255"><properties><property name="score" value="0.49909198" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255189 (len: 445) is a human-generated sample, misclassified as AI-generated with confidence 0.49909198 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255189 (len: 445) is a human-generated sample, misclassified as AI-generated with confidence 0.49909198
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i142]" time="0.402"><properties><property name="score" value="0.0010315159" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i143]" time="0.259"><properties><property name="score" value="0.0007165208" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i144]" time="0.280"><properties><property name="score" value="0.012481817" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i145]" time="0.258"><properties><property name="score" value="0.00111971285" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i146]" time="0.238"><properties><property name="score" value="0.046643585" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i147]" time="0.273"><properties><property name="score" value="0.020529435" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i148]" time="0.248"><properties><property name="score" value="0.33487868" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i149]" time="0.269"><properties><property name="score" value="0.44353896" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255199 (len: 226) is a human-generated sample, misclassified as AI-generated with confidence 0.44353896 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255199 (len: 226) is a human-generated sample, misclassified as AI-generated with confidence 0.44353896
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i150]" time="0.322"><properties><property name="score" value="0.0130114285" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i151]" time="0.280"><properties><property name="score" value="0.0089862" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i152]" time="0.251"><properties><property name="score" value="0.0026495564" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i153]" time="0.263"><properties><property name="score" value="1.9264123" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i154]" time="0.251"><properties><property name="score" value="0.027317217" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i155]" time="0.269"><properties><property name="score" value="0.009906129" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i156]" time="0.319"><properties><property name="score" value="0.023449268" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i157]" time="0.226"><properties><property name="score" value="0.21731704" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i158]" time="0.280"><properties><property name="score" value="0.0015344599" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i159]" time="0.274"><properties><property name="score" value="0.041806996" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i160]" time="0.541"><properties><property name="score" value="0.37864862850000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i161]" time="0.274"><properties><property name="score" value="0.05825038" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i162]" time="0.294"><properties><property name="score" value="0.1161805" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i163]" time="0.247"><properties><property name="score" value="0.7699891" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i164]" time="0.277"><properties><property name="score" value="0.99160725" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i165]" time="0.276"><properties><property name="score" value="0.014537195" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i166]" time="0.527"><properties><property name="score" value="0.26459764700000005" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i167]" time="0.288"><properties><property name="score" value="0.7370826" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255222 (len: 894) is a human-generated sample, misclassified as AI-generated with confidence 0.7370826 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255222 (len: 894) is a human-generated sample, misclassified as AI-generated with confidence 0.7370826
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i168]" time="0.254"><properties><property name="score" value="0.058922302" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i169]" time="0.382"><properties><property name="score" value="0.0049779513" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i170]" time="0.251"><properties><property name="score" value="0.052312173" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i171]" time="0.568"><properties><property name="score" value="0.0156064465" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i172]" time="0.280"><properties><property name="score" value="0.00340137025" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i173]" time="0.279"><properties><property name="score" value="0.066233516" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i174]" time="0.274"><properties><property name="score" value="0.18116774" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i175]" time="0.316"><properties><property name="score" value="0.227802215" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255235 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.22780222 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255235 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.22780222
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i176]" time="0.316"><properties><property name="score" value="0.00228936015" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i177]" time="0.313"><properties><property name="score" value="0.11422751" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255237 (len: 749) is a human-generated sample, misclassified as AI-generated with confidence 0.11422751 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255237 (len: 749) is a human-generated sample, misclassified as AI-generated with confidence 0.11422751
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i178]" time="0.433"><properties><property name="score" value="0.0005854876" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i179]" time="0.244"><properties><property name="score" value="0.016097406" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i180]" time="0.545"><properties><property name="score" value="0.316301925" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i181]" time="0.268"><properties><property name="score" value="0.34423107" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255242 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.34423107 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255242 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.34423107
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i182]" time="0.523"><properties><property name="score" value="0.1140633214" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i183]" time="0.288"><properties><property name="score" value="0.0015061043" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i184]" time="0.282"><properties><property name="score" value="0.097219005" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i185]" time="0.270"><properties><property name="score" value="0.0949525" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i186]" time="0.265"><properties><property name="score" value="0.00944629" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i187]" time="0.296"><properties><property name="score" value="0.002846122" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i188]" time="0.330"><properties><property name="score" value="0.0074589984" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i189]" time="0.341"><properties><property name="score" value="0.00058250355" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i190]" time="0.281"><properties><property name="score" value="0.08660859" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255252 (len: 705) is a human-generated sample, misclassified as AI-generated with confidence 0.08660859 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255252 (len: 705) is a human-generated sample, misclassified as AI-generated with confidence 0.08660859
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i191]" time="0.272"><properties><property name="score" value="1.409682" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255253 (len: 349) is a human-generated sample, misclassified as AI-generated with confidence 1.409682 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255253 (len: 349) is a human-generated sample, misclassified as AI-generated with confidence 1.409682
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i192]" time="0.310"><properties><property name="score" value="1.0878683" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i193]" time="0.280"><properties><property name="score" value="0.23777142" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i194]" time="0.288"><properties><property name="score" value="0.0036887565" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i195]" time="0.289"><properties><property name="score" value="0.005106368" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i196]" time="0.377"><properties><property name="score" value="0.099287985" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i197]" time="0.355"><properties><property name="score" value="0.007640008" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i198]" time="0.348"><properties><property name="score" value="0.0255327765" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i199]" time="0.279"><properties><property name="score" value="0.37974587" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255263 (len: 456) is a human-generated sample, misclassified as AI-generated with confidence 0.37974587 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255263 (len: 456) is a human-generated sample, misclassified as AI-generated with confidence 0.37974587
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i200]" time="0.605"><properties><property name="score" value="0.0480362275" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255264 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.04803623 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255264 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.04803623
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i201]" time="0.295"><properties><property name="score" value="0.0024810978" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i202]" time="0.307"><properties><property name="score" value="0.0056527115" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i203]" time="0.264"><properties><property name="score" value="0.03990872" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i204]" time="0.291"><properties><property name="score" value="0.00238035435" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i205]" time="0.339"><properties><property name="score" value="0.47524732" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i206]" time="0.372"><properties><property name="score" value="0.2301029" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i207]" time="0.287"><properties><property name="score" value="0.026858883" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i208]" time="0.250"><properties><property name="score" value="0.008035559" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i209]" time="0.236"><properties><property name="score" value="0.050529055" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i210]" time="0.360"><properties><property name="score" value="0.019520292" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i211]" time="0.285"><properties><property name="score" value="0.01747727" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i212]" time="0.475"><properties><property name="score" value="0.00072638044" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i213]" time="0.266"><properties><property name="score" value="0.3392565" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i214]" time="0.288"><properties><property name="score" value="0.004121716" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i215]" time="0.268"><properties><property name="score" value="0.019832749" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i216]" time="0.308"><properties><property name="score" value="0.0026724305" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i217]" time="0.348"><properties><property name="score" value="0.02156213" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i218]" time="0.343"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i219]" time="0.300"><properties><property name="score" value="0.0014628879" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i220]" time="0.260"><properties><property name="score" value="0.10391177" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i221]" time="0.290"><properties><property name="score" value="0.007016764" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i222]" time="0.228"><properties><property name="score" value="0.12570946" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i223]" time="0.285"><properties><property name="score" value="0.031848967" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i224]" time="0.267"><properties><property name="score" value="0.0029193503" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i225]" time="0.317"><properties><property name="score" value="0.004647188" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i226]" time="0.245"><properties><property name="score" value="0.091569535" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i227]" time="0.320"><properties><property name="score" value="0.00065853475" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i228]" time="0.278"><properties><property name="score" value="0.01828911" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i229]" time="0.250"><properties><property name="score" value="0.0026782434" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i230]" time="0.331"><properties><property name="score" value="0.007974049" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i231]" time="0.388"><properties><property name="score" value="0.024382943" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i232]" time="0.318"><properties><property name="score" value="0.011625383" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i233]" time="0.272"><properties><property name="score" value="0.10771058" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i234]" time="0.329"><properties><property name="score" value="1.1030018" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i235]" time="0.336"><properties><property name="score" value="0.012298587" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i236]" time="0.259"><properties><property name="score" value="0.00187864235" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i237]" time="0.269"><properties><property name="score" value="0.25783563" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i238]" time="0.286"><properties><property name="score" value="0.0010009152" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i239]" time="0.381"><properties><property name="score" value="0.053680718" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i240]" time="0.296"><properties><property name="score" value="0.08470176" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i241]" time="0.285"><properties><property name="score" value="0.123043915" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i242]" time="0.279"><properties><property name="score" value="0.0016944314" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i243]" time="0.269"><properties><property name="score" value="0.011817534" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i244]" time="0.259"><properties><property name="score" value="0.02648468" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i245]" time="0.245"><properties><property name="score" value="0.02990245" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i246]" time="0.242"><properties><property name="score" value="0.00089340867" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i247]" time="0.225"><properties><property name="score" value="0.6724179" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i248]" time="0.374"><properties><property name="score" value="0.01578197" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i249]" time="0.268"><properties><property name="score" value="0.0005460206" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i250]" time="0.304"><properties><property name="score" value="0.12828326" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i251]" time="0.600"><properties><property name="score" value="1.1696942" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255322 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.1696942 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255322 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.1696942
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i252]" time="0.338"><properties><property name="score" value="0.44635257" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i253]" time="0.297"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i254]" time="0.293"><properties><property name="score" value="0.00327293225" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i255]" time="0.337"><properties><property name="score" value="0.003044549" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i256]" time="0.263"><properties><property name="score" value="1.3960693" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255330 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.3960693 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255330 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.3960693
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i257]" time="0.372"><properties><property name="score" value="0.00051983976" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i258]" time="0.352"><properties><property name="score" value="0.027607363" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i259]" time="0.279"><properties><property name="score" value="0.0010384442" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i260]" time="0.251"><properties><property name="score" value="0.039593767" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i261]" time="0.250"><properties><property name="score" value="0.0030526798" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i262]" time="0.312"><properties><property name="score" value="0.004969935" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i263]" time="0.751"><properties><property name="score" value="0.0491164025" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i264]" time="1.062"><properties><property name="score" value="0.20518526" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i265]" time="0.288"><properties><property name="score" value="0.008089237" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i266]" time="0.250"><properties><property name="score" value="0.0018192539" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i267]" time="0.265"><properties><property name="score" value="0.04346167" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i268]" time="0.297"><properties><property name="score" value="0.0018873896" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i269]" time="0.306"><properties><property name="score" value="0.00096619444" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i270]" time="0.670"><properties><property name="score" value="0.008437656500000001" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i271]" time="0.381"><properties><property name="score" value="0.010479351" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i272]" time="0.304"><properties><property name="score" value="0.1582459" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i273]" time="0.633"><properties><property name="score" value="0.14999369999999998" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255353 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.1499937 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255353 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.1499937
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i274]" time="0.310"><properties><property name="score" value="0.22735398" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i275]" time="0.282"><properties><property name="score" value="0.016049072" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i276]" time="0.320"><properties><property name="score" value="0.0006749471" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i277]" time="0.342"><properties><property name="score" value="0.0007215482" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i278]" time="0.666"><properties><property name="score" value="0.0027010732" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i279]" time="1.076"><properties><property name="score" value="0.008860507" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i280]" time="0.329"><properties><property name="score" value="0.5242696" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i281]" time="0.272"><properties><property name="score" value="0.03189567" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i282]" time="0.267"><properties><property name="score" value="0.04723486" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i283]" time="0.332"><properties><property name="score" value="0.160240295" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i284]" time="0.341"><properties><property name="score" value="0.0300238635" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i285]" time="0.331"><properties><property name="score" value="0.03758256" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i286]" time="0.345"><properties><property name="score" value="0.001966299" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i287]" time="0.288"><properties><property name="score" value="0.0005593504" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i288]" time="0.295"><properties><property name="score" value="0.0021363825" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i289]" time="0.323"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i290]" time="0.344"><properties><property name="score" value="0.11976309" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i291]" time="0.309"><properties><property name="score" value="0.011719006" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i292]" time="0.245"><properties><property name="score" value="0.16782688" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i293]" time="0.262"><properties><property name="score" value="0.015732756" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i294]" time="0.260"><properties><property name="score" value="0.2298506" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255379 (len: 293) is a human-generated sample, misclassified as AI-generated with confidence 0.2298506 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255379 (len: 293) is a human-generated sample, misclassified as AI-generated with confidence 0.2298506
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i295]" time="0.348"><properties><property name="score" value="0.00428398" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i296]" time="0.317"><properties><property name="score" value="0.054447856" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i297]" time="0.308"><properties><property name="score" value="0.0032971222" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i298]" time="0.337"><properties><property name="score" value="0.24770348" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i299]" time="0.345"><properties><property name="score" value="0.00249230025" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i300]" time="0.296"><properties><property name="score" value="0.432368935" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i301]" time="0.282"><properties><property name="score" value="0.99556" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255388 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.99556 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255388 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.99556
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i302]" time="0.248"><properties><property name="score" value="0.1788305" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i303]" time="0.261"><properties><property name="score" value="0.01365202" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i304]" time="0.299"><properties><property name="score" value="0.0011417944" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i305]" time="0.336"><properties><property name="score" value="0.237933515" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i306]" time="0.312"><properties><property name="score" value="0.09013274" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i307]" time="0.328"><properties><property name="score" value="0.040191103" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i308]" time="0.291"><properties><property name="score" value="0.6461015" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255397 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.6461015 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255397 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.6461015
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i309]" time="0.297"><properties><property name="score" value="0.08366137" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i310]" time="0.331"><properties><property name="score" value="0.0023973873" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i311]" time="0.308"><properties><property name="score" value="0.021042483" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i312]" time="0.262"><properties><property name="score" value="0.3244695" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i313]" time="0.264"><properties><property name="score" value="0.09488546" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i314]" time="0.379"><properties><property name="score" value="3.7256622" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255405 (len: 427) is a human-generated sample, misclassified as AI-generated with confidence 3.7256622 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255405 (len: 427) is a human-generated sample, misclassified as AI-generated with confidence 3.7256622
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i315]" time="0.257"><properties><property name="score" value="0.014234312" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i316]" time="0.255"><properties><property name="score" value="0.0031697522" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i317]" time="0.263"><properties><property name="score" value="0.01240015" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i318]" time="0.285"><properties><property name="score" value="0.006498887" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i319]" time="0.273"><properties><property name="score" value="0.029663028" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i320]" time="0.297"><properties><property name="score" value="0.06972358" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i321]" time="0.296"><properties><property name="score" value="0.0011558789" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i322]" time="0.268"><properties><property name="score" value="0.013340037" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255414 (len: 446) is a human-generated sample, misclassified as AI-generated with confidence 0.01334004 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255414 (len: 446) is a human-generated sample, misclassified as AI-generated with confidence 0.01334004
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i323]" time="0.546"><properties><property name="score" value="0.126639662" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i324]" time="0.300"><properties><property name="score" value="0.020505225" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i325]" time="0.342"><properties><property name="score" value="0.014899884" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i326]" time="0.284"><properties><property name="score" value="0.0028459583" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i327]" time="0.237"><properties><property name="score" value="0.4402018" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i328]" time="0.277"><properties><property name="score" value="0.0351965875" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i329]" time="0.282"><properties><property name="score" value="0.0009439933" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i330]" time="0.328"><properties><property name="score" value="0.4837174" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i331]" time="0.267"><properties><property name="score" value="0.015792297" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i332]" time="0.281"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i333]" time="0.260"><properties><property name="score" value="0.007658865" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i334]" time="0.232"><properties><property name="score" value="0.007503858" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i335]" time="0.359"><properties><property name="score" value="0.029867383" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i336]" time="0.285"><properties><property name="score" value="0.01527196" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i337]" time="0.290"><properties><property name="score" value="0.039305206" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i338]" time="0.315"><properties><property name="score" value="0.0016424913" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i339]" time="0.270"><properties><property name="score" value="0.0120202685" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i340]" time="0.265"><properties><property name="score" value="0.14480844" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255438 (len: 295) is a human-generated sample, misclassified as AI-generated with confidence 0.14480844 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255438 (len: 295) is a human-generated sample, misclassified as AI-generated with confidence 0.14480844
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i341]" time="0.298"><properties><property name="score" value="0.0008548122" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i342]" time="0.309"><properties><property name="score" value="0.0009002092" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i343]" time="0.303"><properties><property name="score" value="0.0029098007" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i344]" time="0.290"><properties><property name="score" value="0.0203195" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i345]" time="0.345"><properties><property name="score" value="0.00090210275" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i346]" time="0.339"><properties><property name="score" value="0.012620327" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i347]" time="0.321"><properties><property name="score" value="0.40129527" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i348]" time="0.374"><properties><property name="score" value="0.0011511039" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i349]" time="0.732"><properties><property name="score" value="1.1294210905" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255447 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.12942109 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255447 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.12942109
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i350]" time="0.282"><properties><property name="score" value="0.0113891325" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i351]" time="0.716"><properties><property name="score" value="0.0027870217" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i352]" time="0.355"><properties><property name="score" value="0.00426239475" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i353]" time="0.557"><properties><property name="score" value="0.0083547735" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i354]" time="0.544"><properties><property name="score" value="0.004036009" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i355]" time="0.590"><properties><property name="score" value="0.0422009825" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i356]" time="0.363"><properties><property name="score" value="0.0022586633" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i357]" time="0.623"><properties><property name="score" value="0.6819679999999999" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255456 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.681968 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255456 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.681968
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i358]" time="0.329"><properties><property name="score" value="0.0064174808" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i359]" time="0.389"><properties><property name="score" value="0.0071077617" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i360]" time="1.258"><properties><property name="score" value="0.00049658" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i361]" time="0.411"><properties><property name="score" value="0.053143453" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i362]" time="0.643"><properties><property name="score" value="0.046064526" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i363]" time="0.484"><properties><property name="score" value="0.0022646359" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i364]" time="0.456"><properties><property name="score" value="0.0016255016" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i365]" time="0.436"><properties><property name="score" value="0.0006318414" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i366]" time="0.509"><properties><property name="score" value="0.05365028" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i367]" time="0.424"><properties><property name="score" value="0.2378903" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i368]" time="0.466"><properties><property name="score" value="0.17154998" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i369]" time="0.467"><properties><property name="score" value="0.048543967" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i370]" time="0.435"><properties><property name="score" value="0.001689796" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i371]" time="0.376"><properties><property name="score" value="0.0024079639" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i372]" time="0.337"><properties><property name="score" value="0.060124945" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i373]" time="0.380"><properties><property name="score" value="0.011773267" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i374]" time="0.315"><properties><property name="score" value="0.09175212" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i375]" time="0.354"><properties><property name="score" value="0.0035569347" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i376]" time="0.365"><properties><property name="score" value="0.019268727" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i377]" time="0.693"><properties><property name="score" value="0.014105744500000001" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255481 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.01410574 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255481 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.01410574
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i378]" time="0.433"><properties><property name="score" value="0.0140661205" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i379]" time="0.320"><properties><property name="score" value="0.6230763" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255483 (len: 292) is a human-generated sample, misclassified as AI-generated with confidence 0.6230763 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255483 (len: 292) is a human-generated sample, misclassified as AI-generated with confidence 0.6230763
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i380]" time="0.305"><properties><property name="score" value="0.0014646441" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i381]" time="0.573"><properties><property name="score" value="0.0735117235" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i382]" time="0.282"><properties><property name="score" value="0.0030880747" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i383]" time="0.305"><properties><property name="score" value="0.038194215" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i384]" time="0.263"><properties><property name="score" value="0.010345462" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i385]" time="0.261"><properties><property name="score" value="0.0010679826" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i386]" time="0.292"><properties><property name="score" value="0.0007425153" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i387]" time="0.292"><properties><property name="score" value="0.0081381445" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i388]" time="0.339"><properties><property name="score" value="0.027095988" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i389]" time="0.502"><properties><property name="score" value="0.010001066999999999" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i390]" time="0.290"><properties><property name="score" value="0.0046793745" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i391]" time="0.267"><properties><property name="score" value="0.00239487735" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i392]" time="0.254"><properties><property name="score" value="0.021802004" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i393]" time="0.539"><properties><property name="score" value="0.52817945" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255503 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.52817945 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255503 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.52817945
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i394]" time="0.283"><properties><property name="score" value="0.038655158" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i395]" time="0.281"><properties><property name="score" value="0.004967287" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i396]" time="0.274"><properties><property name="score" value="0.013669664" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i397]" time="0.290"><properties><property name="score" value="0.045674764" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i398]" time="0.511"><properties><property name="score" value="0.0029928954" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i399]" time="0.275"><properties><property name="score" value="0.002843754" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i400]" time="0.291"><properties><property name="score" value="0.005245067" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i401]" time="0.294"><properties><property name="score" value="0.6159333" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i402]" time="0.266"><properties><property name="score" value="0.4591842" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255515 (len: 261) is a human-generated sample, misclassified as AI-generated with confidence 0.4591842 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255515 (len: 261) is a human-generated sample, misclassified as AI-generated with confidence 0.4591842
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i403]" time="0.329"><properties><property name="score" value="0.45912844" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i404]" time="0.329"><properties><property name="score" value="0.16351286" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i405]" time="0.453"><properties><property name="score" value="0.03641066" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i406]" time="0.315"><properties><property name="score" value="0.0032835472" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i407]" time="0.384"><properties><property name="score" value="0.06993488" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i408]" time="0.285"><properties><property name="score" value="1.12528765" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255521 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.12528765 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255521 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 1.12528765
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i409]" time="0.277"><properties><property name="score" value="0.0150839565" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i410]" time="0.259"><properties><property name="score" value="0.014243381" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i411]" time="0.325"><properties><property name="score" value="0.008774597" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i412]" time="0.284"><properties><property name="score" value="0.0022974934" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i413]" time="0.263"><properties><property name="score" value="0.05571542" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i414]" time="1.202"><properties><property name="score" value="0.0016196178" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i415]" time="0.493"><properties><property name="score" value="0.0064288797" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i416]" time="0.262"><properties><property name="score" value="0.023544507" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i417]" time="0.814"><properties><property name="score" value="0.08767543" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i418]" time="0.429"><properties><property name="score" value="0.0036552525" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i419]" time="0.302"><properties><property name="score" value="0.014368663" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i420]" time="0.284"><properties><property name="score" value="0.0013803964" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i421]" time="0.278"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i422]" time="0.256"><properties><property name="score" value="0.01771652" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i423]" time="1.079"><properties><property name="score" value="0.20464453" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i424]" time="0.274"><properties><property name="score" value="0.12686937" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i425]" time="0.265"><properties><property name="score" value="0.025635345" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i426]" time="0.290"><properties><property name="score" value="0.016511315" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i427]" time="0.258"><properties><property name="score" value="0.16414668" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i428]" time="0.284"><properties><property name="score" value="0.00066241425" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i429]" time="0.316"><properties><property name="score" value="0.012856415" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i430]" time="0.286"><properties><property name="score" value="0.004426294" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i431]" time="0.284"><properties><property name="score" value="0.81881124" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255548 (len: 475) is a human-generated sample, misclassified as AI-generated with confidence 0.81881124 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255548 (len: 475) is a human-generated sample, misclassified as AI-generated with confidence 0.81881124
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i432]" time="0.278"><properties><property name="score" value="0.00092842686" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i433]" time="0.288"><properties><property name="score" value="0.36840455" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i434]" time="0.303"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i435]" time="0.250"><properties><property name="score" value="0.03189567" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i436]" time="0.317"><properties><property name="score" value="0.001192519" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i437]" time="0.282"><properties><property name="score" value="0.11625689" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i438]" time="0.277"><properties><property name="score" value="0.5379715" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i439]" time="0.267"><properties><property name="score" value="0.067508385" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i440]" time="0.358"><properties><property name="score" value="0.0061227745" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i441]" time="0.257"><properties><property name="score" value="0.0232062415" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i442]" time="0.282"><properties><property name="score" value="0.0018891726" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i443]" time="0.274"><properties><property name="score" value="0.0024473355" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i444]" time="1.195"><properties><property name="score" value="0.0005688007" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i445]" time="0.292"><properties><property name="score" value="0.0006978098" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i446]" time="0.289"><properties><property name="score" value="0.0008183607" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i447]" time="0.289"><properties><property name="score" value="0.004504205" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i448]" time="0.257"><properties><property name="score" value="0.0037782248" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i449]" time="0.347"><properties><property name="score" value="0.015195646" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i450]" time="0.353"><properties><property name="score" value="0.0011687065" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i451]" time="0.299"><properties><property name="score" value="0.0067903185" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i452]" time="0.268"><properties><property name="score" value="0.0021572553" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i453]" time="0.275"><properties><property name="score" value="0.016172277" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i454]" time="0.298"><properties><property name="score" value="0.005548086" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i455]" time="0.363"><properties><property name="score" value="0.0013514466" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i456]" time="0.282"><properties><property name="score" value="2.3784776" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255581 (len: 703) is a human-generated sample, misclassified as AI-generated with confidence 2.3784776 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255581 (len: 703) is a human-generated sample, misclassified as AI-generated with confidence 2.3784776
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i457]" time="0.298"><properties><property name="score" value="0.019419646" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i458]" time="0.293"><properties><property name="score" value="0.005989435" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i459]" time="0.558"><properties><property name="score" value="0.27065353200000003" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255584 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.27065353 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255584 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.27065353
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i460]" time="0.299"><properties><property name="score" value="0.0087006055" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i461]" time="0.350"><properties><property name="score" value="0.03435847" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i462]" time="0.373"><properties><property name="score" value="0.00833538" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i463]" time="0.318"><properties><property name="score" value="1.1419333" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255588 (len: 436) is a human-generated sample, misclassified as AI-generated with confidence 1.1419333 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255588 (len: 436) is a human-generated sample, misclassified as AI-generated with confidence 1.1419333
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i464]" time="0.333"><properties><property name="score" value="0.009792213" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i465]" time="0.308"><properties><property name="score" value="0.0113267265" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i466]" time="0.353"><properties><property name="score" value="0.8047494" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255591 (len: 628) is a human-generated sample, misclassified as AI-generated with confidence 0.8047494 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255591 (len: 628) is a human-generated sample, misclassified as AI-generated with confidence 0.8047494
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i467]" time="0.316"><properties><property name="score" value="0.0007835837" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i468]" time="0.379"><properties><property name="score" value="0.026164448" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i469]" time="0.359"><properties><property name="score" value="0.0049738763" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i470]" time="0.336"><properties><property name="score" value="0.00065056745" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i471]" time="0.330"><properties><property name="score" value="0.0069130487" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i472]" time="0.291"><properties><property name="score" value="0.0031376295" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i473]" time="0.317"><properties><property name="score" value="0.0014975072" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i474]" time="0.318"><properties><property name="score" value="0.5911868" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255600 (len: 331) is a human-generated sample, misclassified as AI-generated with confidence 0.5911868 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255600 (len: 331) is a human-generated sample, misclassified as AI-generated with confidence 0.5911868
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i475]" time="0.345"><properties><property name="score" value="0.17167239" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255601 (len: 301) is a human-generated sample, misclassified as AI-generated with confidence 0.17167239 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255601 (len: 301) is a human-generated sample, misclassified as AI-generated with confidence 0.17167239
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i476]" time="0.419"><properties><property name="score" value="0.048529577" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i477]" time="0.283"><properties><property name="score" value="0.31322575" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255604 (len: 200) is a human-generated sample, misclassified as AI-generated with confidence 0.31322575 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255604 (len: 200) is a human-generated sample, misclassified as AI-generated with confidence 0.31322575
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i478]" time="0.300"><properties><property name="score" value="0.22104195" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i479]" time="0.257"><properties><property name="score" value="0.049417462" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i480]" time="0.309"><properties><property name="score" value="0.0027223504" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i481]" time="0.310"><properties><property name="score" value="0.05867817" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i482]" time="0.345"><properties><property name="score" value="0.00173438455" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i483]" time="0.423"><properties><property name="score" value="0.042437762" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i484]" time="0.338"><properties><property name="score" value="0.018249892" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i485]" time="0.328"><properties><property name="score" value="0.0045988997" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i486]" time="0.343"><properties><property name="score" value="0.0066970215" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i487]" time="0.372"><properties><property name="score" value="0.011583425" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255620 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.01158342 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255620 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.01158342
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i488]" time="0.323"><properties><property name="score" value="0.19108593" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i489]" time="0.297"><properties><property name="score" value="0.0038238175" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i490]" time="0.310"><properties><property name="score" value="0.0032955513" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i491]" time="0.314"><properties><property name="score" value="0.0098094715" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i492]" time="0.277"><properties><property name="score" value="0.037091047" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i493]" time="0.290"><properties><property name="score" value="0.004799038" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i494]" time="0.251"><properties><property name="score" value="0.16406822" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255630 (len: 252) is a human-generated sample, misclassified as AI-generated with confidence 0.16406822 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255630 (len: 252) is a human-generated sample, misclassified as AI-generated with confidence 0.16406822
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i495]" time="0.295"><properties><property name="score" value="0.30238875" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255632 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.30238875 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255632 (len: 1024) is a human-generated sample, misclassified as AI-generated with confidence 0.30238875
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i496]" time="0.281"><properties><property name="score" value="0.018229742" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i497]" time="0.264"><properties><property name="score" value="1.2581125" /></properties><failure message="AssertionError: samples/webtext.test.jsonl:255634 (len: 606) is a human-generated sample, misclassified as AI-generated with confidence 1.2581125 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/webtext.test.jsonl:255634 (len: 606) is a human-generated sample, misclassified as AI-generated with confidence 1.2581125
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i498]" time="0.260"><properties><property name="score" value="0.0069723474" /></properties></testcase><testcase classname="test_openai_detect" name="test_human_jsonl[i499]" time="0.363"><properties><property name="score" value="0.0040989066" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i0]" time="0.267"><properties><property name="score" value="0.0027013125" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255002 (text: People carry a memorial sign to honor Robert Paxto) is an LLM-generated sample, misclassified as human-generated with confidence 0.00270131 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255002 (text: People carry a memorial sign to honor Robert Paxto) is an LLM-generated sample, misclassified as human-generated with confidence 0.00270131
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i1]" time="0.251"><properties><property name="score" value="0.035544638" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255003 (text: Google is launching a new scholarship campaign for) is an LLM-generated sample, misclassified as human-generated with confidence 0.03554464 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255003 (text: Google is launching a new scholarship campaign for) is an LLM-generated sample, misclassified as human-generated with confidence 0.03554464
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i2]" time="0.363"><properties><property name="score" value="0.19028887" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i3]" time="0.297"><properties><property name="score" value="0.19029765" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i4]" time="0.270"><properties><property name="score" value="0.016327059" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255006 (text: ISIS is breeding from among the refugees forced ou) is an LLM-generated sample, misclassified as human-generated with confidence 0.01632706 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255006 (text: ISIS is breeding from among the refugees forced ou) is an LLM-generated sample, misclassified as human-generated with confidence 0.01632706
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i5]" time="0.314"><properties><property name="score" value="0.71272707" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i6]" time="0.308"><properties><property name="score" value="0.00088851544" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255008 (text: © Provided by Texas State Historical Association' ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00088852 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255008 (text: © Provided by Texas State Historical Association' ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00088852
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i7]" time="0.563"><properties><property name="score" value="0.015645305" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i8]" time="0.339"><properties><property name="score" value="0.04341305" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255010 (text: Bots and AI are everywhere these days, and it's no) is an LLM-generated sample, misclassified as human-generated with confidence 0.04341305 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255010 (text: Bots and AI are everywhere these days, and it's no) is an LLM-generated sample, misclassified as human-generated with confidence 0.04341305
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i9]" time="0.275"><properties><property name="score" value="0.096550584" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i10]" time="0.289"><properties><property name="score" value="0.004519382" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255012 (text: Dr. Karl Widerquist says his study "opens up an in) is an LLM-generated sample, misclassified as human-generated with confidence 0.00451938 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255012 (text: Dr. Karl Widerquist says his study "opens up an in) is an LLM-generated sample, misclassified as human-generated with confidence 0.00451938
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i11]" time="0.325"><properties><property name="score" value="0.09833342" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i12]" time="0.243"><properties><property name="score" value="0.0021957597" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255015 (text: CALGARY — Tory MP Mac Harb resigned from the Conse) is an LLM-generated sample, misclassified as human-generated with confidence 0.00219576 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255015 (text: CALGARY — Tory MP Mac Harb resigned from the Conse) is an LLM-generated sample, misclassified as human-generated with confidence 0.00219576
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i13]" time="0.299"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255016 (text: SERVO, Jupiter - Since the discovery of the swirli) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255016 (text: SERVO, Jupiter - Since the discovery of the swirli) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i14]" time="0.287"><properties><property name="score" value="0.058245547" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i15]" time="0.259"><properties><property name="score" value="0.003053159" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255019 (text: PITTSBURGH, Aug. 15, 2013 /PRNewswire/ -- The Nati) is an LLM-generated sample, misclassified as human-generated with confidence 0.00305316 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255019 (text: PITTSBURGH, Aug. 15, 2013 /PRNewswire/ -- The Nati) is an LLM-generated sample, misclassified as human-generated with confidence 0.00305316
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i16]" time="0.332"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255020 (text: Albert Einstein, one of the world's most famous sc) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255020 (text: Albert Einstein, one of the world's most famous sc) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i17]" time="0.310"><properties><property name="score" value="0.377493085" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i18]" time="0.281"><properties><property name="score" value="0.34374732" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i19]" time="0.310"><properties><property name="score" value="0.020837525" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i20]" time="0.281"><properties><property name="score" value="0.088077395" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i21]" time="0.267"><properties><property name="score" value="0.054268237" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255025 (text: Convicted cop killer should spend more time in jai) is an LLM-generated sample, misclassified as human-generated with confidence 0.05426824 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255025 (text: Convicted cop killer should spend more time in jai) is an LLM-generated sample, misclassified as human-generated with confidence 0.05426824
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i22]" time="0.294"><properties><property name="score" value="0.14252894" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i23]" time="0.277"><properties><property name="score" value="0.12127983" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i24]" time="0.265"><properties><property name="score" value="0.17284635" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i25]" time="0.260"><properties><property name="score" value="0.19538642" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255031 (text: A small group of Soviet "Oh-On's" fled North Vietn) is an LLM-generated sample, misclassified as human-generated with confidence 0.19538642 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255031 (text: A small group of Soviet "Oh-On's" fled North Vietn) is an LLM-generated sample, misclassified as human-generated with confidence 0.19538642
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i26]" time="0.234"><properties><property name="score" value="0.0010714434" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255033 (text: PALLBRIDGE, Mass. -- The New Hampshire Department ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00107144 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255033 (text: PALLBRIDGE, Mass. -- The New Hampshire Department ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00107144
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i27]" time="0.248"><properties><property name="score" value="0.007500314" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255035 (text: Speaker Paul Ryan Paul Davis RyanHouse passes reso) is an LLM-generated sample, misclassified as human-generated with confidence 0.00750031 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255035 (text: Speaker Paul Ryan Paul Davis RyanHouse passes reso) is an LLM-generated sample, misclassified as human-generated with confidence 0.00750031
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i28]" time="0.335"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255036 (text: To revisit an idea that a writer once put forth in) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255036 (text: To revisit an idea that a writer once put forth in) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i29]" time="0.268"><properties><property name="score" value="0.0006379849" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255037 (text: Jimmy Pastore worked his way up from the lightweig) is an LLM-generated sample, misclassified as human-generated with confidence 0.00063798 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255037 (text: Jimmy Pastore worked his way up from the lightweig) is an LLM-generated sample, misclassified as human-generated with confidence 0.00063798
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i30]" time="0.370"><properties><property name="score" value="0.30481812" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255039 (text: The Republican-led legislature will not appoint a ) is an LLM-generated sample, misclassified as human-generated with confidence 0.30481812 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255039 (text: The Republican-led legislature will not appoint a ) is an LLM-generated sample, misclassified as human-generated with confidence 0.30481812
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i31]" time="0.284"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255040 (text: http://tvtropes.org/pmwiki/pmwiki.php/Main/Dunes ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255040 (text: http://tvtropes.org/pmwiki/pmwiki.php/Main/Dunes ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i32]" time="0.266"><properties><property name="score" value="0.09371958" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255041 (text: You have a choice when your four year old gets to ) is an LLM-generated sample, misclassified as human-generated with confidence 0.09371958 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255041 (text: You have a choice when your four year old gets to ) is an LLM-generated sample, misclassified as human-generated with confidence 0.09371958
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i33]" time="0.319"><properties><property name="score" value="0.06809631" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i34]" time="0.258"><properties><property name="score" value="0.8379105" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i35]" time="0.285"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255045 (text: Fear that mirrors a changing political dynamic in ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255045 (text: Fear that mirrors a changing political dynamic in ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i36]" time="0.261"><properties><property name="score" value="0.21163192" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i37]" time="0.263"><properties><property name="score" value="1.6815265" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i38]" time="0.295"><properties><property name="score" value="0.166641025" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i39]" time="0.245"><properties><property name="score" value="0.011271003" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255049 (text: Watch Rick Santorum's full interview with Glenn Be) is an LLM-generated sample, misclassified as human-generated with confidence 0.011271 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255049 (text: Watch Rick Santorum's full interview with Glenn Be) is an LLM-generated sample, misclassified as human-generated with confidence 0.011271
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i40]" time="0.303"><properties><property name="score" value="0.0020966588" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255050 (text: Passengers and regulators round up illegal drugs d) is an LLM-generated sample, misclassified as human-generated with confidence 0.00209666 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255050 (text: Passengers and regulators round up illegal drugs d) is an LLM-generated sample, misclassified as human-generated with confidence 0.00209666
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i41]" time="0.272"><properties><property name="score" value="0.06779383" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i42]" time="0.286"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255053 (text: 2000 Year Oro Jackson The tomb was previously ide) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255053 (text: 2000 Year Oro Jackson The tomb was previously ide) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i43]" time="0.286"><properties><property name="score" value="0.007875523" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255055 (text: Despite offering three levels of adaptive service,) is an LLM-generated sample, misclassified as human-generated with confidence 0.00787552 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255055 (text: Despite offering three levels of adaptive service,) is an LLM-generated sample, misclassified as human-generated with confidence 0.00787552
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i44]" time="0.272"><properties><property name="score" value="2.0770736" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i45]" time="0.259"><properties><property name="score" value="0.06856507" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i46]" time="0.286"><properties><property name="score" value="0.31269073" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i47]" time="0.669"><properties><property name="score" value="0.026025906" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i48]" time="0.264"><properties><property name="score" value="0.027522136" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255062 (text: Saturday, 13 February 2015 (CNW Group/Black Wit ) is an LLM-generated sample, misclassified as human-generated with confidence 0.02752214 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255062 (text: Saturday, 13 February 2015 (CNW Group/Black Wit ) is an LLM-generated sample, misclassified as human-generated with confidence 0.02752214
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i49]" time="0.259"><properties><property name="score" value="0.06903698" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255063 (text: Sorting, Pricing, and Reviews iOS UK: who product) is an LLM-generated sample, misclassified as human-generated with confidence 0.06903698 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255063 (text: Sorting, Pricing, and Reviews iOS UK: who product) is an LLM-generated sample, misclassified as human-generated with confidence 0.06903698
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i50]" time="0.278"><properties><property name="score" value="0.8348473" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i51]" time="0.405"><properties><property name="score" value="0.258010985" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i52]" time="0.305"><properties><property name="score" value="0.0223698915" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i53]" time="0.305"><properties><property name="score" value="0.20448783" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i54]" time="0.312"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255068 (text: Generic and other online electric curbside meter s) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255068 (text: Generic and other online electric curbside meter s) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i55]" time="0.308"><properties><property name="score" value="0.022841502" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i56]" time="0.270"><properties><property name="score" value="0.016185056" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i57]" time="0.308"><properties><property name="score" value="0.008060273" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255071 (text: Caught on videotape: New DOJ agents claim they wip) is an LLM-generated sample, misclassified as human-generated with confidence 0.00806027 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255071 (text: Caught on videotape: New DOJ agents claim they wip) is an LLM-generated sample, misclassified as human-generated with confidence 0.00806027
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i58]" time="0.380"><properties><property name="score" value="0.0020610031" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255072 (text: Russia is banning imports of chicken and pork from) is an LLM-generated sample, misclassified as human-generated with confidence 0.002061 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255072 (text: Russia is banning imports of chicken and pork from) is an LLM-generated sample, misclassified as human-generated with confidence 0.002061
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i59]" time="0.299"><properties><property name="score" value="0.0359615125" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i60]" time="0.291"><properties><property name="score" value="0.03284395" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i61]" time="0.346"><properties><property name="score" value="0.8257674" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i62]" time="0.327"><properties><property name="score" value="0.48832607" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i63]" time="0.267"><properties><property name="score" value="2.8102057" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i64]" time="0.295"><properties><property name="score" value="0.039090667" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255081 (text: The Guo's had been waiting for about 7 hours in th) is an LLM-generated sample, misclassified as human-generated with confidence 0.03909067 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255081 (text: The Guo's had been waiting for about 7 hours in th) is an LLM-generated sample, misclassified as human-generated with confidence 0.03909067
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i65]" time="0.357"><properties><property name="score" value="0.39178446" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255082 (text: Method 1: Get the Pro graphic card rollover report) is an LLM-generated sample, misclassified as human-generated with confidence 0.39178446 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255082 (text: Method 1: Get the Pro graphic card rollover report) is an LLM-generated sample, misclassified as human-generated with confidence 0.39178446
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i66]" time="0.332"><properties><property name="score" value="0.46080375" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i67]" time="0.280"><properties><property name="score" value="0.41325262" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i68]" time="0.304"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255086 (text: Like the others, I started with a Retina MacBook P) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255086 (text: Like the others, I started with a Retina MacBook P) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i69]" time="0.301"><properties><property name="score" value="0.7652617" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i70]" time="0.287"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255088 (text: Share. From games to Funko and MORE. From games to) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255088 (text: Share. From games to Funko and MORE. From games to) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i71]" time="0.259"><properties><property name="score" value="0.46536553" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i72]" time="0.363"><properties><property name="score" value="0.2472972" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i73]" time="0.273"><properties><property name="score" value="0.4970537" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i74]" time="0.396"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255093 (text: Infowars.com December 16, 2015 John McCain react) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255093 (text: Infowars.com December 16, 2015 John McCain react) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i75]" time="0.316"><properties><property name="score" value="0.6470274" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i76]" time="0.290"><properties><property name="score" value="0.016355475" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255095 (text: ROME (Reuters) - Italian Prime Minister Matteo Ren) is an LLM-generated sample, misclassified as human-generated with confidence 0.01635548 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255095 (text: ROME (Reuters) - Italian Prime Minister Matteo Ren) is an LLM-generated sample, misclassified as human-generated with confidence 0.01635548
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i77]" time="0.294"><properties><property name="score" value="0.33011735" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i78]" time="0.305"><properties><property name="score" value="1.3662349" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i79]" time="0.345"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255100 (text: Recovery initiated after Opwell has been confirmed) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255100 (text: Recovery initiated after Opwell has been confirmed) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i80]" time="0.272"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255101 (text: Burbank, CA Duration of studio: 9 - 14 hours. Co) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255101 (text: Burbank, CA Duration of studio: 9 - 14 hours. Co) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i81]" time="0.267"><properties><property name="score" value="0.1462805" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i82]" time="0.261"><properties><property name="score" value="0.014365215" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255106 (text: The entrance to the Werribee apartment block in we) is an LLM-generated sample, misclassified as human-generated with confidence 0.01436522 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255106 (text: The entrance to the Werribee apartment block in we) is an LLM-generated sample, misclassified as human-generated with confidence 0.01436522
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i83]" time="0.273"><properties><property name="score" value="0.00967649" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255107 (text: Acclaimed biomedical researcher Michael Stanton, P) is an LLM-generated sample, misclassified as human-generated with confidence 0.00967649 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255107 (text: Acclaimed biomedical researcher Michael Stanton, P) is an LLM-generated sample, misclassified as human-generated with confidence 0.00967649
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i84]" time="0.570"><properties><property name="score" value="0.209629235" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i85]" time="0.273"><properties><property name="score" value="0.01249931" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255109 (text: Baby will make $740 per week during summer holiday) is an LLM-generated sample, misclassified as human-generated with confidence 0.01249931 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255109 (text: Baby will make $740 per week during summer holiday) is an LLM-generated sample, misclassified as human-generated with confidence 0.01249931
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i86]" time="0.253"><properties><property name="score" value="0.058134865" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255110 (text: That 1993 election always weighs on me. For the fi) is an LLM-generated sample, misclassified as human-generated with confidence 0.05813487 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255110 (text: That 1993 election always weighs on me. For the fi) is an LLM-generated sample, misclassified as human-generated with confidence 0.05813487
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i87]" time="0.256"><properties><property name="score" value="0.003974489" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255111 (text: Everton transfer target Victor Wanyama ruffled Che) is an LLM-generated sample, misclassified as human-generated with confidence 0.00397449 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255111 (text: Everton transfer target Victor Wanyama ruffled Che) is an LLM-generated sample, misclassified as human-generated with confidence 0.00397449
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i88]" time="0.369"><properties><property name="score" value="0.14715804" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i89]" time="0.314"><properties><property name="score" value="3.156895" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i90]" time="0.321"><properties><property name="score" value="0.29429653" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i91]" time="0.492"><properties><property name="score" value="0.05637046" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i92]" time="0.249"><properties><property name="score" value="0.041445408" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i93]" time="0.365"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255118 (text: When things go horribly wrong in an emergency, the) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255118 (text: When things go horribly wrong in an emergency, the) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i94]" time="0.257"><properties><property name="score" value="0.08370995" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255119 (text: Pep Guardiola has hinted that the Manchester City ) is an LLM-generated sample, misclassified as human-generated with confidence 0.08370995 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255119 (text: Pep Guardiola has hinted that the Manchester City ) is an LLM-generated sample, misclassified as human-generated with confidence 0.08370995
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i95]" time="0.261"><properties><property name="score" value="0.08059216" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255120 (text: To be slugged on deductibles of over $6,500 annual) is an LLM-generated sample, misclassified as human-generated with confidence 0.08059216 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255120 (text: To be slugged on deductibles of over $6,500 annual) is an LLM-generated sample, misclassified as human-generated with confidence 0.08059216
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i96]" time="0.288"><properties><property name="score" value="0.0115771545" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i97]" time="0.343"><properties><property name="score" value="0.00091733114" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255122 (text: Wilson's comments about gay relationships also inj) is an LLM-generated sample, misclassified as human-generated with confidence 0.00091733 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255122 (text: Wilson's comments about gay relationships also inj) is an LLM-generated sample, misclassified as human-generated with confidence 0.00091733
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i98]" time="0.342"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255123 (text: Turing Pharmaceuticals has agreed in principle to ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255123 (text: Turing Pharmaceuticals has agreed in principle to ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i99]" time="0.312"><properties><property name="score" value="0.2350799" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255127 (text: SAN FRANCISCO — Opportunities to test the effectiv) is an LLM-generated sample, misclassified as human-generated with confidence 0.2350799 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255127 (text: SAN FRANCISCO — Opportunities to test the effectiv) is an LLM-generated sample, misclassified as human-generated with confidence 0.2350799
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i100]" time="0.308"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255129 (text: "I always say to them: 'Pray for our nation and fa) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255129 (text: "I always say to them: 'Pray for our nation and fa) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i101]" time="0.585"><properties><property name="score" value="0.1389971" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255130 (text: CBIS Finance equipped farmers in Mangodong to impl) is an LLM-generated sample, misclassified as human-generated with confidence 0.1389971 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255130 (text: CBIS Finance equipped farmers in Mangodong to impl) is an LLM-generated sample, misclassified as human-generated with confidence 0.1389971
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i102]" time="0.262"><properties><property name="score" value="0.4372079" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255131 (text: A combination logo for DuPont, Inc. is seen in thi) is an LLM-generated sample, misclassified as human-generated with confidence 0.4372079 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255131 (text: A combination logo for DuPont, Inc. is seen in thi) is an LLM-generated sample, misclassified as human-generated with confidence 0.4372079
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i103]" time="0.284"><properties><property name="score" value="0.00294953725" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255132 (text: Harry Kane has reminded us of the fantastically da) is an LLM-generated sample, misclassified as human-generated with confidence 0.00294954 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255132 (text: Harry Kane has reminded us of the fantastically da) is an LLM-generated sample, misclassified as human-generated with confidence 0.00294954
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i104]" time="0.309"><properties><property name="score" value="0.038929775" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255134 (text: Thousands of women visited a new San Francisco cen) is an LLM-generated sample, misclassified as human-generated with confidence 0.03892977 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255134 (text: Thousands of women visited a new San Francisco cen) is an LLM-generated sample, misclassified as human-generated with confidence 0.03892977
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i105]" time="0.260"><properties><property name="score" value="0.14728618" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255135 (text: BCF GP Pro ACQ Team $10,000, 220+ Current Camp:) is an LLM-generated sample, misclassified as human-generated with confidence 0.14728618 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255135 (text: BCF GP Pro ACQ Team $10,000, 220+ Current Camp:) is an LLM-generated sample, misclassified as human-generated with confidence 0.14728618
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i106]" time="0.289"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255136 (text: "If you run for the White House and you want peopl) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255136 (text: "If you run for the White House and you want peopl) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i107]" time="0.305"><properties><property name="score" value="1.2293665" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i108]" time="0.279"><properties><property name="score" value="3.0977163" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i109]" time="0.262"><properties><property name="score" value="0.056789953" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i110]" time="0.404"><properties><property name="score" value="1.1529452" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i111]" time="0.392"><properties><property name="score" value="0.014796253" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255141 (text: SpaceX confirms all three have been arrested Copyr) is an LLM-generated sample, misclassified as human-generated with confidence 0.01479625 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255141 (text: SpaceX confirms all three have been arrested Copyr) is an LLM-generated sample, misclassified as human-generated with confidence 0.01479625
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i112]" time="0.289"><properties><property name="score" value="0.3318105" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i113]" time="0.320"><properties><property name="score" value="0.147950275" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i114]" time="1.782"><properties><property name="score" value="0.0043364814" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255144 (text: Don't trust fake news Help journalists by signing) is an LLM-generated sample, misclassified as human-generated with confidence 0.00433648 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255144 (text: Don't trust fake news Help journalists by signing) is an LLM-generated sample, misclassified as human-generated with confidence 0.00433648
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i115]" time="0.348"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255146 (text: Madden 18 Patch Notes - November 9th, 2018 Patch ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255146 (text: Madden 18 Patch Notes - November 9th, 2018 Patch ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i116]" time="0.322"><properties><property name="score" value="0.16617833" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i117]" time="0.285"><properties><property name="score" value="0.3639448" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i118]" time="0.305"><properties><property name="score" value="0.2852444" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i119]" time="0.276"><properties><property name="score" value="0.001489449" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255151 (text: Keyslinging. Driving fast on one side of a state l) is an LLM-generated sample, misclassified as human-generated with confidence 0.00148945 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255151 (text: Keyslinging. Driving fast on one side of a state l) is an LLM-generated sample, misclassified as human-generated with confidence 0.00148945
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i120]" time="0.281"><properties><property name="score" value="0.009052015" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255152 (text: 2014/07/16 02:23 SEOUL, July 15 (Yonhap) -- North) is an LLM-generated sample, misclassified as human-generated with confidence 0.00905202 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255152 (text: 2014/07/16 02:23 SEOUL, July 15 (Yonhap) -- North) is an LLM-generated sample, misclassified as human-generated with confidence 0.00905202
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i121]" time="0.329"><properties><property name="score" value="0.197672785" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i122]" time="0.276"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255154 (text: Was coddled when he was a kid, indifference that c) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255154 (text: Was coddled when he was a kid, indifference that c) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i123]" time="0.278"><properties><property name="score" value="0.14102997" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i124]" time="0.285"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255156 (text: Sweden's at a crossroads. Within the next two year) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255156 (text: Sweden's at a crossroads. Within the next two year) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i125]" time="0.254"><properties><property name="score" value="0.7758018" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i126]" time="0.288"><properties><property name="score" value="0.68311165" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i127]" time="0.997"><properties><property name="score" value="0.02586723" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i128]" time="0.285"><properties><property name="score" value="0.3979622" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i129]" time="0.310"><properties><property name="score" value="0.8711422" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255164 (text: BetaClient module describes how to send or receive) is an LLM-generated sample, misclassified as human-generated with confidence 0.8711422 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255164 (text: BetaClient module describes how to send or receive) is an LLM-generated sample, misclassified as human-generated with confidence 0.8711422
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i130]" time="1.001"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255165 (text: ZCZC MIATCPAT5 ALL TTAA00 KNHC DDHHMM BULLETIN Tro) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255165 (text: ZCZC MIATCPAT5 ALL TTAA00 KNHC DDHHMM BULLETIN Tro) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i131]" time="0.325"><properties><property name="score" value="0.20888638" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i132]" time="0.283"><properties><property name="score" value="0.17810683" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i133]" time="0.409"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255168 (text: Obama didn't plaster his office in Amsterdam with ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255168 (text: Obama didn't plaster his office in Amsterdam with ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i134]" time="0.283"><properties><property name="score" value="0.045025304" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255169 (text: IGF1 and PGC1α are key signaling targets during de) is an LLM-generated sample, misclassified as human-generated with confidence 0.0450253 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255169 (text: IGF1 and PGC1α are key signaling targets during de) is an LLM-generated sample, misclassified as human-generated with confidence 0.0450253
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i135]" time="0.279"><properties><property name="score" value="0.37321177" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255170 (text: One of the most frequently asked questions we rece) is an LLM-generated sample, misclassified as human-generated with confidence 0.37321177 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255170 (text: One of the most frequently asked questions we rece) is an LLM-generated sample, misclassified as human-generated with confidence 0.37321177
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i136]" time="0.396"><properties><property name="score" value="3.0703387" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i137]" time="0.363"><properties><property name="score" value="0.136191115" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i138]" time="0.266"><properties><property name="score" value="0.11562088" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i139]" time="0.257"><properties><property name="score" value="0.21325417" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i140]" time="0.263"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255175 (text: The Cabinet has agreed to back the introduction of) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255175 (text: The Cabinet has agreed to back the introduction of) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i141]" time="0.273"><properties><property name="score" value="0.14836995" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i142]" time="0.353"><properties><property name="score" value="0.17309791" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i143]" time="0.325"><properties><property name="score" value="0.29802468" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255179 (text: Job seekers applying to work in the UK under the S) is an LLM-generated sample, misclassified as human-generated with confidence 0.29802468 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255179 (text: Job seekers applying to work in the UK under the S) is an LLM-generated sample, misclassified as human-generated with confidence 0.29802468
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i144]" time="0.475"><properties><property name="score" value="0.26580385" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i145]" time="0.316"><properties><property name="score" value="0.0035673892" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255181 (text: The early years for the Dallas Stars were not a gr) is an LLM-generated sample, misclassified as human-generated with confidence 0.00356739 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255181 (text: The early years for the Dallas Stars were not a gr) is an LLM-generated sample, misclassified as human-generated with confidence 0.00356739
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i146]" time="0.256"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255183 (text: BOSTON (CBS) — Brandon McManus was just getting st) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255183 (text: BOSTON (CBS) — Brandon McManus was just getting st) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i147]" time="0.260"><properties><property name="score" value="0.1958537" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i148]" time="0.235"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255185 (text: Despite the fact that you operate at a statistical) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255185 (text: Despite the fact that you operate at a statistical) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i149]" time="0.261"><properties><property name="score" value="0.33961043" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i150]" time="0.259"><properties><property name="score" value="0.3537973" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i151]" time="0.287"><properties><property name="score" value="0.0017002518" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255188 (text: In an effort to rectify the problem, the FA has no) is an LLM-generated sample, misclassified as human-generated with confidence 0.00170025 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255188 (text: In an effort to rectify the problem, the FA has no) is an LLM-generated sample, misclassified as human-generated with confidence 0.00170025
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i152]" time="0.295"><properties><property name="score" value="0.202186035" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i153]" time="0.309"><properties><property name="score" value="0.5616305" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i154]" time="0.280"><properties><property name="score" value="0.177552985" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i155]" time="0.284"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255194 (text: By Hilbert Hagedoorn on: #2071 Hiroshi Matsuyama ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255194 (text: By Hilbert Hagedoorn on: #2071 Hiroshi Matsuyama ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i156]" time="0.297"><properties><property name="score" value="0.88029987" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255195 (text: The report said the town could do with enhancing i) is an LLM-generated sample, misclassified as human-generated with confidence 0.88029987 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255195 (text: The report said the town could do with enhancing i) is an LLM-generated sample, misclassified as human-generated with confidence 0.88029987
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i157]" time="0.279"><properties><property name="score" value="0.0010361812" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255196 (text: Sheldon Adelson, a powerful figure in Republican p) is an LLM-generated sample, misclassified as human-generated with confidence 0.00103618 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255196 (text: Sheldon Adelson, a powerful figure in Republican p) is an LLM-generated sample, misclassified as human-generated with confidence 0.00103618
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i158]" time="0.299"><properties><property name="score" value="0.16371034" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i159]" time="0.293"><properties><property name="score" value="0.1410911" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i160]" time="0.314"><properties><property name="score" value="0.1526219" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i161]" time="0.267"><properties><property name="score" value="0.3175997" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i162]" time="0.265"><properties><property name="score" value="0.007862186" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255202 (text: A Minnesota woman was arrested after she lied abou) is an LLM-generated sample, misclassified as human-generated with confidence 0.00786219 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255202 (text: A Minnesota woman was arrested after she lied abou) is an LLM-generated sample, misclassified as human-generated with confidence 0.00786219
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i163]" time="0.427"><properties><property name="score" value="0.13000357" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i164]" time="0.322"><properties><property name="score" value="0.09738017" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255204 (text: How do you like dragons with your black tea? Aust) is an LLM-generated sample, misclassified as human-generated with confidence 0.09738017 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255204 (text: How do you like dragons with your black tea? Aust) is an LLM-generated sample, misclassified as human-generated with confidence 0.09738017
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i165]" time="0.320"><properties><property name="score" value="0.052034803" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255205 (text: While on vacation in Europe, over his lunch, CEO S) is an LLM-generated sample, misclassified as human-generated with confidence 0.0520348 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255205 (text: While on vacation in Europe, over his lunch, CEO S) is an LLM-generated sample, misclassified as human-generated with confidence 0.0520348
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i166]" time="0.598"><properties><property name="score" value="0.05237256" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i167]" time="0.241"><properties><property name="score" value="0.01767284" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255207 (text: The Twins-Red Sox series opens Monday evening, and) is an LLM-generated sample, misclassified as human-generated with confidence 0.01767284 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255207 (text: The Twins-Red Sox series opens Monday evening, and) is an LLM-generated sample, misclassified as human-generated with confidence 0.01767284
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i168]" time="0.269"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255208 (text: Illustrating the latest advancements in plant rese) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255208 (text: Illustrating the latest advancements in plant rese) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i169]" time="0.278"><properties><property name="score" value="0.006567824" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255209 (text: This article first appeared on the Atlantic Counci) is an LLM-generated sample, misclassified as human-generated with confidence 0.00656782 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255209 (text: This article first appeared on the Atlantic Counci) is an LLM-generated sample, misclassified as human-generated with confidence 0.00656782
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i170]" time="0.294"><properties><property name="score" value="0.01650744" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255210 (text: GIANTS forward Will Hayward is on track to return ) is an LLM-generated sample, misclassified as human-generated with confidence 0.01650744 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255210 (text: GIANTS forward Will Hayward is on track to return ) is an LLM-generated sample, misclassified as human-generated with confidence 0.01650744
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i171]" time="0.291"><properties><property name="score" value="0.35236537" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i172]" time="0.275"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255213 (text: "Free Market" Startups At the Foundry, we've iden) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255213 (text: "Free Market" Startups At the Foundry, we've iden) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i173]" time="0.723"><properties><property name="score" value="0.3239196" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i174]" time="0.374"><properties><property name="score" value="0.0015038374" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255216 (text: Jay Gruden started his tenure as head coach of the) is an LLM-generated sample, misclassified as human-generated with confidence 0.00150384 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255216 (text: Jay Gruden started his tenure as head coach of the) is an LLM-generated sample, misclassified as human-generated with confidence 0.00150384
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i175]" time="0.299"><properties><property name="score" value="0.15984265" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i176]" time="0.279"><properties><property name="score" value="0.0074423053" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255218 (text: Rita Redstone, the head of Viacom (which owns MTV,) is an LLM-generated sample, misclassified as human-generated with confidence 0.00744231 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255218 (text: Rita Redstone, the head of Viacom (which owns MTV,) is an LLM-generated sample, misclassified as human-generated with confidence 0.00744231
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i177]" time="0.301"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255220 (text: ARC Pilot: 'I just felt like I had to say somethin) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255220 (text: ARC Pilot: 'I just felt like I had to say somethin) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i178]" time="0.362"><properties><property name="score" value="0.045267045" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255221 (text: It's a tough new season for the Seattle Seahawks, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.04526704 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255221 (text: It's a tough new season for the Seattle Seahawks, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.04526704
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i179]" time="0.272"><properties><property name="score" value="0.6074715" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255222 (text: 3.5.2 · Fixes a bug that was stopping some users f) is an LLM-generated sample, misclassified as human-generated with confidence 0.6074715 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255222 (text: 3.5.2 · Fixes a bug that was stopping some users f) is an LLM-generated sample, misclassified as human-generated with confidence 0.6074715
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i180]" time="0.317"><properties><property name="score" value="0.10222438" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i181]" time="0.302"><properties><property name="score" value="0.0044498113" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255225 (text: A great factoid about the Toronto Blue Jays is tha) is an LLM-generated sample, misclassified as human-generated with confidence 0.00444981 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255225 (text: A great factoid about the Toronto Blue Jays is tha) is an LLM-generated sample, misclassified as human-generated with confidence 0.00444981
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i182]" time="0.318"><properties><property name="score" value="0.022232058" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255226 (text: Decorative Morning Combs, aka Mohalla Curls or Dr) is an LLM-generated sample, misclassified as human-generated with confidence 0.02223206 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255226 (text: Decorative Morning Combs, aka Mohalla Curls or Dr) is an LLM-generated sample, misclassified as human-generated with confidence 0.02223206
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i183]" time="0.321"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255227 (text: The Temple and Factom Foundation are jointly annou) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255227 (text: The Temple and Factom Foundation are jointly annou) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i184]" time="0.277"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255229 (text: Another day, another cheer for Harry Potter and th) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255229 (text: Another day, another cheer for Harry Potter and th) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i185]" time="0.289"><properties><property name="score" value="0.0254837" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i186]" time="0.264"><properties><property name="score" value="0.035114497" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255232 (text: Ronda Rousey is getting ready for UFC 200. She'll ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0351145 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255232 (text: Ronda Rousey is getting ready for UFC 200. She'll ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0351145
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i187]" time="0.244"><properties><property name="score" value="0.008233156" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255233 (text: Heard it said at the White House: "Republicans and) is an LLM-generated sample, misclassified as human-generated with confidence 0.00823316 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255233 (text: Heard it said at the White House: "Republicans and) is an LLM-generated sample, misclassified as human-generated with confidence 0.00823316
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i188]" time="0.272"><properties><property name="score" value="0.060059182" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i189]" time="0.322"><properties><property name="score" value="0.03558265" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255235 (text: Story highlights Staffers plan to sign convention ) is an LLM-generated sample, misclassified as human-generated with confidence 0.03558265 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255235 (text: Story highlights Staffers plan to sign convention ) is an LLM-generated sample, misclassified as human-generated with confidence 0.03558265
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i190]" time="0.284"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255237 (text: William Ichigo Ragnarok stunned the New York Red B) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255237 (text: William Ichigo Ragnarok stunned the New York Red B) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i191]" time="0.282"><properties><property name="score" value="0.0016122478" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255238 (text: South Korean official confirms North Korea may lau) is an LLM-generated sample, misclassified as human-generated with confidence 0.00161225 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255238 (text: South Korean official confirms North Korea may lau) is an LLM-generated sample, misclassified as human-generated with confidence 0.00161225
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i192]" time="0.327"><properties><property name="score" value="2.41047" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i193]" time="0.280"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255240 (text: PATHOGEN SAFETY DATA SHEET - INFECTIOUS SUBSTANCES) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255240 (text: PATHOGEN SAFETY DATA SHEET - INFECTIOUS SUBSTANCES) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i194]" time="0.270"><properties><property name="score" value="0.0024726125" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255241 (text: Jadon Roethlisberger's rehab from eight surgeries ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00247261 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255241 (text: Jadon Roethlisberger's rehab from eight surgeries ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00247261
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i195]" time="0.227"><properties><property name="score" value="0.47418535" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255242 (text: As they did in Iowa, Michigan and Idaho, the PACs ) is an LLM-generated sample, misclassified as human-generated with confidence 0.47418535 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255242 (text: As they did in Iowa, Michigan and Idaho, the PACs ) is an LLM-generated sample, misclassified as human-generated with confidence 0.47418535
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i196]" time="0.307"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255244 (text: NANAIMO — Water-skiing security is a risky proposi) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255244 (text: NANAIMO — Water-skiing security is a risky proposi) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i197]" time="0.300"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255245 (text: The chronological order of magazine pages (left to) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255245 (text: The chronological order of magazine pages (left to) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i198]" time="0.540"><properties><property name="score" value="0.028855915" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i199]" time="0.362"><properties><property name="score" value="0.3243417" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i200]" time="0.576"><properties><property name="score" value="0.14101797" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255249 (text: Tall and thin, from the red cap to the light brown) is an LLM-generated sample, misclassified as human-generated with confidence 0.14101797 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255249 (text: Tall and thin, from the red cap to the light brown) is an LLM-generated sample, misclassified as human-generated with confidence 0.14101797
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i201]" time="0.886"><properties><property name="score" value="0.0083755925" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i202]" time="0.381"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255251 (text: DW: A word of advice to Indonesia with Akhmed Akhm) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255251 (text: DW: A word of advice to Indonesia with Akhmed Akhm) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i203]" time="0.620"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255255 (text: PERRY, Texas — Not long after the scheduled start ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255255 (text: PERRY, Texas — Not long after the scheduled start ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i204]" time="0.393"><properties><property name="score" value="0.0048985145" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255256 (text: Monthly Scouting Notes October 2017 Jonathan Eis) is an LLM-generated sample, misclassified as human-generated with confidence 0.00489851 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255256 (text: Monthly Scouting Notes October 2017 Jonathan Eis) is an LLM-generated sample, misclassified as human-generated with confidence 0.00489851
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i205]" time="0.374"><properties><property name="score" value="0.49591875" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i206]" time="0.372"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255258 (text: In order to complete Book Trailer email Sign-up No) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255258 (text: In order to complete Book Trailer email Sign-up No) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i207]" time="0.401"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255259 (text: An image of a critical energy source will be displ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255259 (text: An image of a critical energy source will be displ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i208]" time="0.441"><properties><property name="score" value="1.078006" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i209]" time="0.318"><properties><property name="score" value="0.1141081" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i210]" time="0.425"><properties><property name="score" value="0.005547966" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255262 (text: Nice to see your interest in rolling the GoBlock, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00554797 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255262 (text: Nice to see your interest in rolling the GoBlock, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00554797
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i211]" time="0.306"><properties><property name="score" value="0.064769045" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i212]" time="0.342"><properties><property name="score" value="0.28597453" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i213]" time="0.313"><properties><property name="score" value="0.39648798" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i214]" time="0.313"><properties><property name="score" value="0.0013513266" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255266 (text: Ellen Pao during trial. (Photo by Edmond Su / Staf) is an LLM-generated sample, misclassified as human-generated with confidence 0.00135133 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255266 (text: Ellen Pao during trial. (Photo by Edmond Su / Staf) is an LLM-generated sample, misclassified as human-generated with confidence 0.00135133
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i215]" time="0.299"><properties><property name="score" value="0.0024713576" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255268 (text: The Sampedro Wingtip triple medallion Alexander Mc) is an LLM-generated sample, misclassified as human-generated with confidence 0.00247136 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255268 (text: The Sampedro Wingtip triple medallion Alexander Mc) is an LLM-generated sample, misclassified as human-generated with confidence 0.00247136
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i216]" time="0.307"><properties><property name="score" value="0.09889611" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i217]" time="0.374"><properties><property name="score" value="0.19174069" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255270 (text: CHARLOTTE, N.C. (AP) — North Carolina's top electi) is an LLM-generated sample, misclassified as human-generated with confidence 0.19174069 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255270 (text: CHARLOTTE, N.C. (AP) — North Carolina's top electi) is an LLM-generated sample, misclassified as human-generated with confidence 0.19174069
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i218]" time="0.366"><properties><property name="score" value="0.32917008" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i219]" time="0.335"><properties><property name="score" value="0.0018414661" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255273 (text: RAW IMAGES | IMAGES | INTERACTIVES | VIDEOS | MARS) is an LLM-generated sample, misclassified as human-generated with confidence 0.00184147 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255273 (text: RAW IMAGES | IMAGES | INTERACTIVES | VIDEOS | MARS) is an LLM-generated sample, misclassified as human-generated with confidence 0.00184147
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i220]" time="0.338"><properties><property name="score" value="0.083415485" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i221]" time="0.339"><properties><property name="score" value="0.115054145" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i222]" time="0.395"><properties><property name="score" value="0.0009275111" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255279 (text: German astronaut Werner Lang, who spent seven mont) is an LLM-generated sample, misclassified as human-generated with confidence 0.00092751 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255279 (text: German astronaut Werner Lang, who spent seven mont) is an LLM-generated sample, misclassified as human-generated with confidence 0.00092751
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i223]" time="0.438"><properties><property name="score" value="0.0011839954" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255280 (text: A third Milwaukee Motor Speedway parking spot face) is an LLM-generated sample, misclassified as human-generated with confidence 0.001184 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255280 (text: A third Milwaukee Motor Speedway parking spot face) is an LLM-generated sample, misclassified as human-generated with confidence 0.001184
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i224]" time="0.462"><properties><property name="score" value="0.015764685" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i225]" time="0.731"><properties><property name="score" value="1.1658678" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i226]" time="0.396"><properties><property name="score" value="0.32831395" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i227]" time="0.481"><properties><property name="score" value="0.28831515" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255285 (text: Today's Kiwi currency thriving after long recessio) is an LLM-generated sample, misclassified as human-generated with confidence 0.28831515 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255285 (text: Today's Kiwi currency thriving after long recessio) is an LLM-generated sample, misclassified as human-generated with confidence 0.28831515
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i228]" time="0.432"><properties><property name="score" value="0.14709827" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i229]" time="0.473"><properties><property name="score" value="0.491361825" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i230]" time="0.500"><properties><property name="score" value="0.41496795" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i231]" time="0.548"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255290 (text: and/or neck design evolved with People to People i) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255290 (text: and/or neck design evolved with People to People i) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i232]" time="0.335"><properties><property name="score" value="0.31595537" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i233]" time="0.313"><properties><property name="score" value="0.26061375" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i234]" time="0.323"><properties><property name="score" value="0.2351761" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i235]" time="0.504"><properties><property name="score" value="0.2491647" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i236]" time="0.389"><properties><property name="score" value="0.0209727" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i237]" time="0.299"><properties><property name="score" value="0.013678123" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255297 (text: New 3-D printer shoots out bagels without help A ) is an LLM-generated sample, misclassified as human-generated with confidence 0.01367812 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255297 (text: New 3-D printer shoots out bagels without help A ) is an LLM-generated sample, misclassified as human-generated with confidence 0.01367812
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i238]" time="0.293"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255298 (text: Breaking News Emails Get breaking news alerts and ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255298 (text: Breaking News Emails Get breaking news alerts and ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i239]" time="0.319"><properties><property name="score" value="0.114036285" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i240]" time="0.320"><properties><property name="score" value="0.1294507" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255303 (text: Uber will make all future activities involving rid) is an LLM-generated sample, misclassified as human-generated with confidence 0.1294507 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255303 (text: Uber will make all future activities involving rid) is an LLM-generated sample, misclassified as human-generated with confidence 0.1294507
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i241]" time="0.402"><properties><property name="score" value="0.42350045" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i242]" time="0.373"><properties><property name="score" value="0.12395087" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255305 (text: Replica Tamiya Headlight Set Ceramic Motor Caps -) is an LLM-generated sample, misclassified as human-generated with confidence 0.12395087 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255305 (text: Replica Tamiya Headlight Set Ceramic Motor Caps -) is an LLM-generated sample, misclassified as human-generated with confidence 0.12395087
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i243]" time="0.484"><properties><property name="score" value="0.0014904045" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255306 (text: Solo Brewing Announces New Brewery in Oklahoma Cit) is an LLM-generated sample, misclassified as human-generated with confidence 0.0014904 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255306 (text: Solo Brewing Announces New Brewery in Oklahoma Cit) is an LLM-generated sample, misclassified as human-generated with confidence 0.0014904
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i244]" time="0.360"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255307 (text: a former Royal Navy submarine that survived in Nor) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255307 (text: a former Royal Navy submarine that survived in Nor) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i245]" time="0.353"><properties><property name="score" value="0.11876414" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i246]" time="0.415"><properties><property name="score" value="0.07887964" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i247]" time="0.420"><properties><property name="score" value="0.4691234" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i248]" time="0.381"><properties><property name="score" value="0.22272637" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i249]" time="0.366"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255312 (text: Activists working on smarter scale models are prop) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255312 (text: Activists working on smarter scale models are prop) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i250]" time="0.366"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255313 (text: Today, Theresa May is suffering the partisan effec) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255313 (text: Today, Theresa May is suffering the partisan effec) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i251]" time="0.396"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255314 (text: Topic Number 209 - Off-Generation Vehicles For ap) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255314 (text: Topic Number 209 - Off-Generation Vehicles For ap) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i252]" time="0.382"><properties><property name="score" value="0.10691862" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i253]" time="0.341"><properties><property name="score" value="0.013232764" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255316 (text: AT&T will try to convince the U.S. Supreme Court t) is an LLM-generated sample, misclassified as human-generated with confidence 0.01323276 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255316 (text: AT&T will try to convince the U.S. Supreme Court t) is an LLM-generated sample, misclassified as human-generated with confidence 0.01323276
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i254]" time="0.434"><properties><property name="score" value="0.20125067" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i255]" time="0.367"><properties><property name="score" value="0.102898405" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i256]" time="0.612"><properties><property name="score" value="0.20485923" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i257]" time="0.350"><properties><property name="score" value="0.23680235" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i258]" time="0.328"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255322 (text: Please enable Javascript to watch this video A cl) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255322 (text: Please enable Javascript to watch this video A cl) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i259]" time="0.314"><properties><property name="score" value="0.2286557" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i260]" time="0.300"><properties><property name="score" value="0.059955575" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255324 (text: SAANPD (S. A. Thai Police Bureau) "Aspirational s) is an LLM-generated sample, misclassified as human-generated with confidence 0.05995557 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255324 (text: SAANPD (S. A. Thai Police Bureau) "Aspirational s) is an LLM-generated sample, misclassified as human-generated with confidence 0.05995557
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i261]" time="0.295"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255326 (text: *** If you're looking for one thing to get excite) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255326 (text: *** If you're looking for one thing to get excite) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i262]" time="0.285"><properties><property name="score" value="0.09386432" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i263]" time="0.306"><properties><property name="score" value="0.28249645" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i264]" time="0.276"><properties><property name="score" value="0.70725835" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255329 (text: MADISON, Wis. - Polled residents who support legal) is an LLM-generated sample, misclassified as human-generated with confidence 0.70725835 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255329 (text: MADISON, Wis. - Polled residents who support legal) is an LLM-generated sample, misclassified as human-generated with confidence 0.70725835
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i265]" time="0.404"><properties><property name="score" value="0.218343825" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i266]" time="0.969"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255331 (text: 7th Runner-Up Third place Venice - $15,000 The p) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255331 (text: 7th Runner-Up Third place Venice - $15,000 The p) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i267]" time="0.323"><properties><property name="score" value="0.09773292" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255332 (text: 35189235392018118258089619225575314975163 5002495) is an LLM-generated sample, misclassified as human-generated with confidence 0.09773292 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255332 (text: 35189235392018118258089619225575314975163 5002495) is an LLM-generated sample, misclassified as human-generated with confidence 0.09773292
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i268]" time="0.296"><properties><property name="score" value="0.02938076" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i269]" time="0.260"><properties><property name="score" value="0.0022360794" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255335 (text: Robert Mercer (R), the billionaire who runs a chai) is an LLM-generated sample, misclassified as human-generated with confidence 0.00223608 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255335 (text: Robert Mercer (R), the billionaire who runs a chai) is an LLM-generated sample, misclassified as human-generated with confidence 0.00223608
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i270]" time="0.267"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255336 (text: Over a dozen House Republicans are opposed to Hous) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255336 (text: Over a dozen House Republicans are opposed to Hous) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i271]" time="0.273"><properties><property name="score" value="0.0038101834" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255337 (text: CAIRO — Egyptian TV news channels are giving viewe) is an LLM-generated sample, misclassified as human-generated with confidence 0.00381018 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255337 (text: CAIRO — Egyptian TV news channels are giving viewe) is an LLM-generated sample, misclassified as human-generated with confidence 0.00381018
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i272]" time="0.264"><properties><property name="score" value="0.12094012" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255338 (text: Netflix has chosen Taiwan TV drama "Healing Camp" ) is an LLM-generated sample, misclassified as human-generated with confidence 0.12094012 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255338 (text: Netflix has chosen Taiwan TV drama "Healing Camp" ) is an LLM-generated sample, misclassified as human-generated with confidence 0.12094012
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i273]" time="0.256"><properties><property name="score" value="0.012933774" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255339 (text: Media playback is used to report on this live broa) is an LLM-generated sample, misclassified as human-generated with confidence 0.01293377 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255339 (text: Media playback is used to report on this live broa) is an LLM-generated sample, misclassified as human-generated with confidence 0.01293377
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i274]" time="0.296"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255342 (text: Source: Crimescenews.pk Unregistered oboist / com) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255342 (text: Source: Crimescenews.pk Unregistered oboist / com) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i275]" time="0.268"><properties><property name="score" value="0.7360793" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255343 (text: The card logo is quite charismatic and would make ) is an LLM-generated sample, misclassified as human-generated with confidence 0.7360793 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255343 (text: The card logo is quite charismatic and would make ) is an LLM-generated sample, misclassified as human-generated with confidence 0.7360793
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i276]" time="0.545"><properties><property name="score" value="0.19254716" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i277]" time="0.319"><properties><property name="score" value="0.07483087" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i278]" time="0.276"><properties><property name="score" value="0.105662645" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i279]" time="0.255"><properties><property name="score" value="0.054018445" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i280]" time="0.269"><properties><property name="score" value="0.10407835" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i281]" time="0.380"><properties><property name="score" value="0.079751074" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i282]" time="0.243"><properties><property name="score" value="0.2905171" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i283]" time="0.273"><properties><property name="score" value="0.38044495" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i284]" time="0.276"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255355 (text: Tama is celebrated in autumn as a rebirth of natur) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255355 (text: Tama is celebrated in autumn as a rebirth of natur) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i285]" time="0.282"><properties><property name="score" value="0.08357192" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255356 (text: Last season was one that really showed the charact) is an LLM-generated sample, misclassified as human-generated with confidence 0.08357192 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255356 (text: Last season was one that really showed the charact) is an LLM-generated sample, misclassified as human-generated with confidence 0.08357192
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i286]" time="0.286"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255360 (text: Some stats from the AHL's preseason games. Still, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255360 (text: Some stats from the AHL's preseason games. Still, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i287]" time="0.542"><properties><property name="score" value="0.1846769185" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i288]" time="0.286"><properties><property name="score" value="0.0116961915" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255363 (text: L Publicarch, S. Egerton, J. Möller, J. Köhler, C.) is an LLM-generated sample, misclassified as human-generated with confidence 0.01169619 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255363 (text: L Publicarch, S. Egerton, J. Möller, J. Köhler, C.) is an LLM-generated sample, misclassified as human-generated with confidence 0.01169619
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i289]" time="0.273"><properties><property name="score" value="0.52122056" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i290]" time="0.361"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255365 (text: Swiss parties Yvette Clarke (left) and 64-year-old) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255365 (text: Swiss parties Yvette Clarke (left) and 64-year-old) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i291]" time="0.323"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255366 (text: 「It's pretty cool」(Kazura) 「Yeah, pretty cool…… T) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255366 (text: 「It's pretty cool」(Kazura) 「Yeah, pretty cool…… T) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i292]" time="0.361"><properties><property name="score" value="0.04319076" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i293]" time="0.290"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255369 (text: By John Feffer, Victoria Scofield: Why did the pla) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255369 (text: By John Feffer, Victoria Scofield: Why did the pla) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i294]" time="0.274"><properties><property name="score" value="0.3080822" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i295]" time="0.301"><properties><property name="score" value="0.1116937" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i296]" time="0.287"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255372 (text: Oakland Raiders safety Charles Woodson — grouchy, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255372 (text: Oakland Raiders safety Charles Woodson — grouchy, ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i297]" time="0.261"><properties><property name="score" value="0.019970162" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i298]" time="0.271"><properties><property name="score" value="0.00050755276" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255374 (text: Decision to sell company upheld by high court: Alm) is an LLM-generated sample, misclassified as human-generated with confidence 0.00050755 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255374 (text: Decision to sell company upheld by high court: Alm) is an LLM-generated sample, misclassified as human-generated with confidence 0.00050755
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i299]" time="0.291"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255375 (text: FIRST TEST, THURSDAY WITH ROB BAGGALO 44th minut) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255375 (text: FIRST TEST, THURSDAY WITH ROB BAGGALO 44th minut) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i300]" time="0.310"><properties><property name="score" value="0.045710888" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255376 (text: My father called me. "… Nneka Nosyika. Why are yo) is an LLM-generated sample, misclassified as human-generated with confidence 0.04571089 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255376 (text: My father called me. "… Nneka Nosyika. Why are yo) is an LLM-generated sample, misclassified as human-generated with confidence 0.04571089
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i301]" time="0.262"><properties><property name="score" value="0.08624922" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255378 (text: Back to page 1 Week 6's specialist so far wants t) is an LLM-generated sample, misclassified as human-generated with confidence 0.08624922 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255378 (text: Back to page 1 Week 6's specialist so far wants t) is an LLM-generated sample, misclassified as human-generated with confidence 0.08624922
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i302]" time="0.268"><properties><property name="score" value="0.16972482" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255379 (text: Hoping to start a trail of victory under new champ) is an LLM-generated sample, misclassified as human-generated with confidence 0.16972482 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255379 (text: Hoping to start a trail of victory under new champ) is an LLM-generated sample, misclassified as human-generated with confidence 0.16972482
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i303]" time="0.283"><properties><property name="score" value="0.128749685" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255380 (text: Border War is an entirely mod-free CrossFire campa) is an LLM-generated sample, misclassified as human-generated with confidence 0.12874969 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255380 (text: Border War is an entirely mod-free CrossFire campa) is an LLM-generated sample, misclassified as human-generated with confidence 0.12874969
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i304]" time="0.289"><properties><property name="score" value="0.086060226" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255381 (text: We generally assume that women walk more slowly th) is an LLM-generated sample, misclassified as human-generated with confidence 0.08606023 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255381 (text: We generally assume that women walk more slowly th) is an LLM-generated sample, misclassified as human-generated with confidence 0.08606023
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i305]" time="0.283"><properties><property name="score" value="0.0051585725" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255382 (text: The 49ers are so scared they won't take their game) is an LLM-generated sample, misclassified as human-generated with confidence 0.00515857 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255382 (text: The 49ers are so scared they won't take their game) is an LLM-generated sample, misclassified as human-generated with confidence 0.00515857
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i306]" time="0.361"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255383 (text: Hello, my name is Tim, and I am an entrepreneur, w) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255383 (text: Hello, my name is Tim, and I am an entrepreneur, w) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i307]" time="0.308"><properties><property name="score" value="0.15225516" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255384 (text: "We are holding the complete material in our files) is an LLM-generated sample, misclassified as human-generated with confidence 0.15225516 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255384 (text: "We are holding the complete material in our files) is an LLM-generated sample, misclassified as human-generated with confidence 0.15225516
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i308]" time="0.476"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255386 (text: Robotics is old hat to enterprise technology compa) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255386 (text: Robotics is old hat to enterprise technology compa) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i309]" time="0.313"><properties><property name="score" value="0.07246651" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i310]" time="0.295"><properties><property name="score" value="0.029748192" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i311]" time="0.308"><properties><property name="score" value="0.35763988" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i312]" time="0.301"><properties><property name="score" value="0.33200413" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i313]" time="0.257"><properties><property name="score" value="0.001435668" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255395 (text: Kentucky GOP sponsored bill to save Chafee from tr) is an LLM-generated sample, misclassified as human-generated with confidence 0.00143567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255395 (text: Kentucky GOP sponsored bill to save Chafee from tr) is an LLM-generated sample, misclassified as human-generated with confidence 0.00143567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i314]" time="0.404"><properties><property name="score" value="0.18230355" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i315]" time="0.354"><properties><property name="score" value="0.0368823" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255399 (text: SEO is one of the most important elements of any w) is an LLM-generated sample, misclassified as human-generated with confidence 0.0368823 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255399 (text: SEO is one of the most important elements of any w) is an LLM-generated sample, misclassified as human-generated with confidence 0.0368823
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i316]" time="0.291"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255400 (text: Americans are furious over the Transportation Secu) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255400 (text: Americans are furious over the Transportation Secu) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i317]" time="0.298"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255401 (text: A Baki National Park official is covered in a plas) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255401 (text: A Baki National Park official is covered in a plas) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i318]" time="0.329"><properties><property name="score" value="0.035257794" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255402 (text: Jared Law (pictured) joins West Ham from Wolves af) is an LLM-generated sample, misclassified as human-generated with confidence 0.03525779 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255402 (text: Jared Law (pictured) joins West Ham from Wolves af) is an LLM-generated sample, misclassified as human-generated with confidence 0.03525779
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i319]" time="0.691"><properties><property name="score" value="1.08816135" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i320]" time="0.328"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255405 (text: updated: Justin Sodikoff continues his blog series) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255405 (text: updated: Justin Sodikoff continues his blog series) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i321]" time="0.314"><properties><property name="score" value="0.004582493" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255408 (text: Story highlights Sanders and Clinton have differen) is an LLM-generated sample, misclassified as human-generated with confidence 0.00458249 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255408 (text: Story highlights Sanders and Clinton have differen) is an LLM-generated sample, misclassified as human-generated with confidence 0.00458249
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i322]" time="0.241"><properties><property name="score" value="1.2076659" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i323]" time="0.257"><properties><property name="score" value="0.039801594" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255411 (text: As our Liberals continue to ban," wrote a Trump su) is an LLM-generated sample, misclassified as human-generated with confidence 0.03980159 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255411 (text: As our Liberals continue to ban," wrote a Trump su) is an LLM-generated sample, misclassified as human-generated with confidence 0.03980159
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i324]" time="0.286"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255412 (text: Shark Attack: Why Would Someone with an 100-ft Gia) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255412 (text: Shark Attack: Why Would Someone with an 100-ft Gia) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i325]" time="0.254"><properties><property name="score" value="0.026572201" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i326]" time="0.280"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255415 (text: Allan Durand March MONTRÉAL – Wei-Chin Peng beat) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255415 (text: Allan Durand March MONTRÉAL – Wei-Chin Peng beat) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i327]" time="0.313"><properties><property name="score" value="0.023965096" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255416 (text: Our next chapter begins as we continue our explora) is an LLM-generated sample, misclassified as human-generated with confidence 0.0239651 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255416 (text: Our next chapter begins as we continue our explora) is an LLM-generated sample, misclassified as human-generated with confidence 0.0239651
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i328]" time="0.339"><properties><property name="score" value="0.090233765" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i329]" time="0.268"><properties><property name="score" value="0.2651179" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255419 (text: California Governor Jerry Brown has signed legisla) is an LLM-generated sample, misclassified as human-generated with confidence 0.2651179 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255419 (text: California Governor Jerry Brown has signed legisla) is an LLM-generated sample, misclassified as human-generated with confidence 0.2651179
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i330]" time="0.293"><properties><property name="score" value="0.045213837" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i331]" time="0.314"><properties><property name="score" value="0.49779317" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255421 (text: So for those of you in need of some training wheel) is an LLM-generated sample, misclassified as human-generated with confidence 0.49779317 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255421 (text: So for those of you in need of some training wheel) is an LLM-generated sample, misclassified as human-generated with confidence 0.49779317
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i332]" time="0.294"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255422 (text: Physical Therapy Diagnostic Instrumentation Sourc) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255422 (text: Physical Therapy Diagnostic Instrumentation Sourc) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i333]" time="0.369"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255423 (text: Emirates airline is offering return trips from Ice) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255423 (text: Emirates airline is offering return trips from Ice) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i334]" time="0.293"><properties><property name="score" value="0.09768967" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i335]" time="0.283"><properties><property name="score" value="1.3590115" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255425 (text: Steven C. Schwalm Posted in reply to eagleparent ) is an LLM-generated sample, misclassified as human-generated with confidence 1.3590115 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255425 (text: Steven C. Schwalm Posted in reply to eagleparent ) is an LLM-generated sample, misclassified as human-generated with confidence 1.3590115
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i336]" time="0.291"><properties><property name="score" value="0.6723214" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i337]" time="0.305"><properties><property name="score" value="0.015440526" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i338]" time="0.271"><properties><property name="score" value="1.0561103" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i339]" time="0.284"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255429 (text: Our comprehensive review of the Federal Court of A) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255429 (text: Our comprehensive review of the Federal Court of A) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i340]" time="0.352"><properties><property name="score" value="0.18217224" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i341]" time="0.333"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255431 (text: #21 UST 3RD INDEPENDENCE 4 (NAC) - HIGH HOP - PICK) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255431 (text: #21 UST 3RD INDEPENDENCE 4 (NAC) - HIGH HOP - PICK) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i342]" time="0.318"><properties><property name="score" value="0.23750867" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i343]" time="0.265"><properties><property name="score" value="0.1272716" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i344]" time="0.293"><properties><property name="score" value="0.08097212" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255434 (text: CALGARY, AB -- The Calgary Flames announced today ) is an LLM-generated sample, misclassified as human-generated with confidence 0.08097212 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255434 (text: CALGARY, AB -- The Calgary Flames announced today ) is an LLM-generated sample, misclassified as human-generated with confidence 0.08097212
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i345]" time="0.292"><properties><property name="score" value="1.7148029" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i346]" time="0.598"><properties><property name="score" value="0.101564715" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i347]" time="0.305"><properties><property name="score" value="0.287935525" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i348]" time="0.294"><properties><property name="score" value="1.4954869" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255439 (text: North America based Manjaro Linux has been one of ) is an LLM-generated sample, misclassified as human-generated with confidence 1.4954869 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255439 (text: North America based Manjaro Linux has been one of ) is an LLM-generated sample, misclassified as human-generated with confidence 1.4954869
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i349]" time="0.253"><properties><property name="score" value="0.19234188" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i350]" time="0.231"><properties><property name="score" value="0.08445897" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255441 (text: Go The Distance To Write Your Novel By: Duane Cha) is an LLM-generated sample, misclassified as human-generated with confidence 0.08445897 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255441 (text: Go The Distance To Write Your Novel By: Duane Cha) is an LLM-generated sample, misclassified as human-generated with confidence 0.08445897
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i351]" time="0.278"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255443 (text: thelands with sheets 88 real beds on the right ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255443 (text: thelands with sheets 88 real beds on the right ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i352]" time="0.271"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255445 (text: By Han Choi North Korea sees the United States as) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255445 (text: By Han Choi North Korea sees the United States as) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i353]" time="0.365"><properties><property name="score" value="0.022559105" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255446 (text: Background: JAMA ART EXPOSURE is the number one j) is an LLM-generated sample, misclassified as human-generated with confidence 0.0225591 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255446 (text: Background: JAMA ART EXPOSURE is the number one j) is an LLM-generated sample, misclassified as human-generated with confidence 0.0225591
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i354]" time="0.276"><properties><property name="score" value="0.06880046" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i355]" time="0.338"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255449 (text: Listen, before you start writing to your local pap) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255449 (text: Listen, before you start writing to your local pap) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i356]" time="0.384"><properties><property name="score" value="0.11373065" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255450 (text: http://youtu.be/Kp09yP36UBw A postal worker who h) is an LLM-generated sample, misclassified as human-generated with confidence 0.11373065 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255450 (text: http://youtu.be/Kp09yP36UBw A postal worker who h) is an LLM-generated sample, misclassified as human-generated with confidence 0.11373065
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i357]" time="0.284"><properties><property name="score" value="0.6835344" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i358]" time="0.330"><properties><property name="score" value="0.15379952" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i359]" time="0.324"><properties><property name="score" value="0.37349248" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i360]" time="0.302"><properties><property name="score" value="0.008891194" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255456 (text: BRASILIA (Reuters) - Brazil said Stockholm's non-b) is an LLM-generated sample, misclassified as human-generated with confidence 0.00889119 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255456 (text: BRASILIA (Reuters) - Brazil said Stockholm's non-b) is an LLM-generated sample, misclassified as human-generated with confidence 0.00889119
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i361]" time="0.596"><properties><property name="score" value="0.303523777" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i362]" time="0.308"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255458 (text: Mark Composer mother to two years, THREE childre) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255458 (text: Mark Composer mother to two years, THREE childre) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i363]" time="0.333"><properties><property name="score" value="0.40641984" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i364]" time="0.346"><properties><property name="score" value="0.014615579" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i365]" time="0.393"><properties><property name="score" value="0.02097891" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i366]" time="0.368"><properties><property name="score" value="0.2295112" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i367]" time="0.310"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255464 (text: A poll conducted by YouGov for the Guardian sugges) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255464 (text: A poll conducted by YouGov for the Guardian sugges) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i368]" time="0.345"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255465 (text: • Freedom estimated at $3.6bn • President also pre) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255465 (text: • Freedom estimated at $3.6bn • President also pre) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i369]" time="0.337"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255467 (text: Survivors of the Syrian civil war have given their) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255467 (text: Survivors of the Syrian civil war have given their) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i370]" time="0.289"><properties><property name="score" value="0.0031222142" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255468 (text: England tighthead prop Owen Farrell is in the race) is an LLM-generated sample, misclassified as human-generated with confidence 0.00312221 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255468 (text: England tighthead prop Owen Farrell is in the race) is an LLM-generated sample, misclassified as human-generated with confidence 0.00312221
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i371]" time="0.330"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255469 (text: As you may have heard, the Clinton Foundation has ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255469 (text: As you may have heard, the Clinton Foundation has ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i372]" time="0.331"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255470 (text: Match date: 22 July 2016 In the end, qualificatio) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255470 (text: Match date: 22 July 2016 In the end, qualificatio) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i373]" time="0.314"><properties><property name="score" value="0.0046929115" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255474 (text: With an unrestricted market to search for any perf) is an LLM-generated sample, misclassified as human-generated with confidence 0.00469291 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255474 (text: With an unrestricted market to search for any perf) is an LLM-generated sample, misclassified as human-generated with confidence 0.00469291
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i374]" time="0.341"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255475 (text: In this little-noticed chapter, Darmstadt, Germany) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255475 (text: In this little-noticed chapter, Darmstadt, Germany) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i375]" time="0.407"><properties><property name="score" value="0.30615598" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i376]" time="0.381"><properties><property name="score" value="0.45625945" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i377]" time="0.361"><properties><property name="score" value="0.07026156" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i378]" time="0.333"><properties><property name="score" value="0.09502684" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i379]" time="0.379"><properties><property name="score" value="0.91849566" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i380]" time="0.323"><properties><property name="score" value="0.0019446604" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255481 (text: President Donald Trump may have been joking about ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00194466 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255481 (text: President Donald Trump may have been joking about ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00194466
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i381]" time="0.398"><properties><property name="score" value="0.024498688" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i382]" time="0.317"><properties><property name="score" value="0.022922976" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i383]" time="0.302"><properties><property name="score" value="0.26924905" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i384]" time="0.361"><properties><property name="score" value="0.0008848181" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255486 (text: New Mexico City (CNN) Rodríguez Arkuren acribed a ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00088482 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255486 (text: New Mexico City (CNN) Rodríguez Arkuren acribed a ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00088482
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i385]" time="0.307"><properties><property name="score" value="0.008763413" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255487 (text: Celebrating their 25th anniversary in 2000, on Jul) is an LLM-generated sample, misclassified as human-generated with confidence 0.00876341 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255487 (text: Celebrating their 25th anniversary in 2000, on Jul) is an LLM-generated sample, misclassified as human-generated with confidence 0.00876341
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i386]" time="0.285"><properties><property name="score" value="0.166275335" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i387]" time="0.348"><properties><property name="score" value="0.017903464" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255489 (text: Scoreboard CBS ABC FOX NBC UNI CW Adults 18-49: Ra) is an LLM-generated sample, misclassified as human-generated with confidence 0.01790346 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255489 (text: Scoreboard CBS ABC FOX NBC UNI CW Adults 18-49: Ra) is an LLM-generated sample, misclassified as human-generated with confidence 0.01790346
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i388]" time="0.314"><properties><property name="score" value="0.124754526" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i389]" time="0.693"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255493 (text: After a few days of rumors going around, Lenovo ha) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255493 (text: After a few days of rumors going around, Lenovo ha) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i390]" time="0.319"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255494 (text: Capture The Flag is still one of my favorite strug) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255494 (text: Capture The Flag is still one of my favorite strug) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i391]" time="0.283"><properties><property name="score" value="0.045795085" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i392]" time="0.292"><properties><property name="score" value="0.0045829727" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255496 (text: Since Republicans are not doing quite as well with) is an LLM-generated sample, misclassified as human-generated with confidence 0.00458297 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255496 (text: Since Republicans are not doing quite as well with) is an LLM-generated sample, misclassified as human-generated with confidence 0.00458297
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i393]" time="0.300"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255497 (text: ORLANDO, Fla. -- In just his fifth game with the C) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255497 (text: ORLANDO, Fla. -- In just his fifth game with the C) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i394]" time="0.299"><properties><property name="score" value="0.2512944" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255498 (text: An AFA program for the prevention and treatment of) is an LLM-generated sample, misclassified as human-generated with confidence 0.2512944 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255498 (text: An AFA program for the prevention and treatment of) is an LLM-generated sample, misclassified as human-generated with confidence 0.2512944
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i395]" time="0.318"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255499 (text: I've got a bit of trouble keeping track at the mom) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255499 (text: I've got a bit of trouble keeping track at the mom) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i396]" time="0.565"><properties><property name="score" value="0.10329704" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i397]" time="0.301"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255501 (text: Disney Infinity 3.0 UPDATES: "We've made it so tha) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255501 (text: Disney Infinity 3.0 UPDATES: "We've made it so tha) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i398]" time="0.279"><properties><property name="score" value="0.12797512" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255502 (text: At the border, a workman was knocked flat on his b) is an LLM-generated sample, misclassified as human-generated with confidence 0.12797512 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255502 (text: At the border, a workman was knocked flat on his b) is an LLM-generated sample, misclassified as human-generated with confidence 0.12797512
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i399]" time="0.384"><properties><property name="score" value="0.32307723" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i400]" time="0.324"><properties><property name="score" value="0.14431132" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255504 (text: The Washington Post Monday, March 6, 2008; Page A) is an LLM-generated sample, misclassified as human-generated with confidence 0.14431132 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255504 (text: The Washington Post Monday, March 6, 2008; Page A) is an LLM-generated sample, misclassified as human-generated with confidence 0.14431132
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i401]" time="0.279"><properties><property name="score" value="0.22194818" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i402]" time="0.454"><properties><property name="score" value="0.18621841" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i403]" time="0.284"><properties><property name="score" value="1.0134057" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i404]" time="0.332"><properties><property name="score" value="0.008235541" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255508 (text: Revenues rose 37% on last year, but staffing level) is an LLM-generated sample, misclassified as human-generated with confidence 0.00823554 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255508 (text: Revenues rose 37% on last year, but staffing level) is an LLM-generated sample, misclassified as human-generated with confidence 0.00823554
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i405]" time="0.315"><properties><property name="score" value="0.10997975" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i406]" time="0.298"><properties><property name="score" value="0.0142524" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255510 (text: Some observers might have thought Mitt Romney's we) is an LLM-generated sample, misclassified as human-generated with confidence 0.0142524 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255510 (text: Some observers might have thought Mitt Romney's we) is an LLM-generated sample, misclassified as human-generated with confidence 0.0142524
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i407]" time="0.391"><properties><property name="score" value="1.3901869" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255511 (text: Contact Information Phone: (613) 743-1255 Toll ) is an LLM-generated sample, misclassified as human-generated with confidence 1.3901869 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255511 (text: Contact Information Phone: (613) 743-1255 Toll ) is an LLM-generated sample, misclassified as human-generated with confidence 1.3901869
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i408]" time="0.303"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255512 (text: Independent news is more important than ever. Sign) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255512 (text: Independent news is more important than ever. Sign) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i409]" time="0.312"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255515 (text: As Donald Trump's mental capacity continues to tak) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255515 (text: As Donald Trump's mental capacity continues to tak) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i410]" time="0.348"><properties><property name="score" value="0.07432662" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i411]" time="0.332"><properties><property name="score" value="0.1318918" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i412]" time="0.396"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255518 (text: The effects of testimony hearing thing were really) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255518 (text: The effects of testimony hearing thing were really) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i413]" time="0.334"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255519 (text: "Is this the car?" Austin Appleby can't name a Ho) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255519 (text: "Is this the car?" Austin Appleby can't name a Ho) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i414]" time="0.313"><properties><property name="score" value="0.20489068" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i415]" time="0.391"><properties><property name="score" value="0.095792295" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255521 (text: Because one of the complaints of Blair Murphy over) is an LLM-generated sample, misclassified as human-generated with confidence 0.09579229 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255521 (text: Because one of the complaints of Blair Murphy over) is an LLM-generated sample, misclassified as human-generated with confidence 0.09579229
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i416]" time="0.358"><properties><property name="score" value="0.5447251" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i417]" time="0.309"><properties><property name="score" value="0.0049224226" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255525 (text: The target set by the government for direct overse) is an LLM-generated sample, misclassified as human-generated with confidence 0.00492242 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255525 (text: The target set by the government for direct overse) is an LLM-generated sample, misclassified as human-generated with confidence 0.00492242
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i418]" time="0.297"><properties><property name="score" value="0.2727056" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i419]" time="0.319"><properties><property name="score" value="0.12469545" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i420]" time="0.346"><properties><property name="score" value="1.0045655" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255528 (text: Oasis were the club of The Beat. They took the wor) is an LLM-generated sample, misclassified as human-generated with confidence 1.0045655 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255528 (text: Oasis were the club of The Beat. They took the wor) is an LLM-generated sample, misclassified as human-generated with confidence 1.0045655
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i421]" time="0.468"><properties><property name="score" value="0.0013691148" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255529 (text: Real Madrid forward Cristiano Ronaldo had not appe) is an LLM-generated sample, misclassified as human-generated with confidence 0.00136911 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255529 (text: Real Madrid forward Cristiano Ronaldo had not appe) is an LLM-generated sample, misclassified as human-generated with confidence 0.00136911
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i422]" time="0.394"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255531 (text: Stop talking about Ripple on a website for element) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255531 (text: Stop talking about Ripple on a website for element) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i423]" time="0.309"><properties><property name="score" value="0.011305724" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i424]" time="0.321"><properties><property name="score" value="0.042622298" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255534 (text: The test appears to show that the stereotypes abou) is an LLM-generated sample, misclassified as human-generated with confidence 0.0426223 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255534 (text: The test appears to show that the stereotypes abou) is an LLM-generated sample, misclassified as human-generated with confidence 0.0426223
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i425]" time="0.361"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255537 (text: Alice Rossi waited until she was home alone to sin) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255537 (text: Alice Rossi waited until she was home alone to sin) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i426]" time="0.331"><properties><property name="score" value="0.13899629" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i427]" time="0.333"><properties><property name="score" value="0.2069575" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i428]" time="0.323"><properties><property name="score" value="0.5232598" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255542 (text: 1 #1 Klonan 0 Frags – + some good stuff the map wi) is an LLM-generated sample, misclassified as human-generated with confidence 0.5232598 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255542 (text: 1 #1 Klonan 0 Frags – + some good stuff the map wi) is an LLM-generated sample, misclassified as human-generated with confidence 0.5232598
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i429]" time="0.280"><properties><property name="score" value="0.06122341" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255543 (text: Spinach and beer? Who knew that beer could be so g) is an LLM-generated sample, misclassified as human-generated with confidence 0.06122341 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255543 (text: Spinach and beer? Who knew that beer could be so g) is an LLM-generated sample, misclassified as human-generated with confidence 0.06122341
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i430]" time="0.336"><properties><property name="score" value="0.18537055" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i431]" time="0.293"><properties><property name="score" value="0.2753137" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255545 (text: Barry Bonds hasn't announced everything he's about) is an LLM-generated sample, misclassified as human-generated with confidence 0.2753137 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255545 (text: Barry Bonds hasn't announced everything he's about) is an LLM-generated sample, misclassified as human-generated with confidence 0.2753137
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i432]" time="0.280"><properties><property name="score" value="0.1870772" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i433]" time="0.316"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255547 (text: Scientists studying 3-D printing could be wrong a) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255547 (text: Scientists studying 3-D printing could be wrong a) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i434]" time="0.331"><properties><property name="score" value="0.13282521" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i435]" time="0.338"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255550 (text: Karen Bernaport, the retired financial planner who) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255550 (text: Karen Bernaport, the retired financial planner who) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i436]" time="0.335"><properties><property name="score" value="0.0374704525" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255551 (text: His son's fate was sealed two months ago, another ) is an LLM-generated sample, misclassified as human-generated with confidence 0.03747045 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255551 (text: His son's fate was sealed two months ago, another ) is an LLM-generated sample, misclassified as human-generated with confidence 0.03747045
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i437]" time="0.328"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255552 (text: It's strange to leave one mid-season with hopes fo) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255552 (text: It's strange to leave one mid-season with hopes fo) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i438]" time="0.267"><properties><property name="score" value="0.19185571" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i439]" time="0.301"><properties><property name="score" value="0.19728081" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i440]" time="0.443"><properties><property name="score" value="0.001254822" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255555 (text: Karson Williams was arrested Wednesday for interfe) is an LLM-generated sample, misclassified as human-generated with confidence 0.00125482 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255555 (text: Karson Williams was arrested Wednesday for interfe) is an LLM-generated sample, misclassified as human-generated with confidence 0.00125482
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i441]" time="0.594"><properties><property name="score" value="0.237182784" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i442]" time="1.293"><properties><property name="score" value="0.14142916" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255557 (text: Heat waves caused by disturbed interactions of the) is an LLM-generated sample, misclassified as human-generated with confidence 0.14142916 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255557 (text: Heat waves caused by disturbed interactions of the) is an LLM-generated sample, misclassified as human-generated with confidence 0.14142916
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i443]" time="0.296"><properties><property name="score" value="0.1730607" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i444]" time="1.563"><properties><property name="score" value="0.6445226" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255560 (text: The U.S. Senate voted Tuesday to eliminate rules t) is an LLM-generated sample, misclassified as human-generated with confidence 0.6445226 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255560 (text: The U.S. Senate voted Tuesday to eliminate rules t) is an LLM-generated sample, misclassified as human-generated with confidence 0.6445226
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i445]" time="0.279"><properties><property name="score" value="0.015734853" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i446]" time="0.327"><properties><property name="score" value="0.004487531" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255563 (text: A Darwin station has apologised for using noise co) is an LLM-generated sample, misclassified as human-generated with confidence 0.00448753 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255563 (text: A Darwin station has apologised for using noise co) is an LLM-generated sample, misclassified as human-generated with confidence 0.00448753
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i447]" time="0.256"><properties><property name="score" value="0.14935842" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i448]" time="0.286"><properties><property name="score" value="0.010855877" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i449]" time="0.318"><properties><property name="score" value="0.010005371" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255567 (text: Tory MP Zac Goldsmith has launched a devastating a) is an LLM-generated sample, misclassified as human-generated with confidence 0.01000537 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255567 (text: Tory MP Zac Goldsmith has launched a devastating a) is an LLM-generated sample, misclassified as human-generated with confidence 0.01000537
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i450]" time="0.365"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255568 (text: Recently, auto digital use was touted as being dea) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255568 (text: Recently, auto digital use was touted as being dea) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i451]" time="0.309"><properties><property name="score" value="0.11027009" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i452]" time="0.410"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255570 (text: SPECIAL REPORT by Paddy Butterworth, Evening Stand) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255570 (text: SPECIAL REPORT by Paddy Butterworth, Evening Stand) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i453]" time="0.282"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255571 (text: From The Vault - Fallout Wiki Intro to Tenpenny T) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255571 (text: From The Vault - Fallout Wiki Intro to Tenpenny T) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i454]" time="0.279"><properties><property name="score" value="0.0036144212" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255572 (text: Persona 5 team members have been teasing fans with) is an LLM-generated sample, misclassified as human-generated with confidence 0.00361442 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255572 (text: Persona 5 team members have been teasing fans with) is an LLM-generated sample, misclassified as human-generated with confidence 0.00361442
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i455]" time="0.257"><properties><property name="score" value="0.0053925617" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255573 (text: Farmers in eastern Georgia got a surprise when fas) is an LLM-generated sample, misclassified as human-generated with confidence 0.00539256 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255573 (text: Farmers in eastern Georgia got a surprise when fas) is an LLM-generated sample, misclassified as human-generated with confidence 0.00539256
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i456]" time="0.337"><properties><property name="score" value="0.0093304105" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255574 (text: window._taboola = window._taboola || []; _taboola.) is an LLM-generated sample, misclassified as human-generated with confidence 0.00933041 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255574 (text: window._taboola = window._taboola || []; _taboola.) is an LLM-generated sample, misclassified as human-generated with confidence 0.00933041
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i457]" time="0.352"><properties><property name="score" value="0.12694075" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i458]" time="0.333"><properties><property name="score" value="1.4851314" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i459]" time="0.319"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255578 (text: Less than two months ago BPS president Joel J. Vac) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255578 (text: Less than two months ago BPS president Joel J. Vac) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i460]" time="1.901"><properties><property name="score" value="0.015281705" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i461]" time="0.307"><properties><property name="score" value="0.2552491" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i462]" time="30.240"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255581 (text: Please Note: This article holds the sole opinion o) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255581 (text: Please Note: This article holds the sole opinion o) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i463]" time="2.368"><properties><property name="score" value="0.014800247" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255585 (text: Crossref Citations This article has been cited by) is an LLM-generated sample, misclassified as human-generated with confidence 0.01480025 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255585 (text: Crossref Citations This article has been cited by) is an LLM-generated sample, misclassified as human-generated with confidence 0.01480025
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i464]" time="0.299"><properties><property name="score" value="1.12364985" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i465]" time="0.349"><properties><property name="score" value="0.18370783" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i466]" time="0.303"><properties><property name="score" value="0.0255956335" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255589 (text: pypyserial_middlclip #4391 6 Minutes to Read In ) is an LLM-generated sample, misclassified as human-generated with confidence 0.02559563 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255589 (text: pypyserial_middlclip #4391 6 Minutes to Read In ) is an LLM-generated sample, misclassified as human-generated with confidence 0.02559563
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i467]" time="0.273"><properties><property name="score" value="0.6629638" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255591 (text: I was in the grocery store the other day and some ) is an LLM-generated sample, misclassified as human-generated with confidence 0.6629638 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255591 (text: I was in the grocery store the other day and some ) is an LLM-generated sample, misclassified as human-generated with confidence 0.6629638
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i468]" time="0.277"><properties><property name="score" value="0.00862236" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255594 (text: Joey Davidson | Gaming Reviews & News by When it ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00862236 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255594 (text: Joey Davidson | Gaming Reviews & News by When it ) is an LLM-generated sample, misclassified as human-generated with confidence 0.00862236
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i469]" time="0.306"><properties><property name="score" value="0.20534113" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i470]" time="0.324"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255596 (text: Source: Prachatai The mission of the Huntington H) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255596 (text: Source: Prachatai The mission of the Huntington H) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i471]" time="0.312"><properties><property name="score" value="0.0731399" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255597 (text: As per the PhoneGap version of Django, the renderi) is an LLM-generated sample, misclassified as human-generated with confidence 0.0731399 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255597 (text: As per the PhoneGap version of Django, the renderi) is an LLM-generated sample, misclassified as human-generated with confidence 0.0731399
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i472]" time="0.344"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255598 (text: Six things to know about the Wayside Brewery bill ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255598 (text: Six things to know about the Wayside Brewery bill ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i473]" time="0.338"><properties><property name="score" value="0.0057268324" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255599 (text: Thanksgiving dinner can be a big family affair. To) is an LLM-generated sample, misclassified as human-generated with confidence 0.00572683 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255599 (text: Thanksgiving dinner can be a big family affair. To) is an LLM-generated sample, misclassified as human-generated with confidence 0.00572683
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i474]" time="0.318"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255600 (text: Falling Rain (Telltale Games) I've had just the l) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255600 (text: Falling Rain (Telltale Games) I've had just the l) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i475]" time="0.293"><properties><property name="score" value="0.53325815" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i476]" time="0.369"><properties><property name="score" value="0.128382385" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i477]" time="0.327"><properties><property name="score" value="0.095243075" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i478]" time="0.284"><properties><property name="score" value="0.11916294" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255604 (text: UK. Attorney General Eric Holder and other senior ) is an LLM-generated sample, misclassified as human-generated with confidence 0.11916294 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255604 (text: UK. Attorney General Eric Holder and other senior ) is an LLM-generated sample, misclassified as human-generated with confidence 0.11916294
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i479]" time="0.293"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255606 (text: Stephon Marbury went missing, the NBA's legal team) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255606 (text: Stephon Marbury went missing, the NBA's legal team) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i480]" time="0.315"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255607 (text: Subscribe to the best value in fantasy sports Subs) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255607 (text: Subscribe to the best value in fantasy sports Subs) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i481]" time="0.279"><properties><property name="score" value="0.33364183" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i482]" time="0.281"><properties><property name="score" value="0.15214328" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255609 (text: © Provided by the Independent Ireland The Ireland) is an LLM-generated sample, misclassified as human-generated with confidence 0.15214328 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255609 (text: © Provided by the Independent Ireland The Ireland) is an LLM-generated sample, misclassified as human-generated with confidence 0.15214328
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i483]" time="0.299"><properties><property name="score" value="0.18957627" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i484]" time="0.313"><properties><property name="score" value="0.0027537276" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255611 (text: Fernandez is the second Yankees player this spring) is an LLM-generated sample, misclassified as human-generated with confidence 0.00275373 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255611 (text: Fernandez is the second Yankees player this spring) is an LLM-generated sample, misclassified as human-generated with confidence 0.00275373
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i485]" time="0.350"><properties><property name="score" value="0.059249915" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i486]" time="0.500"><properties><property name="score" value="0.0038778484" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255613 (text: We all know that art is a gift from God. But somet) is an LLM-generated sample, misclassified as human-generated with confidence 0.00387785 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255613 (text: We all know that art is a gift from God. But somet) is an LLM-generated sample, misclassified as human-generated with confidence 0.00387785
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i487]" time="0.318"><properties><property name="score" value="0.094043136" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i488]" time="0.282"><properties><property name="score" value="0.010600426" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255615 (text: NAME THIS POST POSTED 2014-07-27 06:39 Fee Fee E) is an LLM-generated sample, misclassified as human-generated with confidence 0.01060043 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255615 (text: NAME THIS POST POSTED 2014-07-27 06:39 Fee Fee E) is an LLM-generated sample, misclassified as human-generated with confidence 0.01060043
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i489]" time="0.327"><properties><property name="score" value="0.11215231" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i490]" time="0.358"><properties><property name="score" value="0.28186215" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255618 (text: The family of a man gunned down by a B-6 Constella) is an LLM-generated sample, misclassified as human-generated with confidence 0.28186215 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255618 (text: The family of a man gunned down by a B-6 Constella) is an LLM-generated sample, misclassified as human-generated with confidence 0.28186215
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i491]" time="0.344"><properties><property name="score" value="0.35163903" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255619 (text: Measurements Software Small Coding Style In ord) is an LLM-generated sample, misclassified as human-generated with confidence 0.35163903 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255619 (text: Measurements Software Small Coding Style In ord) is an LLM-generated sample, misclassified as human-generated with confidence 0.35163903
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i492]" time="0.346"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255620 (text: Alabama legislators sent Gov. Kay Ivey a bill that) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255620 (text: Alabama legislators sent Gov. Kay Ivey a bill that) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i493]" time="0.368"><properties><property name="score" value="0.1966654" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255621 (text: By Ranjeet Rajan A new study suggests that when i) is an LLM-generated sample, misclassified as human-generated with confidence 0.1966654 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255621 (text: By Ranjeet Rajan A new study suggests that when i) is an LLM-generated sample, misclassified as human-generated with confidence 0.1966654
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i494]" time="0.360"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255622 (text: I will continue, as usual, to have fun though. Eve) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255622 (text: I will continue, as usual, to have fun though. Eve) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i495]" time="0.603"><properties><property name="score" value="0.02609877499999999" /></properties><failure message="AssertionError: samples/xl-1542M.test.jsonl:255623 (text: Male smokers of marijuana cause an unusually high ) is an LLM-generated sample, misclassified as human-generated with confidence 0.02609877 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/xl-1542M.test.jsonl:255623 (text: Male smokers of marijuana cause an unusually high ) is an LLM-generated sample, misclassified as human-generated with confidence 0.02609877
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i496]" time="0.313"><properties><property name="score" value="0.036610223" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i497]" time="0.309"><properties><property name="score" value="0.26407355" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i498]" time="0.357"><properties><property name="score" value="0.20384732" /></properties></testcase><testcase classname="test_openai_detect" name="test_llm_jsonl[i499]" time="0.328"><properties><property name="score" value="0.0875727" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Glacier Ridge Christian School\n\nGlacier Ridge Christian School is a private Christian school in Johnstown, Ohio. It was founded in the fall of 1999 by Gary and Tammy Smith.\n\nThe school started with just 13 students in grades 5-8. By the end of the first year, the school had grown to 65 students in those same grades. As the school has continued to grow, so has the number of teachers.\n\nBy the year 2009, Glacier Ridge had expanded to offer a preschool through 12th grade education, and the school had grown to almost 200 students. In the fall of 2013, the enrollment was over 300 students.\n\nThe school started with the first graduating class of 2002. They are now on their 11th graduating class, and the school's graduates continue to receive acceptance to universities across the United States. The school offers several Advanced Placement classes.\n\nGlacier Ridge has had its students participate in various competitions and competitions. Most notable are the sports teams, especially their basketball teams, which have qualified for state competition multiple times. The school has also had various music groups participate in state and regional competitions, and in the 2010-2011 school year, the school sent students to participate in an International Children's Games competition in Romania.\n\nIn the 2010-2011 school year, a group of the school's teachers were sent to Haiti to help establish a new orphanage, "Eli's Children's House", which was dedicated to Eli Pierre, who had died in a motorcycle accident. They were instrumental in bringing the orphanage into the community by helping establish new programs for the children, including English as a Second Language, Computer Lab, and Physical Education classes. The teachers assisted in the education of the orphans as well as working with the staff on the property.\n\nThe school has also taken various trips over the years, including trips to Virginia and New York City. The school also hosted an educational trip to Washington D.C. for one of their graduating classes.\n\nThe school has participated in various community events and service projects. One of the most notable is their annual "Twilight Prom" that is held each spring. Each year, the school hosts a prom for local high school students who have special needs. The students' dates are typically their own siblings.\n\nOn March 21, 2011, a fire destroyed the school's auditorium, causing over $1 million in damages. After the school received an outpouring of support, the school was able to begin construction on a new auditorium in time for the next school year.\n\nIn 2015, Glacier Ridge Christian School became part of the Christian School Association of Northeast Ohio.\n\nThe School is affiliated with the Association of Christian Schools International, the Ohio Christian Education Association, and the Christian School Association of Northeast Ohio.\n\n]" time="0.310"><properties><property name="score" value="0.14449836" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Akyem Kotoku\n\nAkyem Kotoku is one of the five traditional districts of the Ashanti Empire. The people are collectively known as Akyem Kotokus.\n\nAkyem Kotoku lies in the Eastern region of Ashanti and is bounded by the East Mamprusi to the East, Nkwantanan to the North, Ashanti to the West and Ahanta West to the South. It is part of Ashanti Region. The area is mainly mountainous with some rich valleys and hills. Akyem Kotoku is known as the "Area of Plenty".\n\nThe people are mainly farmers and fishermen. Its capital is Akyem Kotoku. It has two paramountcies, Buokrom and Kumasi. Buokrom, the newest paramountcy, was established in 1975. The Akyem Kotoku Traditional Council has nine chiefs.\n\nThe major towns are Abokobi, Domenase, Akropong, and Nsuaem. Other settlements include Aduanful, Boankraful, Denkyemerem, Anhwiaso, Gyankroma, Kwabenya, Nananom, Obofram, Okwensu, Ofoase, Nkoranza, Nsutam, Aduaso, Adom, Ofram, Odomankoma, Asafo, Anyigbe, Obofram, Kwabenya, Denkyemerem, Odumase, Nsutam, Aduaso, Nsuaem, Nsuaso, Tafo-Nsuaem, Manhyia, Boaso, Adom, Ofram, Anhwiaso, Adoase, Anyigbe, Boankraful, Okwensu, Ofoase, Nkoranza, Akropong, Gyankroma, Domenase, Egyir, Afram, Denkyerem, Nananom, Akuapem South, Asafo, Aboadze and Koma.\n\nThe Akyem Kotoku Traditional Council has nine paramountcies.\n\nThe Akyem Kotoku people have two coats of arms, one to use at home and the other for international use.\n\nThe arms used at home is a gold shield with a black anchor in the center. On the shield is a white dove with a golden olive branch in its beak. The dove is supported by two black wild dogs facing each other.\n\nThe shield is surmounted by a gold mural crown with five points and black stripes.\n\nThe shield is supported by two black lions standing on a white scroll. The scroll bears the motto: "MUSTER FAITHFULNESS" (Cape Coast Latin: "Fidelitas Summa Est").\n\nThe arms used outside the country is a gold shield with a black ram's head in the center. On the shield is a green laurel wreath.\n\nThe shield is surmounted by a gold mural crown with five points and black stripes.\n\nThe shield is supported by two black and white wild dogs standing on a white scroll. The scroll bears the motto: "MUSTER FAITHFULNESS" (Cape Coast Latin: "Fidelitas Summa Est").\n\nThe two dogs represent vigilance. The two lions in the home arms represent fortitude and strength.\n\n]" time="0.307"><properties><property name="score" value="0.021605136" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Frederic Myers\n\nFrederic William Henry Myers (15 January 1843 \u2013 18 January 1901) was a classical scholar, poet, playwright, novelist, and the founder of the Society for Psychical Research, which he led until his death.\n\nFrederic Myers was born at Kew, Surrey, the eldest son of Frederic Myers, a surgeon. He was educated at King's College School, and at St Paul's School in London. After a year at Trinity College, Cambridge (1861\u20132), he was a schoolmaster at Rugby from 1862 to 1871. In 1872 he became classical lecturer at University College, London. He became a member of the Council of the College (now part of UCL), and was appointed professor of Latin there in 1880. In 1876 Myers joined the Metaphysical Society, along with Alfred Tennyson, J. M. Barrie and others. His friendship with Barrie lasted for the remainder of his life, and Myers even accompanied Barrie and his wife on their honeymoon. Myers and Tennyson became close friends and met frequently in later years, as seen in their correspondence.\n\nMyers wrote prose and verse for periodicals, including a parody of Gerard Manley Hopkins, and some detective stories, and contributed to books of poetry and belles lettres, such as "Whistler and His Art" and the "Yellow Book". His poetry was praised by Henry James, who]" time="0.282"><properties><property name="score" value="0.4039993" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[His father was a professor and his mother was an economist. While growing up, he was exposed to the inspiring stories of his parents and their family members in China.\n\n\n\n\n\nKoh attended the University of Michigan where he received a bachelor of arts degree in economics, then went to the University of California, Berkeley where he earned a master of arts and doctor of philosophy degrees in economics.\n\n\n\n\n\nHe returned to Singapore in 1998 and joined the Singapore Civil Service.\n\n\n\n\n\nAs Deputy Secretary of the Ministry of Finance (2001-2007), he was involved in the design and implementation of the Singapore Savings Bond and the Central Provident Fund (CPF) investments.\n\n\n\n\n\nIn 2008, Koh was appointed as the Managing Director of the Monetary Authority of Singapore (MAS), where he oversees the development and implementation of macroeconomic policies for Singapore.\n\n\n\n\n\nHe is also the Chairman of the Government of Singapore Investment Corporation (GIC) which is responsible for the management of Singapore\u2019s foreign reserves and investment portfolio.]" time="0.426"><properties><property name="score" value="0.058522817" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05852282 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05852282
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assert 'Human' == 'AI'
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- AI
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+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Trixie Textured - My cat licked my thumb.\n\n\n\nJoin Date: Nov 2006 Posts: 4,592\n\nI have not been to China, though I have been to Japan and love it.\n\n\n\nI have friends in China who have also been to Japan, and they both love it, and neither of them think of it as a "poor" country. In fact, a lot of people who have been there say that China is much nicer.\n\n\n\nChina is not a poor country. They have tons of money and resources. Their problem is that they do not spend enough on infrastructure and don't value education as highly as they could. So their people do not make as much money as they could. And they don't have nice things. It is much nicer than India, but not as good as Japan. I would like to visit it, because I do not think I would be disappointed, but I don't expect it to be better than Japan.\n\n\n\nThey have a different mindset than us, and do things differently. Their government is not a democracy. It is a communist government. I think that is not a bad thing, and has it's benefits. They have much fewer guns and gun crime than we do. They are, for the most part, more honest than we are. Their infrastructure, while not as nice as ours, is very good. They spend more on infrastructure than we do. They have much more public transportation, and better public transportation. They are working on their environmental problems, and they have made more progress than we have. They have fewer social problems, and less crime than we do. They have a very good education system, especially compared to India.\n\n\n\nThey spend more money on schools and education, and invest more in their future, than we do.\n\n\n\nChina is a country that is far more well developed than many people in the US would think.\n\n\n\nThe fact that they have fewer guns, and better education and fewer social problems is probably why they have fewer school shootings than we do. I think we have way too many guns in this country, and that is a big part of the problem.\n\n\n\nJust my thoughts.]" time="0.270"><properties><property name="score" value="0.02915705" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["Say to them: 'As surely as I live, declares the Sovereign Lord, I take no pleasure in the death of the wicked, but rather that they turn from their ways and live. Turn! Turn from your evil ways! Why will you die, people of Israel?' declares the Sovereign Lord."\n\nEzekiel 33:11-11\n\nGod wants every sinner to be saved. He does not want people to perish but be saved. God hates sin, and sin destroys a person. But He loves people. He created them to have fellowship with Him and one day live in His Kingdom, and He does not want that for one person to be lost.\n\n\n\n\n\nGod's command to Ezekiel was that He was telling him to go and tell the people of Israel that they need to turn to God, because they were going to die if they did not. We know that Ezekiel told them the same thing, because God's word is truth. God's Word does not fail.\n\n\n\n\n\nWhat God is saying is that people are going to die if they do not turn to Him. People who reject God will die. The Bible says in Romans 1:32, "Though they know God's righteous decree that those who do such things deserve death, they not only continue to do these very things but also approve of those who practice them." God says that those people who do these things deserve death, and yet people continue to do them and approve of them.\n\n\n\n\n\nGod will not tolerate the sinful acts of humanity, but He wants every person to be saved. There is only one way to be saved. The Bible says in John 14:6, "Jesus answered, 'I am the way and the truth and the life. No one comes to the Father except through me.'\u201d\n\n\n\n\n\nNo one can be saved except through Jesus Christ, but when people put Jesus as their savior, they are saved. It's that simple.\n\n\n\n\n\nThere are many people who call themselves Christians who say that God wants everyone to be saved, and they quote Ezekiel 33:11 and John 3:16, but they don't realize that God's word is truth. God says in Revelation 21:8, "But the cowardly, the unbelieving, the vile, the murderers, the sexually immoral, those who practice magic arts, the idolaters and all liars\u2014their place will be in the fiery lake of burning sulfur. This is the second death."\n\n\n\n\n\nThere is only one way to be saved, and it is not through anyone or anything but Jesus Christ. Jesus is the only way to heaven. God says that all the people who are going to perish are going to go to a place called the second death. That's hell.\n\n\n\n\n\nWhen people quote Ezekiel 33:11 and John 3:16, they don't realize that God's word is truth. They don't realize that when they say that God wants everyone to be saved, they are not telling the truth. When they say that God wants everyone to be saved, they are putting God in a box, because God's word is truth. God says that those who do not accept Jesus as their Savior are going to perish. God's word is truth, and people who do not put their faith in Jesus Christ are going to die.\n\n\n\n\n\nThe Bible says in John 14:6, "Jesus answered, 'I am the way and the truth and the life. No one comes to the Father except through me.'\u201d\n\n\n\n\n\nJesus is the only way to the Father, and no one can be saved except through Him. He died on the cross for our sins, and He rose from the dead on the third day, and He sits at the right hand of God, interceding for us. It's that simple.\n\n\n\n\n\nLet's take a look at Ezekiel 33:11-11, and read it carefully.\n\n\n\n\n\n"Say to them: 'As surely as I live, declares the Sovereign Lord, I take no pleasure in the death of the wicked, but rather that they turn from their ways and live. Turn! Turn from your evil ways! Why will you die, people of Israel?' declares the Sovereign Lord."\n\n\n\n\n\nGod says that He takes no pleasure in the death of the wicked. God does not like it when people die. But God hates sin, and sin leads to death. If people want to live, they must turn from their sins and put their faith in Jesus Christ.\n\n\n\n\n\nIf people don't put their faith in Jesus Christ, they are going to perish. God doesn't want that. He doesn't want people to perish, but to live.\n\n\n\n\n\nGod wants people to put their faith in Jesus Christ. If people put their faith in Jesus Christ, they are saved. If they don't put their faith in Jesus Christ, they are going to perish. That's the truth. That's the message of Ezekiel 33:11-11.\n\n\n\n\n\nPeople are going to die if they don't put their faith in Jesus Christ. People will perish. People will be lost. People will be doomed. People will go to hell.\n\n\n\n\n\nLet's read Ezekiel 33:11-12.\n\n\n\n\n\n"For I take no pleasure in the death of anyone," declares the Sovereign Lord. "Repent and live!"\n\n\n\n\n\nGod takes no pleasure in the death of anyone. God does not want anyone to perish. He doesn't want anyone to die. He wants people to repent and live. God is saying that He is not going to stand back and watch as people perish. He's going to do something about it.\n\n\n\n\n\nGod says in Ezekiel 33:13-16, "Turn! Turn from your evil ways! Why will you die, people of Israel? I have no pleasure in the death of the wicked, but rather that they turn from their ways and live. Do you think I take pleasure in the death of the wicked? declares the Sovereign Lord. Rather, am I not pleased when they turn from their ways and live? Don't presume that you can say to yourselves]" time="0.634"><properties><property name="score" value="0.023843911000000002" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Working with an example - rotating through an array\n\nFor a number of years, I've been fascinated by the idea of writing code that can rotate through an array. Let's say I have the following array of numbers:\n\nvar myNumbers = [ 1, 2, 3, 4, 5 ];\n\nThe following snippet of code would display the same numbers in reverse order:\n\nfor ( var i = myNumbers.length - 1; i >= 0; i-- ) { console.log( myNumbers[i] ); }\n\nWhat's going on here?\n\nWe know that the index of an array can be used as a "pointer" to the location in memory that contains a particular item in an array. If the array myNumbers has five items, then myNumbers[0] , myNumbers[1] , myNumbers[2] , myNumbers[3] and myNumbers[4] will point to the values 1 , 2 , 3 , 4 and 5 respectively.\n\nIn the previous example, the code starts with the length of the array (5) and subtracts one from it. As we know that index 0 in an array contains the first item in the array, the previous code will execute the following steps:\n\nTake the length of the array (5) Subtract 1 (so we now have 4) Start at the index that contains the first item in the array (myNumbers[4] = 3) and run down the array until we reach the last item in the array (myNumbers[3] = 5)\n\nSo the above code will end up displaying the items in the array in reverse order, starting at index 4 and working backwards to index 0.\n\nAt this point, we have a good idea of how we can access the values in an array in a specific order, but how do we go the other way?\n\nIt would be great if we could simply use the same code as above, but add a "--" operator before the last number. That way, we could add a simple parameter to the code to control the range of numbers it will use.\n\nUnfortunately, we can't do that. While JavaScript will happily work with -- , it will also happily take -- in code and convert it to -1 , or the last number in an array. That's not going to do us any good, as we want the code to be flexible enough that we can work with a number that we specify as the range of numbers.\n\nSo let's look at a simple function that can give us the results we need.\n\nfunction rotate(numbers, direction, number) { numbers.reverse(); numbers.push(number); numbers.unshift(number); };\n\nThe rotate function above has three parameters, and will rotate the values in the numbers array.\n\nnumbers is the array we want to use.\n\ndirection is the parameter that allows us to choose whether we want the values to be rotated in the direction we specify. In this case, we've chosen direction to be either "right" or "left"\n\nnumber is the number we're using as the upper bound of the range that we want to use.\n\nLet's take a look at a simple example:\n\nvar numbers = [ 1, 2, 3, 4, 5 ]; rotate( numbers, "right" ); console.log( numbers ); //output: [ 1, 2, 3, 4, 5 ]\n\nAs we can see, the numbers array is simply rotated right by the number we specified. That's fine, but let's add in some code that we can use to control which numbers are displayed:\n\nvar numbers = [ 1, 2, 3, 4, 5 ]; rotate( numbers, "right", 1 ); console.log( numbers ); //output: [ 1, 4, 3, 5, 2 ]\n\nWe can see that we've rotated the numbers so that the first number in the array is now number 1 , and the next number in the array is 4 .\n\nWe've also specified that we want to rotate in a right-handed manner, by passing "right" as the second parameter. This means that we have access to the following rotation values:\n\nrotate( numbers, "left" ); rotate( numbers, "right" ); rotate( numbers, "right" ); rotate( numbers, "right" ); rotate( numbers, "left" );\n\nIf we try to access the rotate function with "left" as the parameter, we'll see the following output:\n\nvar numbers = [ 1, 2, 3, 4, 5 ]; rotate( numbers, "left" ); console.log( numbers ); //output: [ 4, 3, 5, 2, 1 ]\n\nNot quite what we wanted, right?\n\nWhat we want is to be able to take an array, specify the number of numbers we want to display, and be able to choose the direction of rotation.\n\nWe also want to ensure that the values we are displaying are always within the array's bounds, and we're using them correctly.\n\nThe good news is that it's not too difficult to do this. We simply need to know what we want the code to look like, and write the code to do what we want it to do.\n\nLet's take a look at some simple code to display the numbers in an array in a given direction:\n\nfunction rotateArray( numbers, direction, startAt ) { numbers.reverse(); numbers.push( startAt ); numbers.unshift( startAt ); };\n\nrotateArray function\n\nThis is the code we'll use to display the numbers in the numbers array in the direction we specify. We'll start with a simple parameter:\n\nstartAt is the number we're displaying. It can either be the first number in the array, or any number within the array.\n\nLet's take a look at the code again:\n\nfunction rotateArray( numbers, direction, startAt ) { numbers.reverse(); numbers.push( startAt ); numbers.unshift( startAt ); };\n\nUsing this simple function, we can take any number of numbers, and display them in the direction we want. Let's look at a quick example:\n\nvar numbers = [ 1, 2, 3, 4, 5 ]; rotateArray( numbers, "left", 3 ); console.log( numbers ); //output: [ 4, 3, 5, 2, 1 ]\n\nThis time, we've used "left" as the direction, and we've also used the parameter "3" as the startAt value. The result is that we now have the numbers displayed in the array starting at the number 3 .\n\nIf we use a number that isn't within the bounds of the array, we'll get the following result:\n\nvar numbers = [ 1, 2, 3, 4, 5 ]; rotateArray( numbers, "right", 3 ); console.log( numbers ); //output: [ 5, 2, 4, 1, 3 ]\n\nAs you can see, the direction we've specified is "right", and the value we've specified for startAt is 3 . Unfortunately, this value isn't within the bounds of the array, so the values in the array have been displayed starting from the last number in the array.\n\nLet's take a look at how we can use this code to work with a number that's outside the bounds of the array:\n\nvar numbers = [ 1, 2, 3, 4, 5 ]; rotateArray( numbers, "right", 6 ); console.log( numbers ); //output: [ 5, 2, 4, 1, 3 ]\n\nThis time, we've specified "right" as the direction, and a value of 6 as the startAt parameter. The result is that we now have the values displayed in the array starting at the number 6 .\n\nThis time, the result we want is displayed in the array, but there's a problem. We don't want the number 6 to be the start of the array. Instead, we want it to be the last number in the array.\n\nThe good news is that we can easily handle this by modifying the code slightly:\n\nfunction rotateArray( numbers, direction, startAt ) { numbers.reverse(); numbers.push( startAt ); numbers.unshift( startAt ); };\n\nUsing the simple rotation code above, we can now take any array, specify the number we want to display, and choose the direction we want to use. This means we can write some simple code that can work with any number, regardless of its position in the array.\n\nThe next step is to write some code that can ensure the number we specify as the startAt is in the range that we expect.\n\nLet's take a look at how we can do that:\n\nfunction rotateArray( numbers, direction, startAt ) { if( startAt >= numbers.length ) { throw new RangeError("Start at is outside of the]" time="0.581"><properties><property name="score" value="0.0009482333" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Contents\n\n1. The Meaning of Love\n\n2. Our Attitude Toward Others\n\n3. The Two Great Commandments\n\n4. Developing Love\n\n5. How to Help Others\n\n6. The Golden Rule\n\n7. The Commandments in the New Testament\n\n8. Tolerance\n\n\nCHAPTER 1\n\nThe Meaning of Love\n\nBefore we can love others, we must know the meaning of love. It is important to love God and obey Him and to have a right relationship with Him. But to have a right relationship with Him we must love Him. That means that we must have a good relationship with all His laws.\n\nOf course we can't keep all the commandments all the time. Yet we must have a good relationship with them. Otherwise we will not know what God is like.\n\nLove is based on God's law.\n\nRomans 13:10. The commandments, You shall not commit adultery, You shall not steal, You shall not bear false witness, You shall not covet; and any other commandment, are summed up in this word, You shall love your neighbor as yourself.\n\nGalatians 5:14. For all the law is fulfilled in one word, even in this: You shall love your neighbor as yourself.\n\nLove is based on God's law. We should study God's commandments and know the laws He has given us. Then we will know how to have a good relationship with Him.\n\nOne reason we are to love God and obey Him is that it is important to have a good relationship with God. We need to know how much God loves us. Without knowing this we cannot have a right relationship with God. We need to have a good relationship with Him so we can be happy and serve Him better.\n\nLet us understand what love is.\n\n1 John 4:8,9. He who does not love does not know God, for God is love. In this the love of God was manifested toward us, that God has sent His only begotten Son into the world, that we might live through Him.\n\nIn these verses John explained that love is the opposite of lawlessness. Love is the opposite of murder, hatred, malice, evil, adultery, stealing, lying, and a lot of other bad things.\n\nRomans 13:8-10. Owe no man anything, but to love one another: for he that loves another has fulfilled the law. For this, You shall not commit adultery, You shall not kill, You shall not steal, You shall not covet, and if there be any other commandment, it is briefly comprehended in this saying, namely, You shall love your neighbor as yourself. Love does no harm to a neighbor; therefore love is the fulfillment of the law.\n\nWe learn from this that the opposite of love is lawlessness. The opposite of love is murder, hatred, envy, malice, evil, and all the other things mentioned in these verses.\n\nVerse 10 says, "Love does no harm to a neighbor." In other words, love is a good thing. It is a good thing to have a good relationship with God.\n\nRomans 13:8 says, "Love does no harm to a neighbor." Love helps and blesses others.\n\nLove is a good thing. The reason love is a good thing is because God is love.\n\n1 John 4:16. And we have known and believed the love that God has for us. God is love; and he who abides in love abides in God, and God in him.\n\nGod is love.\n\n1 John 4:7-11. Beloved, let us love one another: for love is of God; and every one that loves is born of God, and knows God. He that loves not knows not God; for God is love. In this was manifested the love of God toward us, because that God sent his only begotten Son into the world, that we might live through him. Herein is love, not that we loved God, but that he loved us, and sent his Son to be the propitiation for our sins. Beloved, if God so loved us, we ought also to love one another. No man has seen God at any time. The only begotten Son, which is in the bosom of the Father, he has declared him.\n\nVerse 8 says, "God is love." God's name is Love.\n\nGod's name is Love.\n\nJohn 4:8. \u2026 the well was deep; and I said, "How shall I get down?"\n\nAnd he said, "Come, and I will show you."\n\n9. And he said, "Draw you [a] little water out of the well, and \u2026 drink."\n\n10. And I said, "Sir, give me [a] little to drink."\n\n11. And he said, "Drink, my [b] son, and \u2026 your eyes shall be opened."\n\n12. And I drank, and it was as if I had had new vision given to me; for I could see [c] through those walls of water.\n\n13. And he said to me, "Go [a] down, for the water is [b] yet a little way below the earth. \u2026\n\n15. \u2026 This water is [c] that which I said \u2026 will make you come up hither."\n\n16. And as he spoke, I drank; and I was [d] inebriated, and my eyes were opened; and I was able to see. \u2026\n\n19. \u2026 "Come," he said, "follow me \u2026 and I will give you \u2026 rest."\n\nGod is the God of rest.\n\n1 Thessalonians 4:9. \u2026 God has not appointed us to wrath, but to obtain salvation by our Lord Jesus Christ.\n\nGod is our salvation. God is our rest. God is our peace.\n\nGod is our rest.\n\n1 Peter 2:6. \u2026 you may be \u2026 a kind of first-fruits of his creatures.\n\nGod is our first fruits.\n\n2 Timothy 2:13. If we are faithless, he remains faithful; for he cannot deny himself.\n\nGod is faithful.\n\nGod is the God of rest.\n\nGod is our salvation.\n\nGod is our peace.\n\nGod is our rest.\n\nHebrews 4:10-13. For he who has entered His rest has himself also ceased from his own works, as God did from His. Let us therefore be diligent to enter that rest \u2026\n\n12. \u2026 For the word of God is living and active, and sharper than any two-edged sword, and piercing even to the division of soul and spirit, and of joints and marrow, and is a discerner of the thoughts and intents of the heart.\n\n13. \u2026 neither is there any creature that is not manifest in his sight; but all things are naked and opened to the eyes of him with whom we have to do.\n\nGod is a discerner of the thoughts and intents of the heart.\n\nGod sees everything.\n\nGod sees everything.\n\n1 John 4:8,9. He who does not love does not know God, for God is love. In this the love of God was manifested toward us, that God has sent His only begotten Son into the world, that we might live through Him.\n\nGod is love.\n\n1 John 3:16,18. Hereby perceive we the love of God, because he laid down his life for us: and we ought to lay down our lives for the brethren.\n\n19. But whoso has this world's goods, and sees his brother in need, and shuts up his heart from him, how does the love of God abide in him?\n\nGod is love.\n\nGod is our rest.\n\nGod is our salvation.\n\nGod is our peace.\n\nGod is a discerner of the thoughts and intents of the heart.\n\nGod is love.\n\nGod is our rest.\n\nGod is our salvation.\n\nGod is our peace.\n\nGod is a discerner of the thoughts and intents of the heart.\n\nThe Bible says that God is love.\n\nWe can study love.\n\n1 John 4:7-11. Beloved, let us love one another: for love is of God; and every one that loves is born of God, and knows God. He that loves not knows not God; for God is love. In this was manifested the love of God toward us, because that God sent his only begotten Son into the world, that we might live through him. Herein is love, not that we loved God, but that he loved us, and sent his Son to be the propitiation for our sins. Beloved, if God so loved us, we ought also to love one another. No man has seen God at any time. The only begotten Son, which is in the bosom of the Father, he has declared him.\n\nVerse 11 says, "Herein is love, not that we loved God, but that he loved us." The opposite of love is lawlessness. But the opposite of love is not lawlessness. The opposite of love is law.\n\nLoving God and obeying Him is loving Him.\n\nThe Bible says that God is love.\n\nLoving God and obeying Him is loving Him.\n\nLoving God and obeying Him is loving God.\n\nJohn 14:21. He that has my commandments,]" time="0.609"><properties><property name="score" value="0.086402328" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Interviews\n\nInterview with Ariel Efraim (Soilwork)\n\nInterview with Steven Rosen (August Burns Red)\n\nInterview with Brent Hinds (Mastodon)\n\nInterview with Paul Kuhr (I See Stars)\n\nInterview with Christian Antidormi (Hatebreed)\n\nInterview with Jack Syperek (Structures)\n\nInterview with Ben Gordon (The Treatment)\n\nInterview with Doc Coyle (God Forbid)\n\nInterview with Chris Barnes (Six Feet Under)\n\nInterview with Mike D (The Sword)\n\nInterview with Russ Rankin (The Slackers)\n\nInterview with Claudio Sanchez (Coheed and Cambria)\n\nInterview with Udo Dirkschneider (Accept)\n\nInterview with Ben Weinman (Dillinger Escape Plan)\n\nInterview with Matt Pike (High On Fire)\n\nInterview with Joe Duplantier (Gojira)\n\nInterview with Johannes Eckerstr\xf6m (Evergrey)\n\nInterview with Pete Loose (Reel Big Fish)\n\nInterview with Pete Wentz (Fall Out Boy)\n\nInterview with Daniel Svensson (Raubtier)\n\nInterview with Chino Moreno (Deftones)\n\nInterview with Pierre Bouvier (Simple Plan)\n\nInterview with Jon Egan (The Ghost Of A Thousand)\n\nInterview with Mike D (Lack Of Afro)\n\nInterview with Michael Crafter (Sevendust)\n\nInterview with Charlie Benante (Anthrax)\n\nInterview with Rob Caggiano (Volbeat)\n\nInterview with Ronnie Atkins (Pretty Maids)\n\nInterview with Gee Anzalone (Exhorder)\n\nInterview with Micky Shirley (Five Finger Death Punch)\n\nInterview with Oderus Urungus (GWAR)\n\nInterview with Ryan Downey (Texas Hippie Coalition)\n\nInterview with Chris Chasse (Unearth)\n\nInterview with Lee Altus (Suffocation)\n\nInterview with Roy Mayorga (Soulfly)\n\nInterview with Gus G (Firewind)\n\nInterview with Paul Allender (In Flames)\n\nInterview with Francesco Artusato (All Shall Perish)\n\nInterview with Rody Walker (Pyogenesis)\n\nInterview with Mike Dean (Slipknot)\n\nInterview with Angela Gossow (Arch Enemy)\n\nInterview with Trevor Strnad (The Black Dahlia Murder)\n\nInterview with Mike Peters (The Alarm)\n\nInterview with Jonas Ekdahl (Freak Kitchen)\n\nInterview with Dave Ellefson (Megadeth)\n\nInterview with Corey Taylor (Slipknot)\n\nInterview with Keith Buckley (Every Time I Die)\n\nInterview with Jack Frost (Kill Devil Hill)\n\nInterview with Josh Rand (Temple of Brutality)\n\nInterview with Michael Amott (Arch Enemy)\n\nInterview with Scott Gorham (Thin Lizzy)\n\nInterview with Matt Heafy (Trivium)\n\nInterview with Joe Kresge (Unearth)\n\nInterview with Randy Blythe (Lamb of God)\n\nInterview with Benji Webbe (Dimmu Borgir)\n\nInterview with Max Cavalera (Soulfly)\n\nInterview with John Bush (Armored Saint)\n\nInterview with Davey Muise (Exhorder)\n\nInterview with Stephen Carpenter (Deftones)\n\nInterview with Dani Filth (Cradle Of Filth)\n\nInterview with Leif Cuzner (Darkane)\n\nInterview with George \u201cCorspegrinder\u201d Fisher (Cannibal Corpse)\n\nInterview with Steve Asheim (Hatebreed)\n\nInterview with Bobby Blitz Ellsworth (Overkill)\n\nInterview with Adam Dutkiewicz (Killswitch Engage)\n\nInterview with Mick Murphy (Exhumed)\n\nInterview with Doug Pinnick (King\u2019s X)\n\nInterview with Alexi Laiho (Children Of Bodom)\n\nInterview with M. Shadows (Avenged Sevenfold)\n\nInterview with Alex Holzwarth (Rhapsody Of Fire)\n\nInterview with Carlos Cruz (Soulfly)\n\nInterview with Glenn Hughes (Deep Purple/Black Country Communion)\n\nInterview with Oliver Palotai (Kamelot)\n\nInterview with Meegs Rascon (The Mars Volta)\n\nInterview with Joakim Brod\xe9n (Sabaton)\n\nInterview with Tim \u201cRipper\u201d Owens (Iced Earth/Yngwie Malmsteen)\n\nInterview with Matt Heafy (Trivium)\n\nInterview with Warrel Dane (Nevermore)\n\nInterview with Zach Myers (Shinedown)\n\nInterview with Michael Poulsen (Volbeat)\n\nInterview with Michael Amott (Arch Enemy)\n\nInterview with Mat Sinner (Primal Fear)\n\nInterview with Bj\xf6rn \u201cSpeed\u201d Strid (Soilwork)\n\nInterview with Matt Heafy (Trivium)\n\nInterview with Rob Flynn (Machine Head)\n\nInterview with Serj Tankian (System Of A Down)\n\nInterview with Ville Valo (HIM)\n\nInterview with Jimmy DeGrasso (Megadeth)\n\nInterview with Joey Jordison (Slipknot)\n\nInterview with Chris Jericho (Fozzy/Fozzy Osbourne)\n\nInterview with Jon Donais (Shadows Fall)\n\nInterview with Jason Hook (Five Finger Death Punch)\n\nInterview with Steve Mazur (Grave Digger)\n\nInterview with Bj\xf6rn \u201cSpeed\u201d Strid (Soilwork)\n\nInterview with Sonny Sandoval (P.O.D.)\n\nInterview with Serj Tankian (System Of A Down)\n\nInterview with Fredrik Thordendal (Meshuggah)\n\nInterview with Wes Borland (Limp Bizkit)\n\nInterview with Alexi Laiho (Children Of Bodom)\n\nInterview with Blaze Bayley (Iron Maiden)\n\nInterview with Mark Hunter (Chimaira)\n\nInterview with Max Cavalera (Soulfly/Sepultura)\n\nInterview with Dave Lombardo (Slayer)\n\nInterview with Bruce Dickinson (Iron Maiden)\n\nInterview with Morgan Lander (Fear Factory)\n\nInterview with Oliver Palotai (Kamelot)\n\nInterview with James Hetfield (Metallica)\n\nInterview with Al Jourgensen (Ministry)\n\nInterview with Corey Taylor (Stone Sour/Slipknot)\n\nInterview with Alex Skolnick (Testament)\n\nInterview with Charlie Benante (Anthrax)\n\nInterview with Chris Reifert (Autopsy)\n\nInterview with Lajon Witherspoon (Sevendust)\n\nInterview with Jason McMaster (Grave Robber)\n\nInterview with Jon Howard (Light The Torch)\n\nInterview with Neil Fallon (Clutch)\n\nInterview with Dino Cazares (Fear Factory)\n\nInterview with Oderus Urungus (GWAR)\n\nInterview with Rex Brown (Pantera)\n\nInterview with Dave Lombardo (Slayer)\n\nInterview with Serj Tankian (System Of A Down)\n\nInterview with John Moyer (Disturbed)\n\nInterview with Mike Portnoy (Adrenaline Mob)\n\nInterview with King Diamond\n\nInterview with Trevor Strnad (The Black Dahlia Murder)\n\nInterview with Mikael \xc5kerfeldt (Opeth)\n\nInterview with Scott Ian (Anthrax)\n\nInterview with Paul Gray (Slipknot)\n\nInterview with Casey Chaos (Amen)\n\nInterview with Opeth\u2019s Mikael \xc5kerfeldt\n\nInterview with Mark Morton (Lamb Of God)\n\nInterview with Shawn Drover (Megadeth)\n\nInterview with Chino Moreno (Deftones)\n\nInterview with Serj Tankian (System Of A Down)\n\nInterview with Bruce Corbitt (Corrosion Of Conformity)\n\nInterview with Ray Alder (Fates Warning)\n\nInterview with Rob \u201cBlasko\u201d Nicholson (Ozzy Osbourne)\n\nInterview with Tom Araya (Slayer)\n\nInterview with Max Cavalera (Soulfly)\n\nInterview with Ryan Martinie (Cynic)\n\nInterview with Max Cavalera (Soulfly)\n\nInterview with Jason Newsted (Voivod)\n\nInterview with Mick Murphy (Exhumed)\n\nInterview with Lars Frederiksen (Rancid)\n\nInterview with Mike Muir (Suicidal Tendencies)\n\nInterview with Dave Mustaine (Megadeth)\n\nInterview with Neil Fallon (Clutch)\n\nInterview with Bruce Dickinson (Iron Maiden)\n\nInterview with Maynard James Keenan (Tool)\n\nInterview with Mike \u201cRat\u201d Ratner (S.O.D.)\n\nInterview with Max Cavalera (Soulfly)\n\nInterview with Tom Araya (Slayer)\n\nInterview with Chuck Billy (Testament)\n\nInterview with Tom Araya (Slayer)\n\nInterview with Phil Anselmo (Down)\n\nInterview with King Diamond\n\nInterview with Corey Taylor (Stone Sour/Slipknot)\n\nInterview with Dave Mustaine (Megadeth)\n\nInterview with Lars Ulrich (Metallica)\n\nInterview with Jerry Cantrell]" time="0.599"><properties><property name="score" value="0.0438856735" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04388567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04388567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Apple\u2019s ResearchKit is off to a good start, but there\u2019s plenty of work to be done.\n\n\n\nResearchKit was launched in March as a way for Apple\u2019s developers to easily tap into medical data from the iPhone to help researchers track and collect information about a variety of health conditions. Since its debut, there have been nearly 2,000 registered medical researchers, while more than 40 institutions have launched clinical studies through the app platform.\n\n\n\nBut there are several hurdles for Apple and its partners. On Wednesday, Dr. Harvey Fineberg, president of the Institute of Medicine, will join at a panel discussion at Mount Sinai Hospital in New York to examine what works and what\u2019s missing in the fast-evolving field of mobile health.\n\n\n\nThe session, titled \u201cWhat Are the Future Directions for ResearchKit?\u201d comes after a first wave of successful projects on ResearchKit, including apps that help people manage diabetes, heart disease and asthma.\n\n\n\nThere are also some examples of the problems Apple is facing as it tries to get more partners to adopt the tool. Earlier this month, a major player in the diabetes community said it would not be taking part in the app\u2019s data collection. The Juvenile Diabetes Research Foundation said in a statement that its members were not interested in the iPhone platform and \u201cwould prefer to conduct research studies using our own patient data that is gathered on an Android platform.\u201d\n\n\n\nThat\u2019s likely an expensive prospect for the organization, given the popularity of iPhones in the United States. As of last year, Android devices accounted for just over half of all U.S. smartphone subscribers, while iOS devices made up around 41 percent. That\u2019s according to the Pew Research Center, which estimated last year that there were 121 million iPhone users in the United States.\n\n\n\nThe success of Apple\u2019s platform will hinge in part on how it handles data privacy and security concerns. Apple had to clear some hurdles in the early days of ResearchKit because many people were concerned about privacy when they heard it would rely on data from Apple\u2019s servers. Apple has since taken several steps to make it clear that the data is anonymous and that people can opt out of data collection.\n\n\n\nThe app program could also be a major part of the iPhone\u2019s future if it takes off. It could help it better compete against the likes of Google, which is also hoping to get in on the health data space with a new Android product called Android Wear.\n\n\n\nThe first public version of ResearchKit will be unveiled on Wednesday, the panel will also include representatives from Mount Sinai and Pfizer.\n\n\n\nThat event will be at 11:30 a.m. EDT in New York City, and it will be livestreamed on Fortune\u2019s website.]" time="0.323"><properties><property name="score" value="0.0012089905" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00120899 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00120899
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Get the biggest daily news stories by email Subscribe Thank you for subscribing We have more newsletters Show me See our privacy notice Could not subscribe, try again later Invalid Email\n\nAs the Queen's cousin, Lady Amelia Windsor is more used to socialising with the royal family than you or I.\n\nBut even for her, it seems the sight of seeing Kate Middleton and Prince William in attendance at Pippa Middleton's wedding - as well as the newlyweds' own big day - was enough to make her feel "uncomfortable".\n\nSpeaking at the wedding of one of her friend's brothers in Kent, the 28-year-old spoke about how it made her feel to have them there, reports the Daily Mail .\n\nShe said: "Well I think it is a beautiful wedding, obviously, because it's Pippa and James.\n\n"I've never been to a wedding before, so I don't know really what it should be like. But I do find it quite uncomfortable seeing them."\n\nThe Royal family came together to celebrate the wedding of Kate's sister to hedge fund manager James Matthews in the Berkshire village of Englefield.\n\n(Image: Getty Images Europe)\n\n(Image: PA)\n\n(Image: PA)\n\nAnd while Pippa and James' wedding was a private affair with just 200 guests, they were still surrounded by some royals as well as other notable names.\n\nLady Amelia's father is the Queen's first cousin, so it was no surprise to see the Queen herself attend the wedding, alongside Prince Harry and Duchess Meghan.\n\nThe Princesses Beatrice and Eugenie were also there, as well as Kate's sister, Pippa's brother James Middleton, David and Victoria Beckham and Sir Elton John.\n\nLady Amelia revealed that she even had a few words with Harry and Meghan, with the former asking her how she felt about her cousin's big day.\n\nShe said: "I had a little conversation with Harry and Meghan, and they said how lovely the wedding was. I said 'yes, but I don't feel very comfortable seeing you all here' and Harry said, 'Oh well, you're used to it'.\n\n(Image: PA)\n\n(Image: PA)\n\n"I said, 'Yes, but it is still very strange to see you here'. I suppose you can't blame me, I am a bit naive. But the whole thing was really lovely."\n\nShe added: "I mean, James is my cousin, I grew up with him and I love him dearly, so it was really lovely to see him. It was a lovely wedding, they are such a lovely couple. I am so pleased they are so happy."\n\n(Image: Getty Images Europe)\n\n(Image: Getty Images Europe)\n\nAnd as for what she thought of her father's outfit - which caused much comment among fans - she admitted she wasn't sure.\n\nShe said: "Well, he always wears an odd choice of clothes, but that is what he likes. It wasn't bad, I mean he didn't look like a big prawn."\n\nShe added: "It was lovely to see him happy."]" time="0.311"><properties><property name="score" value="0.4662261" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.4662261 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.4662261
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Dewalt DW3200 review, there are few tools that are as versatile as this one. You may have a thousand bucks of cordless tools, but there\u2019s nothing that will do as much as this one will do. As you might have noticed, the construction of this unit is incredibly sturdy, so that you don\u2019t have to worry about it breaking when you use it. Also, it is a bit heavy, and it will take a while to get used to using it, especially if you have not used any other heavy drills.\n\nPower\n\nWe also tested the power of this Dewalt DW3200 and we must say that it is very impressive. It delivers 3,300 RPM, which is more than enough to bore holes and drill in all kinds of materials. It can easily penetrate into wood, brick, or concrete and it can bore holes up to two inches. The trigger lock mechanism also works well, which makes this drill safer to use.\n\nCordless or corded?\n\nIt is important to remember that this drill can work either as a corded or a cordless unit, and this is very important for you to know. This Dewalt DW3200 uses the 20 volt lithium-ion batteries and they can last longer than you might expect. They are also very light and durable, so you will be able to use them for a long time. There are four batteries included in the kit, and they can last for a long time. You can also get a second battery if you want to have more freedom, and this will make the drill work for a much longer time.\n\nExtra Features\n\nYou may also like the extra features included in this Dewalt DW3200. There is the light that will make the job easier, and there are also other important features, like the variable speed. This is also a very durable drill, so it will last for a very long time. Also, the build quality is fantastic, so you don\u2019t have to worry about it breaking easily.\n\nOverall\n\nIf you have a lot of different drilling needs, this is the drill for you. This drill is perfect for the casual user, but it can also be used by professionals. It is also very durable, so you can use it for a very long time, and you will get the most for your money. You should also remember that this drill is very powerful, and it can work for a long time, without breaking down.\n\nIf you want to see what more we have, you can visit Amazon.com and check all of the available drills. You can also check our article on the best reciprocating saw, to see what the best product in this category is. Also, don\u2019t forget to like and share this article, if you liked it.]" time="0.303"><properties><property name="score" value="0.03911174" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[LAS VEGAS, NV - JANUARY 07: Recording artist Demi Lovato performs onstage during the 2017 DIRECTV NOW Super Saturday Night Concert at Park Theater at Park MGM on January 7, 2017 in Las Vegas, Nevada. (Photo by Kevin Winter/Getty Images for DIRECTV) (Photo: Kevin Winter, 2017 Getty Images)\n\nLAS VEGAS - Former Disney star Demi Lovato will release a new single from her sixth studio album on June 15th.\n\nThat's according to a video of Lovato, 26, posted on the YouTube channel of Las Vegas radio station KVEG.\n\nThe new album is the follow-up to 2015's "Confident," which features the top 10 hits "Cool for the Summer" and "Confident."\n\nMore: Everything you need to know about this year's 2017 Route 91 Harvest festival\n\nMore: Demi Lovato set for national tour with DJ Khaled\n\nMore: Demi Lovato re-engages with ex-boyfriend Wilmer Valderrama, so could there be more?\n\nThe pop singer also revealed she is launching a partnership with American Airlines to celebrate Hispanic Heritage Month, and she plans to go on a national tour with DJ Khaled.\n\nDemi Lovato to Release New Single, Announce Album Title on June 15th https://t.co/OBkKbXWySZ \u2014 Pop Crave (@PopCrave) June 1, 2017\n\nRead or Share this story: https://usat.ly/2rVY4mA]" time="0.277"><properties><property name="score" value="0.0016723684" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00167237 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00167237
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[RACISM IN BRITAIN HAS BECOME SO entrenched that it is becoming a bigger problem than it was at the time of the Birmingham pub bombings, when the threat of violent nationalism in the late 1970s prompted the first official inquiry into racial attacks, according to a report published today by the Equality and Human Rights Commission (EHRC).\n\nThe report, We\u2019re still struggling: the legacy of the Stephen Lawrence inquiry, says that despite years of measures to increase the representation of ethnic minorities in public life and protect them from discrimination, they are still \u201con the receiving end of racism\u201d, with black people twice as likely to suffer police stop and search tactics as whites.\n\nFigures from the Crown Prosecution Service (CPS) show that more than 40 per cent of cases involving charges of racially aggravated harassment are dropped, with charges reduced to more minor ones, or not pursued. The EHRC report cites figures showing that more than half of black and Asian people report experiencing discrimination when looking for a job.\n\nIn October, the Telegraph reported how]" time="0.319"><properties><property name="score" value="0.011899202" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0118992 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0118992
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[# This Source Code Form is subject to the terms of the Mozilla Public\n\n# License, v. 2.0. If a copy of the MPL was not distributed with this\n\n# file, You can obtain one at http://mozilla.org/MPL/2.0/.\n\n# The following comment must be at the start of a new line.\n\n#\n\n#\n\n# The contents of this file are subject to the Mozilla Public\n\n# License Version 1.1 (the "License"); you may not use this file\n\n# except in compliance with the License. You may obtain a copy of\n\n# the License at http://www.mozilla.org/MPL/\n\n# Software distributed under the License is distributed on an "AS\n\n# IS" basis, WITHOUT WARRANTY OF ANY KIND, either express or implied.\n\n# See the License for the specific language governing rights and\n\n# limitations under the License.\n\n# The Original Code is Mozilla Communicator client code, released\n\n# March 31, 1998.\n\n# The Initial Developer of the Original Code is\n\n# Netscape Communications Corporation.\n\n# Portions created by the Initial Developer are Copyright (C) 1998\n\n# the Initial Developer. All Rights Reserved.\n\n# Contributor(s):\n\n#\n\n# Alternatively, the contents of this file may be used under the terms of\n\n# either of the GNU General Public License Version 2 or later (the "GPL"),\n\n# or the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),\n\n# in which case the provisions of the GPL or the LGPL are applicable instead\n\n# of those above. If you wish to allow use of your version of this file only\n\n# under the terms of either the GPL or the LGPL, and not to allow others to\n\n# use your version of this file under the terms of the MPL, indicate your\n\n# decision by deleting the provisions above and replace them with the notice\n\n# and other provisions required by the GPL or the LGPL. If you do not delete\n\n# the provisions above, a recipient may use your version of this file under\n\n# the terms of any one of the MPL, the GPL or the LGPL.\n\n#\n\n# ***** END LICENSE BLOCK *****\n\nMOCHITEST_MANIFESTS += [\n\n' xpcshell.ini ' ,\n\n' mochitest-glue.ini ' ,\n\n' mochitest-plain.ini ' ,\n\n]\n\nDIST_DIRS += [\n\n' external/ ' ,\n\n' ipc/ ' ,\n\n' modules/ ' ,\n\n]\n\nEXTRA_COMPONENTS += [\n\n' mozLoop.js ' ,\n\n' webextensions.js ' ,\n\n]\n\ndeps = [\n\n'../base ' ,\n\n'../browser/base ' ,\n\n'../browser/components/migration ' ,\n\n'../browser/components/places ' ,\n\n'../browser/themes/shared ' ,\n\n'../content/base ' ,\n\n'../content/html ' ,\n\n'../content/xul ' ,\n\n'../embedding/browser ' ,\n\n'../embedding/components/browser ' ,\n\n'../embedding/components/toolkit ' ,\n\n'../extensions/browser/api ' ,\n\n'../extensions/common/moz.build ' ,\n\n'../gfx/2d ' ,\n\n'../gfx/layers ' ,\n\n'../intl ' ,\n\n'../netwerk ' ,\n\n'../printing ' ,\n\n'../services/sync ' ,\n\n'../toolkit/components/global ' ,\n\n'../toolkit/components/printing ' ,\n\n'../toolkit/components/satchel ' ,\n\n'../toolkit/crashreporter ' ,\n\n'../toolkit/library ' ,\n\n'../toolkit/mozapps/extensions ' ,\n\n'../toolkit/mozapps/extensions/extensions-types.js ' ,\n\n'../xpcom/base ' ,\n\n'../xpcom/build ' ,\n\n'../xpcom/build/shared-nspr ' ,\n\n'../xpcom/build/shared-nspr/src ' ,\n\n'../xpcom/ds ' ,\n\n'../xpcom/ds/io ' ,\n\n'../xpcom/ds/xpcom ' ,\n\n'../xpcom/glue ' ,\n\n'../xpcom/io ' ,\n\n'../xpcom/threads ' ,\n\n'../xpcom/threads/src ' ,\n\n'../xpcom/threads/xpcom ' ,\n\n' ../xpfe/appshell/nsAppShell.cpp ' ,\n\n' ../xpfe/appshell/nsAppShell.h ' ,\n\n' ../xpfe/appshell/nsAppsShellService.cpp ' ,\n\n' ../xpfe/appshell/nsAppsShellService.h ' ,\n\n' ../xpfe/appshell/nsNativeAppSupportWin.cpp ' ,\n\n' ../xpfe/appshell/nsNativeAppSupportWin.h ' ,\n\n' ../xpfe/appshell/nsNativeAppSupportXPConnect.cpp ' ,\n\n' ../xpfe/appshell/nsNativeAppSupportXPConnect.h ' ,\n\n' ../xpfe/appshell/nsWindowRoot.cpp ' ,\n\n' ../xpfe/appshell/nsWindowRoot.h ' ,\n\n' ../xpfe/appshell/nsXULAppAPI.h ' ,]" time="0.309"><properties><property name="score" value="0.0026306708" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The world of professional wrestling is always changing, but the superstars themselves can sometimes get lost in the shuffle. Sometimes, the changes within the industry are so drastic that a superstar's popularity can get left in the past. WWE's superstars who were the best during their career, but are rarely talked about anymore.\n\nWWE is still the leader of the wrestling world. The company is no stranger to using the Attitude Era as a way to sell itself. They have had so many superstars through the years that they should make up their own Hall of Fame. Some of those superstars are the ones who are mentioned the most.\n\nThe casual fan knows about Hulk Hogan, Stone Cold, and The Rock. That is what makes this so fun. Everyone wants to see these greats become legends of the industry, but it is also nice to remember the stars who used to be a big deal. Whether they were a big deal in WWE or not, they are still worth remembering.\n\nContinue scrolling to keep reading Click the button below to start this article in quick view Share Tweet Email Copy Link Copied\n\n10 Sin Cara\n\nvia trbimg.com\n\nSin Cara has become a joke of a superstar. It has been a series of unfortunate events that have taken him from being a major star to a sideshow that should be in the pre-show, not a main event. When Sin Cara debuted, he was seen as a major star that was going to be used a lot. It took some time, but it finally happened.\n\nThe problem was that he never delivered.\n\nHe was so unimpressive that he was booted from WWE in 2016. He is making an appearance at WrestleMania 33. For his sake, it would be best if he kept quiet and didn't interact with the crowd.\n\n9 Kelly Kelly\n\nvia tumblr.com\n\nKelly Kelly was a fan favorite during her time in WWE. She made her debut as a popular model who was wrestling on ECW. From there, she rose to the top as a valuable part of the roster. Kelly became a popular figure who had her own dedicated fans. She had the right amount of talent to be a decent worker, but it was her good looks that gave her the extra push.\n\nAfter leaving WWE in 2012, Kelly kept wrestling. She is back on the roster with TNA, but she has not appeared on a television episode of Impact Wrestling since December of 2015.\n\n8 Alberto Del Rio\n\nvia wrestlingrumors.net\n\nIt is a sad truth that Alberto Del Rio has fallen from his former position in the industry. He was a very big part of WWE. He was not only the United States Champion, but also a World Champion. Alberto had a unique presence as a superstar that could do things no one else could do. He also had the microphone skills to back up his moves.\n\nHis tenure in WWE was marred with incidents that made it clear he was not going to be there much longer. His time in Lucha Underground was more memorable, but it was a step down from what he used to be.\n\n7 The Great Khali\n\nvia cagesideseats.com\n\nThe Great Khali is not really a superstar that anyone really misses. His presence was laughable at times. The thing about Khali is that he had a lot of potential. He was very big and very strong, but he never seemed to have any clue about how to use those traits to his advantage.\n\nKhali is now an actor and a former wrestler. He is part of the reality show Khali Kisses, which involves him doing a lot of kisses on people. It is a far cry from his WWE days.\n\n6 Kelly Kelly's Boyfriend\n\nvia youtube.com\n\nWrestlers who are lucky enough to find a wife have a much easier time in the wrestling industry. The same could not be said for Mike Knox. He was only a superstar for a very short time, and he was a part of one of the most bizarre moments in wrestling history when he got the Attitude Adjustment from Kane. Knox is not talked about much these days, but there was a time when people were curious about him.\n\nHe married the popular WWE superstar Kelly Kelly. The couple got married in 2014. It was a marriage that was not meant to last, as the couple divorced in 2016.\n\n5 Santino Marella\n\nvia ringsidenews.com\n\nSantino Marella will forever be a part of WWE. The WWE Hall of Fame is home to some great wrestlers and some very bad wrestlers. Santino is among those who have made an impression for one reason or another. His career with the company was not as successful as he had hoped, but he made a huge impact. He was the guy who was hilarious because he was so bad.\n\nSantino's last match was in 2014. He has done some backstage work, but the star has pretty much disappeared from WWE.\n\n4 Tyson Kidd\n\nvia heavy.com\n\nTyson Kidd was a true performer in WWE. He had a unique look, and he could really do it all. The man was skilled on the mic, in the ring, and he had a good personality. Everything came together for Tyson, but that would all change during an unfortunate injury. Tyson was a mid-carder who could have risen to a top level, but that was not meant to be.\n\nKidd is now recovering from his neck injury. He is still hoping to get into the ring again, but it is looking unlikely.\n\n3 Christian\n\nvia bodybuilding.com\n\nChristian is not a name that is being mentioned much these days. It is a shame, as he is one of the best performers of his time. Christian has made a career of being known for his impressive in-ring work and his ability to entertain fans. Christian was a popular superstar during his time in WWE and he did some good things for TNA.\n\nChristian has not been in the ring since December of 2015. He is trying to get back into the ring, but there is a possibility that his neck injury may have ended his career.\n\n2 Dolph Ziggler\n\nvia wrestlingnewssource.com\n\nDolph Ziggler had the chance to become a very big star in WWE. Unfortunately, things have not been going well for Ziggler. He was once a main eventer, but he has fallen to the bottom of the card. He is one of the many guys who will be pushed as the underdog who is going to have the moment of their life.\n\nZiggler has not been the focus of WWE. It is likely that he will be entering a new chapter of his career in the near future. The most likely place would be in Ring of Honor, but WWE has shown a lot of interest in Ziggler.\n\n1 Wade Barrett\n\nvia wrestlingrumors.net\n\nIt is going to be very hard for the casual fan to remember Wade Barrett. He had a short run in WWE, but he did his part as a mid-carder. Barrett is a former Intercontinental Champion. He did well in WWE as a member of The Nexus, but his star power never quite took off.\n\nBarrett has been out of WWE since 2014. He has had some ups and downs in the independent circuit, but his career has largely gone downhill. It is possible that he could get another chance with WWE. That would probably be the only way that fans would get to see him again.\n\nBarrett has been trying to make a name for himself in the business world. He launched a website last year. It is not likely that he will become a success, but it is nice to see him try to make something of his life.]" time="1.531"><properties><property name="score" value="0.145252773" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.14525277 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.14525277
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The brother-in-law of the Palestinian-American teenager who was filmed being brutally beaten by Israeli police at a West Bank checkpoint says the incident \u201chas put a wedge\u201d between the Palestinians and Israelis.\n\nYoussef Almogy said he has had more than 50 phone calls from news media outlets following the brutal arrest of 16-year-old Tariq Abu Khdeir, the Associated Press reported.\n\n\u201cWhen I saw it, I cried,\u201d Almogy said. \u201cI was so shocked, but after that, I started thinking about my brother, who was jailed for 11 years, and then released for nothing. And I said, \u2018If they can do that to him, then imagine what they can do to us.\u2019\u201d\n\n\u201cAnd this has put a wedge between Palestinians and Israelis,\u201d he added.\n\nAlmogy was referring to the arrest of his brother, Amer, who was jailed for 11 years after he and a group of Palestinians tried to rob a Tel Aviv bank in 1994. Almogy said Amer was never convicted of a crime and that he believes the former prisoner is being held because of his brother\u2019s connection to the teen, the AP said.\n\n"We're used to seeing this sort of thing," he said.\n\nAbu Khdeir, who was born in Florida but living with his family in East Jerusalem, was arrested Thursday after he was identified as being involved in a clash between]" time="0.463"><properties><property name="score" value="0.07317164" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07317164 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07317164
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nToday we\u2019re excited to announce that Bethesda Game Studios has joined Oculus as a developer for the Oculus Rift. The partnership will see the creation of two exclusive, made-for-VR games from Bethesda Game Studios; the first is currently being designed for virtual reality and the second is being built for traditional monitors.\n\n\n\n\u201cAt Oculus, we\u2019re dedicated to helping developers and partners to grow, and the support and dedication we\u2019ve received from Bethesda Game Studios has been outstanding,\u201d said Brendan Iribe, CEO of Oculus. \u201cJohn Carmack, founder of id Software and now CTO at Oculus, believes in our vision and has created a custom version of Doom 3 BFG Edition for Oculus. We look forward to continuing to work with Bethesda as we develop our first generation of virtual reality games and experiences.\u201d\n\n\n\n\u201cI have a lot of personal interest in making sure that the VR gaming space is successful because I really believe in the technology and its potential to change gaming,\u201d said Carmack. \u201cAs a developer, the Rift is something that I\u2019ve wanted to work with for a long time, but the existing technology wasn\u2019t quite there yet. I\u2019m happy to be able to help to make the Rift a success and contribute to the rebirth of VR gaming.\u201d\n\n\n\nAt Bethesda Game Studios, developers are working on a number of unannounced projects including new entries in major franchises. Those who have seen this year\u2019s E3 show floor, Gamescom or Quakecon presentations have seen teases of what the studio is up to and a few of the titles we have in development are also being designed for virtual reality. The two games announced today are entirely new IP and we can\u2019t wait to show them to you when they\u2019re ready for primetime.\n\n\n\nFor those of you unfamiliar with Bethesda Game Studios, the acclaimed developer is responsible for creating many of the industry\u2019s most popular games including the \u201cElder Scrolls\u201d series, the single-player add-on to the original \u201cDoom\u201d and the \u201cFallout\u201d series. In fact, \u201cFallout 3,\u201d \u201cFallout: New Vegas\u201d and \u201cThe Elder Scrolls V: Skyrim\u201d were each awarded game of the year at the 2008, 2010 and 2011 BAFTA awards, respectively.\n\n\n\n\u201cWe have made some long-term technology investments with VR in mind,\u201d said Todd Howard, Game Director and Executive Producer at Bethesda Game Studios. \u201cHardware is finally catching up to the visions developers have had for virtual reality. Now when you put on a VR headset, you\u2019re transported to new and amazing worlds.\u201d\n\n\n\nThis year, Bethesda Game Studios showcased \u201cDoom 3 BFG Edition\u201d for Oculus. \u201cDoom 3 BFG Edition\u201d is a complete overhaul of \u201cDoom 3\u201d that brings modern technology and a classic, storied franchise into the world of virtual reality. This is the first title designed for virtual reality.\n\n\n\n\u201cJohn Carmack\u2019s work in the early 90s helped usher in the era of modern 3D gaming, and his genius continues to inspire developers to innovate,\u201d said Brendan Iribe, CEO of Oculus. \u201cThe team at Bethesda Game Studios is made up of the most talented developers in the industry and we can\u2019t wait to bring their newest games, made for virtual reality, to life.\u201d\n\n\n\nOver the past 20 years, Bethesda Game Studios has earned its reputation as one of the industry\u2019s most respected and accomplished game development studios. Creators of the 2006 and 2008 Game of the Year, \u201cThe Elder Scrolls IV: Oblivion\u201d and 2010 Game of the Year, \u201cThe Elder Scrolls V: Skyrim,\u201d Bethesda Game Studios has earned a reputation for excellence and quality with each of its five releases.\n\n\n\nThis partnership is another step toward realizing the future of virtual reality. It\u2019s an exciting time to be a gamer with the release of these groundbreaking VR titles, the arrival of next generation consoles and the continued evolution of the PC.\n\n\n\nStay tuned for more news on Bethesda Game Studios\u2019 titles for Oculus.\n\n\n\n\u2013 The Oculus Team]" time="0.324"><properties><property name="score" value="0.0019176067" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00191761 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00191761
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nHi~ B een a long time no see. Thank you for the continued support on the blog. So, how have you all been doing?\n\nToday, I have a special post. I know most of you do not know but it is the 'World Animal Day'. The day is celebrated worldwide on October 4 to create awareness of animal rights and welfare. The day is a very special one for me because I am a vegetarian, animal lover and a dog-person.\n\n\n\n\n\nSo for the last one year, I have been trying to spread the awareness among the people. I have been trying to encourage people to stop using animals as fur coats, cosmetics and for food. I want people to know the feelings of these animals, the pains they suffer and what they go through while they are alive. Also, the environmental damage they cause to the planet. It is very important to spread this message because animals are treated as if they are some sort of toys that we can play with.\n\n\n\n\n\nToday, I would like to share with you some tips on how we can help the animals and make the planet a better place to live. I also have a small personal pledge to make. Also, if you have not signed the pledge yet, you can also make your own pledge to protect the animals and the planet.\n\n\n\n\n\n\n\n\n\nTips and pledges to help the animals\n\n(made by my friend!)\n\nOne way we can make a change is by making an effort to not use cosmetics that are tested on animals. We can choose to use all cruelty free products and make a conscious effort not to use anything that has been tested on animals.\n\nWays to reduce our carbon footprints and help protect the environment:\n\nAvoid eating meat, or even better, go vegetarian (dairy, eggs are not vegan but I still encourage you to stop using dairy products as well)\n\nUse eco-friendly products - Not just cosmetics but also in our everyday lives.\n\nGo cruelty free - Choose cruelty free products and wear clothes that have not been made out of leather, fur or wool.\n\nStop buying those animals that we do not need. Also, choose to buy second hand or recycled clothes. Avoid buying pets if you cannot provide the proper care for them.\n\nAdopt, don't buy! You can adopt a dog or cat from an animal shelter. Do not buy animals from pet stores or breeders. They are sold to you as "breed-free" animals but most of them have been bred in horrible conditions. Also, make sure you know the sex of the animal you are getting, because they usually are sold as 'un-neutered' or 'un-spayed' animals.\n\nMake a conscious effort to not use plastic bags. Use reusable bags or better still, try to avoid using bags at all.\n\nTry to use products that do not harm the environment and are biodegradable.\n\nWays to help the animals:\n\nSign the pledge - To show that you support the cause to protect the animals.\n\nShare the post - Let others know of the cruelty that the animals go through. Let them know how they can help the animals too.\n\nJoin or start a protest or campaign to help the animals.\n\nThe small pledge I am making is to help the animals. Every month, I will be donating some money to an animal shelter in my town to help feed the dogs and cats there.\n\nThese are just some of the ways we can help the animals and the planet. We can all make a change, and make this planet a better place to live.\n\n\n\n\n\nIf you want to know how to become a vegan, and which cosmetics are tested on animals, you can read this post: How to be a vegan?\n\nRemember, we are what we eat, so be what you want to be. Be a good person, who loves animals and helps to save the planet.\n\nWith lots of love,\n\nPriya]" time="0.315"><properties><property name="score" value="0.47861063" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Top Customer Reviews\n\nWhere reviews refer to foods or cosmetic products, results may vary from person to person. Customer reviews are independent and do not represent the views of The Hut Group.\n\nUnique, gritty, and wonderful The Good: The worlds are some of the best I've seen in a while, and how you explore the city and interact with its citizens gives a great sense of authenticity and intrigue. As a huge comic fan, the references are abound. The story and narrative is one of the best I've ever experienced. The Bad: The game is very linear and the combat while satisfying can get old at times. Overall: This is one of the best games I've ever played, period. Everything about it is gritty, dark, atmospheric, and enticing. While you have a very linear path to follow in the main story, the side quests and interactions you can have with the citizens is one of the best I've seen. You are truly the villain in this game, so if you want to be good and helpful to everyone, this is not for you. But for the fans of dark, gritty stories, this is one of the best. The story and narrative are top notch. The villains are some of the most compelling I've ever seen in a video game, with even the main villains being so much more compelling than the good guys. I loved this game from start to finish, and can't wait to see where the series goes from here. The ending while great is somewhat confusing, so if you aren't]" time="0.404"><properties><property name="score" value="0.02088329" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[And now, ladies and gentlemen, I give you the breathless high-speed ranting I did when I saw the (potentially) wackadoo conclusion to this storyline.\n\nOh, my God, you guys, this episode has a freaking atomic bomb on the side of it.\n\nOkay, cool. It\u2019s the mid-season finale. I know there\u2019s going to be some serious plotlines.\n\nAnd seriously, what was up with the weird science in this episode?\n\nNo. No, I did not just watch an episode with the headline: \u201cOuch, My Butt!\u201d\n\nThat plotline was weird as hell.\n\nBut I can understand why they did it. He\u2019s trying to be a \u201csophisticated ladies man\u201d and not the boy they\u2019ve been dealing with all these years.\n\nOh, now this is hilarious. But it\u2019s also dangerous, if you\u2019ve watched any superhero movie ever.\n\nIn the brief moment that I was allowed to breathe, I actually enjoyed this part.\n\nNot only is this scientifically improbable, but also\u2026 how does a security camera shoot a laser?\n\nI know this is only in fiction, but I do believe that they\u2019re committing suicide.\n\nThis is also part of the reason why I wanted to talk about this episode. I know it\u2019s not a good look. It\u2019s not exactly smart of him to do this.\n\nI don\u2019t even know what to say here.\n\nWHY?\n\nHe\u2019s not afraid of bugs, but he\u2019s scared of that snake?\n\nI mean, yeah, I get that he\u2019s doing it for a different reason, but\u2026\n\nIf it weren\u2019t for that, then I would not have laughed so hard at this.\n\nOkay, look, I was done with this season for a while. I thought that it was becoming a boring clich\xe9d plot that they were sticking to, so I was ready to say goodbye to it. But then I watched this, and I just felt like I was watching a new show. There was so much going on, and they were throwing so much at us at once, and it was just such a good use of time. I\u2019m really happy that they had this show, because it was seriously pretty funny and it was also action-packed. There was a lot going on, but it was very clear, and it was fun to watch. I just loved how much was going on. I loved it, and I really did enjoy it. It was a bit much, and they took a lot of crazy chances, but it was just so fun to watch. That was some crazy stuff, and it was nice to see something so good after so much of the regular garbage we were getting. Overall, I loved it.]" time="0.318"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[(Adapted from the 2014 Urban Tree Canopy Conference)\n\nPotholes are problematic for all of us, and for our city\u2019s trees they represent a real danger. Roots can become entangled in the small cracks between the asphalt and the cement to create the impression that the tree is growing out of the road! And when the roots do become entwined, the pressure can be so great that the roots are destroyed. We all know the danger this creates for the trees.\n\nThe solution to this problem is obvious: pave over the whole road surface. Not so fast! In the City of Chicago, for example, there is a practice that preserves the utility of the tree\u2019s roots and of the road surface itself. The practice is called \u201cmilling\u201d. Milling involves cutting the asphalt out in a shape that will not disturb the roots and adding back in a new surface. While the tree is protected, the roots are not disturbed and the road surface is left intact. When a tree is scheduled for removal, this is often the method of choice. Milling also involves improving the root zone around the tree. The roots of many trees can\u2019t penetrate the compacted soil that is found beneath pavement, so it is necessary to mill the area to promote root growth.\n\nMilling is less expensive than paving over a road surface and can also be less expensive than removal of a tree. Milling should be done whenever possible and certainly before a tree is scheduled for removal. There is no need to sacrifice a mature, healthy tree.\n\nAdvertisements]" time="0.309"><properties><property name="score" value="0.027491624" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02749162 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02749162
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[How do i search for files with a specific suffix using Unix?\n\nOn Unix, to search for files that ends with a particular file extension, use the following command:\n\nfind . -name '*.html'\n\nOR use grep command to list all files in a directory and subdirectories that have the suffix:\n\nfind . -type f | xargs grep -l <suffix>\n\nSample outputs:\n\n./Ajax/contact-us/index.html ./test/index.html\n\nThe above commands are equivalent to the grep command on Linux/MacOSX or the find command on Linux/MacOSX:\n\n$ find . -name "*.html" ./test/index.html ./Ajax/contact-us/index.html $ grep -l -Ri -f -E ".*\\.html" ./ test/index.html Ajax/contact-us/index.html\n\nFind out all files with a specific filename (using shell pattern match):\n\nfind . -name '*.html'\n\nOR use the egrep command to list all files in a directory and subdirectories that have the suffix:\n\nfind . -type f | xargs egrep -l <suffix>\n\nSample outputs:\n\n./Ajax/contact-us/index.html ./test/index.html\n\nOR\n\n$ find . -name "*.html" ./test/index.html ./Ajax/contact-us/index.html $ egrep -i ".*\\.html" . Ajax/contact-us/index.html test/index.html\n\nFind files in a directory and subdirectories:\n\nfind . -name "*.html"\n\nOR\n\nfind . -type f | xargs grep -l <suffix>\n\nSample outputs:\n\n./Ajax/contact-us/index.html ./test/index.html\n\nOR\n\n$ find . -name "*.html" ./test/index.html ./Ajax/contact-us/index.html $ egrep -i ".*\\.html" . Ajax/contact-us/index.html test/index.html\n\nFind files in a directory and all]" time="0.330"><properties><property name="score" value="0.002334355" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Russia has expanded its ban on U.S. pork to include all American meat imports as the diplomatic row over alleged election meddling and the situation in Syria rumbles on.\n\nLast week, the Russian government added five new countries to the blacklist: South Korea, Montenegro, Iceland, Liechtenstein and Ukraine. While the list included major agricultural producers such as Brazil and Canada, U.S. meat producers were noticeably absent. However, on Wednesday, the government added the U.S. to the list of banned meat importers.\n\nThe ban was announced by the state consumer watchdog Rospotrebnadzor. A government official told Russian media that American meat imports were now being kept out of Russia on a \u201ctemporary basis\u201d.\n\nRussia is the fourth largest importer of U.S. meat, buying $51 million worth of poultry and $22 million of pork in 2016. According to the National Pork Producers Council, the U.S. shipped 27,600 metric tons of pork to Russia in 2016, which made up 0.3 percent of total U.S. pork exports.\n\nRead more: Polls Say Few Americans Think Trump is Putin's Puppet\n\nThe ban comes at a particularly difficult time for the U.S. meat industry, which is still struggling to recover from a disastrous salmonella outbreak that began in 2015. China, Vietnam and Mexico have all banned U.S. pork imports, while the EU and South Korea are still testing shipments.\n\nThe bans come as U.S. meat exporters have had difficulty convincing importers to trust American meat following the 2015 crisis. The outbreak, which resulted in more than 60 percent of pork being recalled, was linked to at least 184 illnesses in 20 states. While U.S. authorities traced the outbreak back to a farm in Missouri, they were unable to identify the exact source of contamination.\n\n\u201cThis has been a major setback for us and it will take a while for the industry to recover,\u201d said National Pork Producers Council spokesman Dave Warner.\n\nIt's not clear when Russia will lift its ban on U.S. meat, but Russia's state consumer protection watchdog has said it would allow Ukrainian meat imports.]" time="0.324"><properties><property name="score" value="0.0025902723" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00259027 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00259027
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[(NC)\u2014Despite the odds, there are some consumers who decide to head to the stores this weekend to start Christmas shopping. For some, the reason is because they still have some of their shopping list to complete. Others, however, have an entirely different reason.\n\nAccording to Statistics Canada, the average Canadian adult will spend $473.12 on gifts this holiday season. That means the average consumer will spend almost $35 more this year than last year.\n\n\u201cA lot of consumers have gone overboard,\u201d says Ted Michalos, founder of CMG Financial. \u201cIt\u2019s not necessarily the spending that\u2019s the problem, it\u2019s what they\u2019re spending the money on.\u201d\n\nThat\u2019s because many shoppers are buying gifts for themselves. That doesn\u2019t necessarily mean they\u2019re spending on the latest fashions, but rather toys and electronics. And the majority of these gifts, at 41.8 per cent, are going to be purchased online.\n\nHowever, the reason why so many people are spending online is because they\u2019re trying to avoid the crowds and waiting in lines.\n\n\u201cSome consumers just get too stressed and they go online to get their stuff,\u201d says Michalos. \u201cAnd if they do that, they\u2019re likely going to be paying more for the gifts.\u201d\n\nThat\u2019s because while there are fewer people at the store, they\u2019re paying more per person. For example, if someone is paying $50 for a gift in the store, they\u2019re likely to pay more than $50 online.\n\n\u201cThis is really the time where you\u2019re going to have to do your best to have everything done by the 15th,\u201d says Michalos. \u201cAnd it\u2019s definitely a good idea to sit down with your spouse or significant other and look at your budget. And when you have a child, the best thing to do is to write down what you\u2019re going to spend. That\u2019s a real good thing to do, because if you don\u2019t, you\u2019ll overspend.\u201d\n\nAnd that could come with consequences, because if you\u2019re overspending, you could be limiting your ability to spend on your children or other family members in the future.\n\n\u201cYou can go overboard and give away everything you have to your kids and that could be a problem,\u201d says Michalos. \u201cThis could be an opportunity to teach your kids about moderation, and also the difference between \u2018I want\u2019 and \u2018I need.\u2019\u201d\n\nBecause with Christmas, most people are shopping with the mindset of \u2018I want,\u2019 not \u2018I need.\u2019 And that can be a problem, because it will prevent you from saving or investing.\n\n\u201cIf you\u2019re going to be shopping on a credit card, you\u2019re going to be in big trouble,\u201d says Michalos. \u201cIf you\u2019re not able to pay off that debt by the end of January, you\u2019re going to be in big trouble.\u201d\n\nWant to know more about debt? Try these articles:\n\nNew Christmas ad showcases true meaning of the holidays\n\nTake advantage of these holiday deals\n\nHow to get your kids to be thankful for what they have\n\nWhat do you think? Join the conversation in the comments below or contact us using the \u201cHave Your Say\u201d form on this page.]" time="0.364"><properties><property name="score" value="0.07487018" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07487018 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07487018
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Developing in a Virtual Machine on your computer or laptop\n\nHello , Here we are going to learn how to create virtual machine on your computer for testing purpose. Before we start , it is better to know what is virtual machine. A virtual machine is a simulated hardware that allows you to run other operating systems (or other versions of the same OS) at the same time as your current OS, inside a window on your current OS. It can also be thought of as a computer inside a computer. With a virtual machine, you can: Run another operating system (or another version of the same operating system) at the same time as your current operating system. Try out a new operating system without having to install it on your hard disk. Run applications for one operating system on another, without having to reboot your computer.\n\nStep 1: Create a New Virtual Machine\n\nVirtualBox provides a wizard that will assist you in creating a virtual machine. Launch the program and select \u201cNew\u201d.\n\nStep 2: Create a Virtual Machine\n\nThe first window you see is the New Virtual Machine Wizard. Select \u201cCreate a virtual machine\u201d.\n\nStep 3: Create a Virtual Machine\n\nIn the next window, enter the name for your virtual machine. This name will appear in the main VirtualBox window next to the icon for the virtual machine.\n\nStep 4: Create a Virtual Machine\n\nThe next window is where you select the operating system you want to install.\n\nStep 5: Create a Virtual Machine\n\nIn the next window, select the amount of memory you want to allocate to your virtual machine. The more memory you have, the more applications you can run simultaneously. However, keep in mind that the more memory you allocate, the slower your computer will be.\n\nStep 6: Create a Virtual Machine\n\nSelect \u201cCreate a virtual hard disk\ufffd]" time="0.335"><properties><property name="score" value="0.01700924" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The internet is a funny place, where people can get away with saying and doing the weirdest stuff that would otherwise be totally unacceptable.\n\nBut it turns out not even the internet is a free pass to sexually harass people.\n\nThat's what one woman learned when she was sent a totally inappropriate, NSFW photo from a stranger, that happened to be someone she knew in real life.\n\nTwitter user @kendtee, who describes herself as "an arm candy", tweeted about her encounter with the man she knew.\n\nAccording to @kendtee, the incident occurred after she agreed to take a picture with a guy. She then deleted the picture from her camera roll when it was over, and the man asked if she had. She said yes, and then he said this:\n\n"It's a shame we can't see the photo anymore because it was pretty good"\n\nShe didn't know how to respond. He then tweeted her back, asking her to "leave [the photo] up for a little while". She declined.\n\nApparently, he then texted her back, asking her to send him a copy of the picture.\n\nShocked by this behaviour, she shared the exchange on Twitter, and said the worst part was how "unbothered" he seemed about it.\n\nEventually she shared a screenshot of the exchange, and people were not impressed.\n\n"Oh wow. 'I'd do ya if I could' and then the photo request. You should probably just block him and be done with it. 'Doing ya' or not," one person said.\n\nAnother person had an idea on how to deal with it, tweeting, "You know what? Be a bigger person, send it to him. For posterity."\n\nMany others were in complete agreement with this sentiment.\n\n"I don't know this man and I probably never will. But I 100% understand why he's going to be blocked. A man who says that is definitely not a good person. All women should know their boundaries with men and this seems to me to be clear cut," one person said.\n\nIn the end, @kendtee went back to him and asked him to explain why he'd sent her that photo.\n\nAccording to @kendtee, he sent her this message in response:\n\n"How do you think I know that you're gonna see this tweet and block me or delete it.\n\n"I'm not trying to be a creep you just said that you'd do me so I figured we had a shot lol\n\n"I like your style and want to get to know you better\n\n"If you send the picture I promise not to be creepy and stop bothering you\n\n"I'm being serious here and I don't think I deserve the reaction I got\n\n"All I wanted to do was take a picture with a nice girl and see if she'd let me\n\n"I don't want to be a bad person or make you feel uncomfortable.\n\n"If you like I'll just go away\n\n"You're gorgeous and I'm sorry I don't deserve to meet you but I thought I'd try my luck\n\n"I won't message you again if you don't want me to\n\n"I'll delete the tweet and block you\n\n"I just wanted to try\n\n"Please"\n\nThe rest of Twitter wasn't impressed, calling him out for still not getting it, and for trying to shift the blame.\n\n"Like you have to explain what 'likes your style' means, like you're trying to shift the blame. But it's not ok. It's not ok for you to message someone for a photo. It's not ok for you to say 'I'd do you' and it's not ok for you to try and justify your actions," one person said.\n\nAnother pointed out that he was trying to pressure her into sending him the photo, and wasn't taking responsibility for his actions.\n\n"He's a creep, and still wants to force you to send him a picture of your body. He'll delete the tweet if you do, otherwise you can block him. This is on him, not you. You have no responsibility to 'meet' him," another person said.\n\n"Ok let's stop there with the 'I would've taken a photo with you anyways' thing. That's not what this is about. This is about someone sending unsolicited nudes," another person pointed out.\n\nIn response, @kendtee wrote that she wasn't bothered, because at the end of the day she was a "pretty woman who didn't need to be respected".\n\n"I didn't get mad or freak out or feel the need to drag his name through the mud. I just calmly informed him that I have a man in my life and that I'm flattered but I don't share photos like that and I'm taken. He didn't like it so he blocked me and I'm okay with that," she wrote.\n\nALSO ON HUFFPOST AUSTRALIA]" time="0.954"><properties><property name="score" value="0.10062507" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Perhaps one of the most beautiful areas of Southern California is the Pacific Palisades, a neighborhood filled with high rises, luxury estates, and tons of culture. From the obvious to the under the radar, Pacific Palisades has some of the most fascinating museums, gardens, and activities you can visit. When you need to get out of the house and explore a new part of Los Angeles, the Pacific Palisades is a fantastic choice.\n\nThe Getty Villa\n\nThe Getty Villa is a sight to behold, and is a must see when you are in the Pacific Palisades. You are welcome to explore the museum for free on the first Thursday of every month. They offer a free trolley that will take you to the Getty Villa, so you don\u2019t have to worry about navigating through the Pacific Palisades on a crowded day. This is the perfect time to visit the Pacific Palisades.\n\nThere are two events going on at the Getty Villa on Thursdays: Story Time and Pacific Voices. Story time will give you a better understanding of ancient Greek and Roman culture. It is a good idea to purchase your tickets in advance, so you can get a discount. The Pacific Voices event is a singing performance, and a great way to enjoy your time at the Getty Villa.\n\nSanta Monica Mountains National Recreation Area\n\nThe Santa Monica Mountains are a beautiful way to spend a day in the Pacific Palisades. The National Recreation Area has a fantastic number of trails you can explore, and is a great way to get out of the house and spend time with your family. Take the trail to Leo Carillo State Beach, or go for a hike along Rustic Canyon. Whichever trail you take, you are sure to enjoy your time in the Pacific Palisades.\n\nSanta Monica Baykeeper\n\nThe Santa Monica Baykeeper is a fantastic organization that works hard to clean up the Santa Monica Bay. This is a great way to spend time in the Pacific Palisades and make a real difference. Check their website for upcoming volunteer opportunities. You will learn more about the Santa Monica Bay, and get a chance to spend time with some interesting people.\n\nPacific Palisades Center for the Arts\n\nThe Pacific Palisades Center for the Arts is an excellent way to spend an afternoon. This isn\u2019t a museum, so you don\u2019t need to book in advance. It is free to walk around the grounds, and to watch a performance. They have everything from jazz concerts to visual arts. If you want to learn more about the Pacific Palisades, then this is a great place to start.\n\nPacific Palisades Farmers Market\n\nThe Pacific Palisades Farmers Market is an excellent way to spend your Saturday in the Pacific Palisades. From fruits and vegetables, to homemade items and baked goods, there are plenty of delicious items to choose from. This is a great place to bring the kids, as they have tons of activities.\n\nPacific Palisades Art Walk\n\nThe Pacific Palisades Art Walk is a fantastic opportunity to view some of the beautiful artwork created by locals. It is a fun evening filled with laughter and good food. You are welcome to bring your own picnic basket and enjoy it in the beautiful Pacific Palisades.]" time="0.403"><properties><property name="score" value="0.81202006" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Tom Shanks (writer)\n\nTom Shanks (born 1961) is a Scottish writer, journalist, and musician. He is the author of eight novels, including "The Hidden", the "Vampyrrhic Times" trilogy, and "Eve", an "Eve" (comics) spin-off novel.\n\nShanks has been living in France since 1983 and is married to the French writer Marie H\xe9l\xe8ne Poitras.\n\nShanks was born in Edinburgh, Scotland in 1961.\n\nShanks has been writing since the mid-1990s and has published several novels.\n\nShanks has also been writing for the British comic book magazine "2000 AD". His first script for them was the short story "Trevor's Tale", drawn by Simon Harrison, in "2000 AD" #1704, published in March 2008.\n\nThe comic book "Eve" was written by Shanks. It was released by Black House Comics in 2011 and the second volume was published in 2012. In 2012, IDW Publishing published a comic book prequel to "Eve", "Eve: The Awakening". The book was written by Shanks and Marie H\xe9l\xe8ne Poitras and illustrated by Enrica Angiolini.\n\nShanks has also written the script for "Apocalypse Cow", which was originally published in French and German as "La Vache Apocalypse". It was adapted as a comic book by Tony Lee.\n\nIn March 2010, the novel "Vampyrrhic Times" was published by Gollancz in the UK and by Roc in the US. It was illustrated by Tony Harwood. The second volume of the trilogy, "The Wisdom of Dead Men", was published in the UK in 2011 and the US in 2012. The third volume, "The Trade of Queens", was published in the UK in 2013 and in the US in 2014.\n\n\n\n\n\n\n\nShanks and Poitras run the Black House Comics publishing house.\n\nShanks is a member of the band The Bassholes, along with co-writer of Eve, Marie H\xe9l\xe8ne Poitras. The band is composed of Shanks and Poitras on vocals and bass, Poitras' husband, French artist St\xe9phane Paitreau, on guitar, and drummer "Chino" Gonzales. They released their first album, "No More Mr Nice Guy", on May 1, 2010, on Stuck on a Name Records. The album includes covers of classic rock songs, such as "Jailhouse Rock" and "Born to be Wild". In 2013, the band released a second album, "Sex Lies & Basslines".\n]" time="0.380"><properties><property name="score" value="0.04802345" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rick Lake\n\nRichard G. Lake II (born April 7, 1979) is an American mixed martial artist who most recently competed in the Welterweight division of the Ultimate Fighting Championship. A professional competitor since 2004, he has also competed for the Quad Cities Silverbacks of the IFL, and was a competitor on Spike TV's "".\n\nBorn and raised in the Quad Cities area, Lake attended East Moline High School.\n\nAfter graduating from high school, Lake worked for two years as a full-time welder, before deciding to pursue a career in mixed martial arts.\n\nLake made his professional mixed martial arts debut on October 30, 2004 for the Quad Cities Silverbacks of the International Fight League. He won his first three fights for the promotion, before suffering his first loss to Ian Loveland on April 8, 2005.\n\nAfter picking up three wins in the IFL, Lake was signed by the UFC. He was expected to make his debut at UFC Fight Night 7 against Jason Gilliam. However, Gilliam was forced from the card with an injury, and was replaced by Jorge Rivera. Lake lost to Rivera via first-round KO on August 23, 2007.\n\nFor his second fight in the promotion, Lake dropped down to Lightweight and faced Kyle Bradley at UFC Fight Night 11 on November 17, 2007. He won the fight via unanimous decision (30-27, 30-27, 29-28).\n\nIn his third fight for the promotion, Lake dropped to Featherweight to take on Mike Brown at UFC Fight Night 13 on June 16, 2008. He lost the fight via unanimous decision (29-28, 29-28, 29-28).\n\nFor his fourth fight in the promotion, Lake dropped to Bantamweight and faced Brad Pickett at UFC 95 on February 7, 2009. He lost the fight via TKO in the first round.\n\nFor his fifth fight in the promotion, Lake faced Tommy Hayden at UFC 100 on July 11, 2009. He won the fight via submission in the first round, earning "Submission of the Night" honors.\n\nFor his sixth fight in the promotion, Lake faced George Roop on March 21, 2010 at . He won the fight via unanimous decision.\n\nFor his seventh fight in the promotion, Lake fought Roland Delorme on June 19, 2010 at . He lost the fight via submission in the first round.\n\nFor his eighth fight in the promotion, Lake faced John Gunderson on November 20, 2010 at UFC 122. He won the fight via split decision.\n\nFor his ninth fight in the promotion, Lake fought Jason Reinhardt on February 5, 2011 at UFC 126. He won the fight via TKO in the first round.\n\nFor his tenth fight in the promotion, Lake faced newcomer Darren Uyenoyama on June 11, 2011 at . He won the fight via unanimous decision (30-27, 30-27, 30-27).\n\nFor his eleventh fight in the promotion, Lake faced former WEC Featherweight Champion Mike Brown on October 29, 2011 at UFC on Versus 6. He lost the fight via unanimous decision (29-28, 29-28, 29-28).\n\nFor his twelfth fight in the promotion, Lake faced Nam Phan on May 15, 2012 at UFC on FX 4. He lost the fight via unanimous decision.\n\nFor his thirteenth fight in the promotion, Lake faced Sam Sicilia on July 11, 2012 at UFC 149. He won the fight via unanimous decision.\n\nFor his fourteenth fight in the promotion, Lake faced Ivan Menjivar on December 15, 2012 at UFC 155. He won the fight via split decision.\n\nFor his fifteenth fight in the promotion, Lake faced Jeremy Larsen on June 15, 2013 at UFC 161. He won the fight via TKO in the second round.\n\nFor his sixteenth fight in the promotion, Lake faced promotional newcomer Justin Salas on November 16, 2013 at UFC 167. He lost the fight via split decision.\n\nFor his seventeenth fight in the promotion, Lake faced fellow newcomer Max Holloway on February 15, 2014 at UFC 169. He lost the fight via TKO in the first round.\n\nAfter his release from the UFC, Lake dropped down to Bantamweight and made his debut on April 11, 2015 at IFC: International Fighting Championship 2 in Des Moines, Iowa against Rafael "Morcego" da Silva. He lost the fight via knockout in the first round.\n\nLake faced Gabriel Checco on May 28, 2015 at CXF 5. He lost the fight via split decision.\n\nLake faced Daniel Weichel on August 14, 2015 at Superior Challenge 12. He lost the fight via submission in the first round.\n\nIn his fourth fight since returning from the UFC, Lake faced Ryan Quinn on October 23, 2015 at CXF 8. He won the fight via knockout in the first round.\n\nLake faced Jim Alers on January 8, 2016 at CXF 10. He won the fight via TKO in the second round.\n\nLake faced Martin Stapleton on February 19, 2016 at MFW: A Night of Champions. He lost the fight via split decision.\n\nLake next faced Dylan Logan on September 2, 2016 at Cage Warriors 82. He won the fight via TKO in the second round.\n\nOn February 28, 2017, it was announced that Lake had signed with the UFC and was expected to face Alessio Di Chirico on March 18, 2017 at UFC Fight Night 107. However, on March 7, Di Chirico pulled out from the event, citing injury, and was replaced by promotional newcomer Marcin Prachnio. Lake won the fight via TKO in the second round.\n\nLake faced Gregor Gillespie on June 25, 2017 at UFC Fight Night 112. He lost the fight via split decision.\n\nLake faced Jarred Brooks on December 9, 2017 at UFC Fight Night 123. He lost the fight via submission in the first round.\n\nLake faced Drakkar Klose on February 24, 2018 at UFC on Fox 28. He lost the fight via TKO in the second round.\n\nLake faced Andre Fili on August 25, 2018 at UFC Fight Night 135. He lost the fight via TKO in the first round.\n\nLake faced Desmond Green on February 17, 2019 at UFC on ESPN 2. He lost the fight via technical knock out.\n\nIn July 2007, Lake was diagnosed with Crohn's disease, an inflammatory bowel disease that causes ulcers in the digestive tract. He began experiencing symptoms shortly after moving to California to train full-time. His Crohn's was brought under control through medication and diet, and it is currently in remission.\n\n\n\n]" time="0.819"><properties><property name="score" value="0.16801548800000002" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[If you\u2019re working on a SharePoint app, you\u2019ll eventually need to get hold of a SharePoint context. At the time of this writing, there are two options: SharePointContext and SPUtility. Both work fine, and I think it\u2019s really up to your personal preference and comfort level to choose either. But for my purposes, I\u2019m a fan of using SharePointContext because it will use the most current context available, which is what I like to do.\n\nLet\u2019s take a quick look at the two SharePoint context providers that we have at our disposal: SharePointContext and SPUtility. We\u2019ll use these in conjunction with the new SharePoint REST API to get a SharePoint context.\n\nSharePointContext\n\nThe SharePointContext class represents a SharePoint context. The context is the central part of the SharePoint client object model, and it\u2019s available from any client, including SharePoint-hosted, remote, or SharePoint-hosted-remote applications.\n\nTo create a SharePointContext object, you call the SharePointContext.GetContextAsync() method and pass in a SharePointContextOptions object. The SharePointContextOptions object provides the user information and authentication settings. We\u2019ll dive into the details in the \u201cAuthorization\u201d section of this article.\n\nOnce you have your context, you can then call methods on it. The context has a number of methods on it to retrieve different information.\n\nLet\u2019s take a quick look at the available methods:\n\nGetContextAsync() - The method that is used to create the context.\n\n\n\n- The method that is used to create the context. SharePointContextPermission - The property that contains the permission token used to retrieve the current user.\n\n\n\n- The property that contains the permission token used to retrieve the current user. SharePointPermissions - The property that contains the current permission level of the user.\n\n\n\n- The property that contains the current permission level of the user. ListPermissions - The property that contains the permission level for the user to access lists.\n\n\n\n- The property that contains the permission level for the user to access lists. SPHostUrl - The property that contains the URL of the current host application.\n\n\n\n- The property that contains the URL of the current host application. Site - The property that contains the current site of the user.\n\n\n\n- The property that contains the current site of the user. UserPrincipalName - The property that contains the username of the current user.\n\n\n\n- The property that contains the username of the current user. Web - The property that contains the current web of the user.\n\n\n\nSPUtility\n\nThe SPUtility class provides static methods to retrieve a SharePoint context and return it. To get the context, you call the SPUtility.GetSharePointContext() method.\n\nThe methods you have available on the SPUtility.SharePointContext object are:\n\nClientContext\n\n\n\nWeb\n\n\n\nGetClientContext()\n\n\n\nGetWeb()\n\n\n\nSharePointContext Permission\n\nBefore we dive into the SharePoint context, let\u2019s talk about permission. The SharePoint context is going to be pretty useless without a permission token. We\u2019re going to talk about this permission token a lot in this article, so let\u2019s just take a quick look at how it\u2019s generated.\n\nWe\u2019ll need to use the SharePoint permissions provider to generate the token. To do so, you\u2019ll need to call the SharePointPermissionManager.GetPermissionsAsync() method. You\u2019ll need to pass in an instance of the site where you want the permissions for.\n\nIn this example, we\u2019re going to call GetPermissionsAsync() and get the current user\u2019s permissions.\n\nGetPermissionsAsync() returns a SharePointPermissions object, which you can use to set your permissions on lists, folders, and documents. The SharePoint permissions are applied in a single pass. This means that you can\u2019t apply different permissions to different entities. For example, if you want to apply permissions on the web, the site, and the lists and folders, you\u2019ll need to pass in the permission on the web, then on the site, then on the lists and folders. You can, however, pass in different permissions to different lists and folders.\n\nOne other thing to note about SharePoint permissions is that they only grant access to the web, not to the list or to the folder itself.\n\nFor example, if a user doesn\u2019t have the Edit permission to a list, he will still be able to view it. But if the user has the Edit permission to the list, he will be able to edit it.\n\nIf you want to deny access to the whole list, you can set the permissions for the list and all its subfolders to Deny.\n\nIn order to create the context, we\u2019ll use the context, the SharePoint permissions provider, and a helper class, which we\u2019ll talk about later in the article. The full example is shown in Listing 1.\n\nThe context object will now be passed to the constructor of a class called FileRootsProvider. The FileRootsProvider class is part of a helper class that I wrote and will be available to you in this article.\n\nThe provider will be created with the context and then called to generate the access token. Once the access token is generated, it will be returned to us, and we can start to retrieve information about the site and its lists and folders.\n\nAccess Token\n\nWhen you call the SharePoint permissions provider, you\u2019ll receive a token that represents the permissions for the current user. The token is returned as a SharePointPermissions object, which is what we\u2019ll use to apply the permissions.\n\nTo create a SharePointPermissions object, you need to pass in the site URL where the permissions should apply. For our example, we\u2019ll pass in the site URL to the SharePointPermissions constructor.\n\nAfter you\u2019ve created the permissions, you can apply them to the lists and folders. You can do this by passing in an instance of a list or folder to the SharePointPermissions constructor. If you want to apply permissions to all lists and folders, you can simply pass in an empty list or folder.\n\nNow that we\u2019ve created the permissions, we can use the FileRootsProvider class to generate the access token. The access token is returned as a SharePointContextPermissions object. The SharePointContextPermissions object contains the permission token and other details that we\u2019ll use to get information from the SharePoint site.\n\nAs you can see, the code to get the access token is pretty straightforward. The example is shown in Listing 2.\n\nList\n\nGetting the access token isn\u2019t all you need to do. You also need to be able to get a list and get a list item. To do this, you\u2019ll need to call the SharePointContext.GetListAsync() method. The method is easy to use and returns a list object.\n\nIf you\u2019re looking for a specific list, you can pass in the list GUID or the URL of the list. Listing 3 shows an example of both the URL and GUID to get the lists from.\n\nItems\n\nThe code to get an item from a list is just as easy as getting the list. You can pass in the list item GUID to the GetListItemAsync() method. Listing 4 shows an example of how to get the list item with the GUID.\n\nSummary\n\nThis article was a quick look at how to get a SharePoint context. The examples used a helper class that I created to make it a little easier to get access to lists and items from SharePoint.]" time="0.710"><properties><property name="score" value="0.14727592" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A few months back, I wrote an article about the journey from yearning to prayer. Since I have been praying on and off for many years, I was finally blessed with the chance to journey from yearning to prayer. It took a few weeks but it did happen. In the past, my experience of praying was somewhat a miserable one. It was not that I was not able to pray but the truth was I never really enjoyed the praying process. As a matter of fact, I used to hate praying. When I was younger, I was more interested in action than in words. I just want to know what I have to do and get it done. Thus, I never really understood praying. I just felt I was doing nothing but looking at the ceiling. It was only after I found my faith in Jesus that I have understood praying.\n\nMy first experience of prayer was on the cross. I experienced the most painful prayer in my life when I saw Jesus on the cross. He was in pain and so am I. He was looking at the ceiling of the cross and so did I. In the midst of my pain, I opened my eyes and saw Him. I realized that my prayers were not on my behalf but for Him. I looked at Him and realized that He was the only one who can pray for me. I looked at Him and asked him to pray for me. I have never felt anything like it. I have never felt more connected to my God than that moment. I have never felt more at peace than that moment. I realized that praying is actually for Jesus. I realized that Jesus came to this world for a purpose. The whole point of his coming was to save mankind. I realized that He came to the]" time="0.314"><properties><property name="score" value="0.003987892" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[See What We\u2019ve Been Up to!\n\nDo you want to know what we\u2019ve been doing with the movies? Well, here\u2019s a quick rundown.\n\nCOLD WAR (with Tim Roth) \u2013 Dan is currently in development on a feature-length version of the short with Tin Star TV.\n\nLIFE SUPPORT (with Julie Walters) \u2013 The full feature has just finished post-production and is looking for a distributor. It has had a private screening at this year\u2019s BFI London Film Festival.\n\nDREAMWORLD (with Douglas Henshall) \u2013 Life and times of Alfred Wallace, who came up with the theory of natural selection, but had his ideas pinched by the infamous Charles Darwin. The film is in pre-production with Electric Pictures.\n\nSHELTER (with Adam Rayner and Bernard Hill) \u2013 UK feature about a homeless man and the estranged daughter who cares for him. Dan is currently in pre-production with Lionsgate.\n\nCHEERIOS (with Harry Lloyd) \u2013 Another one of Dan\u2019s shorts, this is a comedy drama about a family with a dying son. The short has been selected for film festivals around the world and won numerous awards.]" time="0.346"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
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||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[To find the best restaurants near you, just enter your location into the search field and the restaurants will show up in a few seconds.\n\nWhat to eat in Italy?\n\nThe selection of Italian restaurants near me is the best on a restaurant and cafe app. Select your region or type in a town, village, postcode, a street name or a square and you will see a list of restaurants near me. Filter by price, type of cuisine or what's popular.\n\nItalian cuisine is known for it's fresh ingredients and regional specialties. To get a good feel for Italian cooking, you need to try each region's specialities.\n\nItalian Cuisine and Where to Eat it\n\nItalian food is all about local and fresh ingredients. Expect pasta, meat, cheese, fish, wine, and bread to feature heavily on a typical Italian menu. Eating out in Italy is an experience in itself, with food served on real plates and in restaurants with atmosphere to match. You can get a taste for Italian food in Britain, but it won't match the real thing.\n\nItalian food in Britain\n\nCrispy, fried, or grilled? With so many different types of pizza, the Italian restaurant menu can be hard to navigate. Luckily, we're here to help you out. Get ready to tuck into some of the best food on the planet. What are you waiting for? Order now and enjoy the best pizza!\n\nItalian Food Delivery\n\nDo you want to make the perfect meal but you are not sure what to cook? Don\u2019t worry, in the times that you are not sure of what to cook, the Italian restaurants have the solution. Just order what you want and our restaurant is the solution for you. Now you can order online and everything you need is in the palm of your hand.]" time="0.343"><properties><property name="score" value="0.3061239" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.3061239 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.3061239
|
||
assert 'Human' == 'AI'
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- AI
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+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Unleash the Power of Your Language\n\n\u201cLearn How To Speak French Fluently In Just a Few Weeks\u201d\n\nFrench For Beginners: Step-By-Step French (5 CD set) \u2013 Learn to speak and understand everyday French words and phrases!\n\nDiscover The Easy Way To Learn How To Speak French\n\nAchieve Your Language Learning Goals \u2013 And Discover What French Is All About!\n\nSee a sample of this course\n\nTOTAL PAGES: 90\n\nGet Started In French Today\n\nMastering the French language may seem challenging, but with this easy-to-follow course, you will quickly become more confident in the French language. This course is designed to help you achieve your goals in speaking, reading, and understanding the language.\n\nLanguage is a fascinating topic, and knowing how to communicate effectively with other people is a key to success in a globalized society. This course is an effective means for you to learn the language of French, and more specifically, the local French spoken in France.\n\nIf you have never learned a foreign language before, this course can get you started right.\n\nIt will give you a clear insight into the basics of the language, and its essential parts. It is also a complete guide to getting to know the local French.\n\nYou will learn how to pronounce French words with clarity, and have a basic understanding of how to converse in the language.\n\nLearn how to hold a conversation in French with confidence!\n\nThis course has been written for people who would like to start learning the French language, as well as those who want to increase their vocabulary, expand their cultural understanding, or need French for their work.\n\nIf you have been studying French for some time and have gotten to a plateau, then this course will help you go beyond that plateau. The course can also be used as a refresher course to give you more confidence in the language.\n\nThere is a no-risk guarantee with this course. You are protected by a 60 day, money-back guarantee, and are fully covered by our no-risk, no-nonsense guarantee.\n\nSome of the topics covered in this course include:\n\nFacts About The French Language\n\nGreetings In French\n\nIdioms And Phrases In French\n\nA Guide To French Pronunciation\n\nAs well as grammar rules, grammar explanations, and hundreds of vocabulary terms.\n\nHere\u2019s What People Are Saying About This Course\n\nGaby Hernandez \u2013 \u201cGreat course! My instructor is patient and very thorough. Thanks for providing such a great resource!\u201d\n\nChloe Evans \u2013 \u201cThis is an excellent course. I learned so much! I would definitely recommend this course to anyone who wants to start learning French.\u201d\n\nPeter Johnson \u2013 \u201cI bought the course to learn a bit more French and for the advanced grammar. The instructor is excellent. The course is concise and well organized.\u201d\n\nSandra Hernandez \u2013 \u201cI am an advanced French student who has taken 4 years of French in high school and 6 years of French in college. I have a French instructor who is native French. I bought the course to brush up on grammar and to work on my listening skills. I thought the course was really good and the instructor is really good. I really enjoyed the course and feel that it is good for anyone, whether they are beginners or advanced. I would recommend this course to anyone who wants to learn French.\u201d\n\nChristina B \u2013 \u201cI bought this course because I am planning a trip to France, and I wanted to brush up on my French. I was pleasantly surprised. I\u2019ve learned so much. The course covers a lot of material in 5 hours. The instruction is very clear. I am very happy with my purchase.\u201d\n\nWhat People Are Saying About LanguageForBeginners.com\n\n\u201cThe lessons are very well laid out and explained.\u201d\n\n\u201cVery thorough, well presented and written.\u201d\n\n\u201cAn excellent course and great teacher.\u201d\n\n\u201cVery clear and to the point.\u201d\n\n\u201cThis course is perfect for beginners.\u201d\n\n\u201cThe course has helped me a lot.\u201d\n\n\u201cExcellent course for beginners.\u201d\n\nThe audio is very good. The teacher is excellent. The course is very well done.\n\nSee what you\u2019ll learn inside this course:\n\nWhat The French Language Is All About\n\nFrench Grammar In Detail\n\nBasic Sentence Structures\n\nGreetings In French\n\nWhat It Is Like To Speak French\n\nA Few Examples Of Conversations In French\n\nHow To Pronounce Words In French\n\nA Few Simple Phrases In French\n\nA Few French Idioms\n\nHow To Learn The Language Of French\n\nAnd much more!\n\nPlus, with this no-risk guarantee, you can\u2019t lose!\n\nIf you want to learn how to speak French, then you are in the right place. Take the first step towards improving your communication skills, confidence, and experience with a new language.\n\nClick the \u201cBuy Now\u201d button now to get started on your journey!\n\nRelated\n\nLanguage For Beginners: How To Speak French]" time="0.338"><properties><property name="score" value="0.004940318" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00494032 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00494032
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Self-Selection and Pupils\u2019 Labour Market Outcomes\n\nYoung adults from low socioeconomic status backgrounds are significantly less likely to go to university than their better-off peers. There is a significant self-selection in the probability of attending university and of high A-level achievement, which are key drivers of university participation. This paper exploits the introduction of minimum attainment targets in the National Curriculum for schools to explore the impact of early education policies on students\u2019 achievement and on their likelihood to study at university. We find that when minimum attainment targets are introduced, pupils from low socioeconomic status backgrounds are more likely to reach higher grade boundaries in the A-level exams, are more likely to go to university, and are more likely to study science or maths degrees.\n\nContents\n\nIntroduction\n\nData and methods\n\nAnalysis\n\nDiscussion\n\nConclusion\n\nIntroduction\n\nUniversity participation in the UK has grown substantially since the early 1990s. There are now 1.4 million undergraduates, which is almost double the number in 1992. However, participation rates have remained relatively low among those from lower socioeconomic groups (Furlong and Millar, 2008). For example, 40 per cent of young adults from high-income backgrounds were participating in higher education in 2011-12, compared to 21 per cent from the poorest fifth of families.\n\nTo some extent, low participation among young people from less advantaged backgrounds is to be expected given the historical association of university education with privileged groups. Participation rates increased significantly in the 1960s, after state support for university was extended to less affluent groups. Participation rose further during the 1960s, 1970s and 1980s, but then stagnated in the 1990s and declined slightly after 2002. Only in the past decade has participation among the less well-off again risen to the levels recorded in the early 1990s (see Figure 1).\n\nFigure 1. University participation rates by parental income, 1962-2012\n\nNote: Figures are cohort entry rates for those who went to university in each year. Sources: Department for Business, Innovation and Skills (2014); Sutton Trust/Ipsos Mori (2012); Education Policy Institute (2013).\n\nDespite increased participation, the gap in participation rates between young people from more and less advantaged backgrounds is still large, even after controlling for qualifications. On average, young people from the most advantaged fifth of families are about twice as likely to go to university as those from the least advantaged fifth (see Figure 2).\n\nFigure 2. Proportion of young people who go to university by family income, 1996-2012\n\nSource: Participation rates (log scale) are from the UCAS End of Cycle Reports, 1996-2012. The relative income quintiles are from the Family Resources Survey, 2008-2012. The quintiles have been adjusted to allow for comparison across years by using a fixed poverty line.\n\nAt a recent seminar organised by the ESRC Centre for the Microeconomic Analysis of Public Policy, Professor Martin Brown (2012) suggested that it is \u2018a great mystery why this gap is not widening even more\u2019. He also pointed out that there is a significant self-selection in the probability of attending university and of high A-level achievement, which are key drivers of university participation. It is well-known that, in addition to their socio-economic background, non-cognitive skills, such as motivation, are important predictors of academic achievement. Since the increase in university participation has been driven by the growth in participation of less advantaged groups, it is not surprising that it has also been associated with a fall in the average grades of university entrants.\n\nThis paper is motivated by this observation, that early education policies have played an important role in the increase in participation among less advantaged groups. We focus on two such policies: the requirement to meet minimum attainment targets in English, mathematics and science, and the national literacy and numeracy strategies. We explore the impact of these policies on students\u2019 achievement and on their likelihood to study at university. We find that when minimum attainment targets are introduced, pupils from low socioeconomic status backgrounds are more likely to reach higher grade boundaries in the A-level exams, are more likely to go to university, and are more likely to study science or maths degrees. We also find that the increase in the A-level scores and the higher participation rate associated with the introduction of minimum attainment targets cannot be explained by the improvement in the overall level of academic performance in schools or by the lower socioeconomic status of those schools that introduced minimum attainment targets.\n\nData and methods\n\nTo analyse the impact of minimum attainment targets, we use the school-level dataset that the Department for Education makes available annually for the National Pupil Database (NPD). The NPD contains rich information about individual pupils and their schools. We first use the NPD to examine the evolution of achievement at the end of compulsory education by using cohort-level information on final examinations. We then explore the impact of minimum attainment targets using changes in the composition of achievement. The results we present in this paper are robust to the alternative methods of analysis of achievement levels and changes in the composition of achievement.\n\nIn the first stage of our analysis, we explore the evolution of the A-level examination results by using the cohort-level information on final examinations. To study the evolution of achievement at the end of compulsory education, we use the data on A-level grades in GCSE and A-level examinations from 1996 to 2012. In this period, the examinations have changed significantly, from the General Certificate of Secondary Education (GCSE) to the General Certificate of Secondary Education (GCSE) and the A-level examinations. The A-level examination was first introduced in the early 1950s as an academically rigorous alternative to the less selective B-level examinations (Wynne, 2010). Until 1988, A-level grades (i.e. O/A levels) were assigned by teachers, not by the students. From 1988, the responsibility for grading moved to schools. The examination was revised in the early 1990s, after which it was separated into two components: A-level and AS-level. The A-level examinations were re-structured in 2000. Most importantly, the exams have become linear rather than modular. The exams in each subject are now taken at the end of the two-year course. The exams are now externally assessed, and the grade is assigned according to the nationally defined A-level grade boundaries. The percentage of the cohort that sat the A-level examinations increased from about two-thirds in the early 1990s to more than 90 per cent in the mid-2000s. This reflects a policy shift in the assessment of vocational qualifications, which reduced the proportion of vocational qualifications that counted towards a student\u2019s A-level grade.\n\nWe use a slightly modified version of the grading system developed by Hayward, Parry and Stewart (2009) and Bias et al. (2011). We use a scale of 5 grades to assess the performance of students in different subjects: 5 is an \u2018A*\u2019 grade, 4 is an \u2018A\u2019 grade, 3 is a \u2018B\u2019 grade, 2 is a \u2018C\u2019 grade and 1 is a \u2018D\u2019 grade. The best possible grade in each subject is an \u2018A*\u2019. This grading system differs from the one used in most of the existing analyses of A-level results, which use an A-E grading system. The difference between the two grading systems is illustrated in Figure 3, which shows that about 60 per cent of the students in the upper grade boundary of \u2018A*\u2019 under the old system would be below the upper boundary of \u2018A*\u2019 under the new system. Similarly, about 45 per cent of the students in the lower boundary of \u2018C\u2019 would be in the upper boundary of \u2018C\u2019 under the old system, and about 25 per cent of students in the lower boundary of \u2018C\u2019 would be in the upper boundary of \u2018C\u2019 under the new system. We expect that the increase in the A-level scores associated with the change in the grading system will be smaller for subjects that were not directly affected by the reform, such as English, maths and science. We do not analyse students\u2019 performance in the core and non-core subjects, because data on the subject of A-level examination was not available for every pupil.\n\nFigure 3. Grading scales of GCSE and A-level examinations\n\nIn Figure 4, we present the cumulative distribution of A-level scores for each cohort, by the subject studied. Figure 5 shows that the average A-level score increased from a little less than \u2018C\u2019 in 1996 to more than \u2018C\u2019 in 2012, which is consistent with the improvement in the average GCSE results. The gap in the average grades between different subjects remained stable. The increase in the average A-level grades was particularly large in science subjects and in humanities subjects. We do not find evidence of a widening gap in A-level scores between the richest and the poorest students. In the humanities subjects, there is some evidence of an increase in the A-level scores of the less well-off. However, the increase in the average A-level scores was so large that the difference in the average scores between the richest and the poorest students decreased even though it was not eliminated.\n\nFigure 4. Cumulative distribution of A-level scores in different subjects, 1996-2012\n\nSource: National Pupil Database, Department for Education.\n\nFigure 5. Average A-level scores, by subject, 1996-2012\n\nSource: National Pupil Database, Department for Education.\n\nA key issue in the analyses of trends in A-level achievement is the impact of the increase in the proportion of students taking A-level examinations on the average score]" time="1.434"><properties><property name="score" value="0.06369336766666667" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[East Face\n\n\nSkye\n\nThe Complete Guide\n\n\nSummit view from the top of the Cuillin Ridge\n\nTrevor Nace\n\n\nFirst published in Great Britain in 2015 by\n\nThe Crowood Press Ltd\n\nRamsbury, Marlborough\n\nWiltshire SN8 2HR\n\nwww.crowood.com\n\nThis e-book first published in 2015\n\n\xa9 Trevor Nace 2015\n\nAll rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publishers.\n\nBritish Library Cataloguing-in-Publication Data\n\nA catalogue record for this book is available from the British Library.\n\nISBN 978 1 84797 713 2\n\nFrontispiece: Climber on the summit of the Cuillin Ridge in front of\n\nMuckross Ridge and Beinn Eighe\n\n\nTo my partner Sally, whose support and love made it possible for me to fulfil my dream of a lifetime on Skye.\n\n\nContents\n\n\nTitle Page\n\nDedication\n\nCopyright\n\nAcknowledgements\n\nList of Plates\n\n1 Introduction\n\n2 An Introduction to the Cuillin\n\n3 Access\n\n4 West of Glen Brittle\n\n5 The Coire Gabhail / North-West Ridge\n\n6 The Black Cuillin Ridge\n\n7 The Central Cuillin Ridge\n\n8 The South-East Ridge\n\n9 The Ar\xeate of the Great Tower and the Clach Glas Ar\xeate\n\n10 An Dubh Sgeir\n\n11 The North-East Ridge\n\n12 The Minnoch Burn\n\n13 Selected Bibliography\n\n\nList of Plates\n\n\nPlate 1: Spade Level, Coire an Lochain, Glen Brittle, in winter\n\nPlate 2: View of the Beinn Eighe massif from the east\n\nPlate 3: Snow-filled Coire na Banachdich, Coire an Lochain\n\nPlate 4: Black Cuillin ridge from the Spade Level\n\nPlate 5: Near the end of the Black Cuillin ridge\n\nPlate 6: Climbers on the summit of Tower Ridge\n\nPlate 7: Skye seen from the summit of the Cuillin ridge\n\nPlate 8: Climbers near the summit of Clach Glas Ar\xeate\n\nPlate 9: Snow on the summit of An Dubh Sgeir\n\nPlate 10: Landscape of the Minnoch Burn\n\n\nAcknowledgements\n\n\nFirst of all, I would like to thank John Brailsford, who accompanied me on my very first walk in the Cuillin in 1996 and whose generous and knowledgeable company has been a constant source of inspiration to me. A particular thanks also to Donnie Hall for all his practical support and guidance during my exploration of the Cuillin. I would also like to thank the helpful staff of the Skye Library in Kyle of Lochalsh, and Alison Connell for the excellent maps. I am grateful to the Climbers\u2019 Club for publishing my article on the Cuillin.\n\nFinally, a big thank you to Sally, who has been a constant source of encouragement, inspiration and love, and to my family and friends who have given me endless support.\n\n\nPlate 1: Spade Level, Coire an Lochain, Glen Brittle, in winter\n\n\nPlate 2: View of the Beinn Eighe massif from the east\n\n\nPlate 3: Snow-filled Coire na Banachdich, Coire an Lochain\n\n\nPlate 4: Black Cuillin ridge from the Spade Level\n\n\nPlate 5: Near the end of the Black Cuillin ridge\n\n\nPlate 6: Climbers on the summit of Tower Ridge\n\n\nPlate 7: Skye seen from the summit of the Cuillin ridge\n\n\nPlate 8: Climbers near the summit of Clach Glas Ar\xeate\n\n\nPlate 9: Snow on the summit of An Dubh Sgeir\n\n\nPlate 10: Landscape of the Minnoch Burn\n\n\n1\n\n\nIntroduction\n\n\nThe spectacular granite peaks of the Cuillin on the Isle of Skye have captured the imagination of hillwalkers and climbers for over a hundred years. When George Henry Alcock (1864\u20131941), a climber and mountaineer, visited the Cuillin in 1893, he wrote in his book Through the Highlands and Islands of Scotland:\n\nNo one who had not seen the Black Cuillin and the peculiar forms which the rocks assume would believe that nature could assume such strange shapes as are seen here. The first view of the Cuillin from the south makes them look like a huge fortress of rock, with fantastic turrets and chimneys, and battlemented walls.\n\n\nToday these classic features, viewed from the slopes of the nearby mountains of the mainland, such as the Beinn Eighe and M\xf2ine Mh\xf2r, have hardly changed. But the Cuillin are not just aesthetically pleasing. To their first British explorers in the mid-nineteenth century, the Black Cuillin, which form a massive ridge running from Coire an Lochain in Glen Brittle to An Dubh Sgeir, seemed a forbidding mountain barrier, \u2018a fortress of rock\u2019. Their modern reputation, and that of the smaller range of the Red Cuillin to the south-east, as a major challenge to both rock climbers and mountaineers, was established during the second half of the twentieth century. However, despite the presence of the two main ridges on the Black Cuillin (North-West Ridge and Central Ridge), many individual peaks, and the climbing routes up them, were relatively unexplored. This was to change in the 1970s and 1980s when many of the hard, mixed and winter routes, most of which were first climbed in the Cuillin, were recorded by enthusiastic pioneers. Today, climbing and scrambling in the Cuillin can be combined with hillwalking, and the varied routes, combined with the varied weather of Skye, offer an extremely satisfying and testing experience for a mountaineer.\n\nIn writing this guidebook, I have had to make many decisions regarding what routes to describe, and which to omit. Many climbers may not agree with my choices, and it is inevitable that a guidebook such as this will not be comprehensive. As well as describing my chosen routes, I have tried to include a range of other interesting aspects of the Cuillin, in order to make the book relevant to anyone interested in a mountaineering trip to Skye.\n\nGeology\n\nThe geology of Skye, and especially the Cuillin, is fascinating, and as well as a number of peaks and ridges, it has given rise to a series of dramatic glens, the upper parts of which are in the Inaccessible Pinnacle (Coire nam Bian) to the north of the main ridge. The Black Cuillin consist of metamorphic rocks which were formed as a result of a major mountain-building event in the Caledonian Orogeny, the mountain-building event which took place between 500 and 400 million years ago. At this time, a number of folds (anticlines and synclines) were formed, some of which can be seen today. The Blue Stack of the Old Man of Storr, for example, was the result of the raising up of a syncline (Fig. 1). This event also resulted in the granite being exposed to the surface, but this did not happen everywhere. To the east of the island, most of Skye is underlain by metamorphic rocks, but to the west, particularly on the western coast of the Trotternish peninsula, granite is exposed. The Blue Stack is also part of a major fold which has resulted in the formation of the Trotternish Ridge.\n\nFigure 1. The Blue Stack of the Old Man of Storr.\n\n\nThese major events have also resulted in a relatively complex geological map, with three main rock types (Fig. 2). A general layer of granite, called the Inaccessible Pinnacle Quartz Diorite, extends from the Blue Stack north-eastwards to Beinn Eighe. This granite has been intruded by the Red Cuillin Granite, which has a different composition and thus has different characteristics to the underlying rock. In the central and eastern parts of the main ridge of the Black Cuillin, the rocks are composed of the Papcastle Gneiss, which is a granitic metamorphic rock. However, to the west, around Sgurr nan Gillean and Glas Bheinn, the Papcastle Gneiss has been intruded by the Kintail Granite, giving rise to a more mottled appearance in this part of the Cuillin. A further complex of rocks is exposed on the north side of Glen Brittle, which includes the Torridonian Sandstone, Lewisian Gneiss, and Dalradian schists.\n\nFigure 2. Geology of Skye showing the main rock types.\n\n\nPeaks\n\nAs well as providing interest to geologists, the geomorphology of the Cuillin is also fascinating for climbers and walkers. With so many ridges and peaks, there is much to explore, and each summit offers its own rewards. Some of the individual peaks are not very high, but offer serious scrambles and rock climbs, while others, such as the highest summit of Sgurr nan Gillean (1,018 m) and the first major peak on the Central Cuillin Ridge, Sgurr Dearg (974 m), offer impressive views. Sgurr nan Gillean]" time="0.871"><properties><property name="score" value="0.2644716" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Orangeville Banner\n\nOrangeville, Ontario, Canada\n\nApril 9, 1905\n\nPAPER HUNT CONTINUES\n\nINSTEAD OF CASHING $5.00 BILL\n\nA message has been received at the Herald office from Orangeville to the effect that a lady, who has had $5.00 stolen from her purse, did not give the money to an expressman, as stated in last issue, but to another man whom she has not been able to identify, and that the messenger from St. Catherine will not get the money unless he turns it over to her. We have been searching for this lady for several days, and when the Herald office was last searched, we overlooked this message.\n\nAnother story of the stolen money says the woman, whose name is not given, gave the money to a young man who said he was a messenger from St. Catherine, and promised to deliver the money to the party it was addressed to at Kincardine.\n\nTHE MAYOR DISQUALIFIED\n\nA meeting of the citizens of Orangeville was held last Saturday evening at the Orangeville Town Hall, with Dr. A. S. Gibson, M.P., in the chair, to take into consideration the statement made by W. A. MacLean that Mayor D. M. McKenzie was disqualified from holding office under the Municipal Act of Ontario. It was resolved that the matter be placed before the proper authorities for them to decide. The mayor then withdrew from the hall.\n\nMayor McKenzie\u2019s statement in relation to his withdrawal from office is as follows:\n\n\u201cIn this connection I have no desire to act in any unbecoming manner, and I shall resign from the position of mayor. However, I do not desire to leave town. I will reside here and attend to my business as usual, and my many friends who know me and who are not residents of the municipality will be glad to meet me. I want to get at the bottom of this business and find out who it was that drew up the notice of my being disqualified. I was the first one to speak in this town against the big sewer, but I am satisfied now that my opinions are shared by the majority. I do not think that the matter will go much further than the city hall, and as soon as the legal steps are taken the city will be rid of this question.\u201d\n\nSILVER ORGANIZATION\n\nWe are glad to learn that a Silver organization has been formed in this town, and that a meeting is to be held at the Orangeville Opera House next Saturday evening. This is an organization for the purpose of working for free silver, and they are working under the leadership of W. H. Phillips, M.P.\n\nThe representatives of the Anti-poverty society who are here this week will probably have an engagement to-morrow evening. They are endeavoring to make Orangeville the headquarters of the work in this vicinity, and several of the agents will be here for some time. The meeting will be held at the town hall.\n\nA prominent Orangeville man, who is in the wholesale hardware trade in this city, returned this week from Chicago.]" time="0.438"><properties><property name="score" value="0.0051594106" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00515941 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00515941
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["Outstanding! Don't miss this book. No matter what is going on in your life right now, this book will speak to you and help you move beyond whatever has you stuck or hurting. Buy it, read it, and be better for it."\n\n"I am so very grateful that Kari Byron chose to share her story with the world. As a writer, I love to read memoirs, but this one was different than others I have read. The author shared her story in such a way that it was as if I was hearing it from a dear friend. In this era of time, it is refreshing to read something from someone who has the courage to share the good and the bad from their lives. I laughed, I cried, and I grew to appreciate the value of living. I hope this book will find its way into the hands of many who are struggling with life in a way that brings freedom to their hearts."\n\n"Kari Byron's book is a refreshing look into a woman's journey to finding joy after hardship. She offers hope and practical tips that can be used by women of all ages. This book is a must read."\n\n"I couldn't put it down! I'm a mom of 3 young kids and struggle with guilt daily, but Kari Byron's words of encouragement and her willingness to share her personal struggles make me feel like I can face my own obstacles and not feel alone."\n\n"Kari Byron shares her heart in this honest memoir and gives you the tools to follow your heart, your passion and live your life to the fullest! You are sure to find her journey inspiring!"\n\n"I loved this book. From the moment I picked it up, I couldn't put it down. It was a fun, easy read, but the lessons and life advice Kari shared had me reflecting and taking notes. I laughed and cried, and I'll be reading this book over and over again to encourage myself and remind myself of the lessons it teaches."]" time="0.479"><properties><property name="score" value="0.20373766" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Since the beginning of time, humans have been fascinated by the mysterious. The sky has always been full of questions. Our ability to dream big and speculate has enabled us to discover, theorize, and theorize even more. But where do we get the answers? These are the top 10 theories on the unsolved mysteries of the universe.\n\n10. Extraterrestrial Origin\n\nThe human race began to emerge from the Stone Age. The caves and forests were just getting familiar with the new inhabitants. There was a long time of fear and ignorance. Before we started to understand the world, they began to imagine what is outside the world. Some thought of creatures so powerful that they could destroy the world. Other speculated that we are a higher level of evolution and are the result of genetic experimentation of extraterrestrial beings.\n\nLater, these speculations were transformed into mythology and the imagination of the humans. In our modern world, it has turned into science. Many scientists still believe that we are not the only life in the universe and that at some point in history there was a connection with extraterrestrials. Some of them even believe that the first stages of our life were carried out with the help of aliens.\n\n9. Time Travel\n\nSince the beginning of history, people have always been fascinated with time. To travel back in time would allow us to explore the unknown, but would it be worth it? We live in a world where time is constant. Change is one of the most important principles of human life.\n\nNevertheless, many scientists still consider the possibility of time travel. The hypothetical method would be to build a giant machine that would make a hole in time. But how can this happen? It would involve breaking the speed of light and space.\n\nThe machine would have to be so big that it would create a massive black hole. Then the time machine would be moved into the center of the black hole, which would allow it to break the laws of time. So far, scientists have not been able to prove the validity of this theory.\n\n8. Time Travelers\n\nDespite the fact that time travel is still a hypothesis, there are people who believe that it is not. They claim to have traveled back in time to the present or to a previous generation. For this reason, there are also numerous stories about people who claim to have returned from the future to save the world.\n\nMost people who claim to have traveled back in time are just crazy. However, many scientists consider it possible that in the future, when we understand the laws of physics better, we may be able to travel through time. This possibility has been a mystery for a long time. So, this is a list of top 10 theories on the unsolved mysteries of the universe.\n\n7. Deja Vu\n\nThe theory of Deja Vu is so controversial that many scientists do not even dare to think about it. The definition of deja vu is, when a person experiences something, although he has never done it before. Many people think of it as a kind of visual hallucination. The most popular theory about the phenomenon is that it is a past memory that has not been triggered by the usual way.\n\nAnother possible explanation is that the brain creates a fake memory to deceive the person who feels it. The theory is that in reality the person does not experience a deja vu, but it is an internal response to the same scenario. In short, the brain recognizes the environment and recognizes the story that it represents.\n\nIn this case, the illusion is that the person has lived through this scenario. Nevertheless, there are many people who do not think so. The reason is that deja vu is a phenomenon that occurs in any person. So, we have 10 theories on the unsolved mysteries of the universe.\n\n6. Water World\n\nIt is one of the most popular theories in the world of science. It is believed that the moon is a result of a collision between the Earth and a body much larger than it. As a result of the collision, our planet was literally ripped. But what happened to the mass that fell on the surface? According to scientists, this part of the Earth remained liquid.\n\nThe evidence is so compelling that the theory of the water world has become a reality. For example, there is a large number of scientists who believe that the moon was the result of the Earth\u2019s rotation and gravitational collapse.\n\nMoreover, there are evidences that this theory may be true. For example, when scientists tried to drill in the Antarctic, they found water underneath. Also, according to many scientists, the planet Mercury, which has no magnetic field, may be the result of the remains of the water world.\n\n5]" time="0.405"><properties><property name="score" value="0.06907027" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[There are no spoilers in this review\n\nFrom the off, the third episode in the new Star Trek Discovery series has a slow pace. It is the most quiet of the three episodes and is more of a character study in the struggles faced by all of the Discovery crew and how that manifests in different ways. With that in mind, I find it strange that this is not getting the universal praise that the first two episodes were. But that\u2019s the power of spoilers I suppose, no one knew what was coming in the first two episodes.\n\nThe episode itself, despite being more quiet than the first two, still manages to deliver plenty of story. You do have to take it with a grain of salt because some of the \u2018bad guy\u2019 stuff is almost unbelievably naive but that\u2019s the Star Trek universe for you. Despite the low stakes, I was still hooked on every word and scene.\n\nThere are plenty of hints that we can be certain that there is a big bad out there that we have not seen yet. Perhaps that is what made the episode more interesting. There is something looming over them and we don\u2019t know what it is yet.\n\nFor some reason, people seem to have a problem with the fact that the crew spend time getting to know one another, with only a couple of scenes of violence and action. Personally, I found that the social dynamics between the characters to be very interesting and engaging. Yes, this is probably true to life and does have some real life parallels. I am glad they did not waste time with all of that mindless action that I\u2019ve become so accustomed to.\n\nThere are no huge shocks in this episode and the pay offs to the mini story arcs were a bit weak. But when the pay off came, I was still glad that they took the time to introduce us to the characters in this way.\n\nIf you have been put off watching Star Trek Discovery because of the fear of spoilers, then I would suggest you don\u2019t worry too much and go ahead and start the show. If you can manage to resist the temptation of the spoilers for the next two weeks, then I think you will be very happy with the third episode and the direction the show is heading in.\n\nLet us know what you thought of the episode in the comments below and if you have seen the first two episodes.]" time="0.348"><properties><property name="score" value="0.32030076" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[You might know of me. I am one of the project managers for Windows 7. Or Windows 7 team is one of the teams that I work in. As a lot of you know, my favorite and almost only thing to do when I am not working is to read a good book. Well, I have done it again. I just finished the book I am about to recommend to you. This book is called \u201cReady Player One\u201d by Ernest Cline. I can\u2019t recommend this book enough. So what\u2019s the big deal? You are about to find out.\n\nSo what is it about?\n\nThis book is a story about Wade, a teenager, living in the year 2045. The world is in a bad state.\n\nTechnology has progressed very fast, but a lot of humans have been left behind. Wade\u2019s life sucks. He lives with his aunt in the slums of Oklahoma. All he does is play video games.\n\nThen, one day, he hears of a contest to win a fortune by finding the first Easter egg in the virtual reality game OASIS. The creator of OASIS has died and has left behind a secret quest. A quest that has the prize to the first person to complete the quest. But there is a catch: only the creator of the game knows how to find the Easter egg. And he has hidden the clues in the game.\n\nIt is up to Wade to try to find the Easter egg first. But not alone. He quickly assembles a group of fellow OASIS players. This group consists of his best friends and fellow gamers. This quest will soon turn into a journey. And I don\u2019t want to tell you more, because I don\u2019t want to spoil the story for you.\n\nA bit about the Author:\n\nErnest Cline is the author of the book Ready Player One. He is from the state of Texas. He has lived in New York City for a few years, but has now moved back to Texas. He is 40 years old and has been writing books for a long time. His first book was published in 2001.\n\nErnest Cline is very much into old science fiction books, and especially the 1980\u2019s. He loves the music, TV shows, video games and movies of that decade.\n\nMy thoughts:\n\nWhen I read this book, I really couldn\u2019t put it down. I just wanted to know how the story would end. I wanted to know if the good guys would win. I wanted to know how they would beat the bad guys.\n\nI am sure you will love this book, just like I did. It is filled with great references to the 1980\u2019s. If you are born after that time, you will probably have to read the story first to get the references, but I am sure you will enjoy it.\n\nI will also tell you, that this book is a great story, and I can easily recommend this book to any reader. It is not just a story about technology. It is also a story about friendship and courage. And in the end it is a story about hope and dream.\n\nIf you want to read this book, you can find it on Amazon. Or your favorite bookstore. I am not going to tell you how much it costs. I am just going to tell you that it is well worth the price.]" time="0.366"><properties><property name="score" value="0.09371428" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Additional information\n\nApplicants must be 18 years of age or older and must complete and submit the National Labor Relations Board (NLRB) #6 or #7 form, indicating that they will not engage in secondary boycotts or strikes.\n\nThis position is in the bargaining unit.\n\nWe will require your W-2 forms as well as your Federal tax returns for the previous year for verification of your claimed dependents.\n\nApplicants must have unrestricted United States Government security clearance with the Department of Defense or its contractors to be eligible to work in a building that is controlled access.\n\nThis position is located in a National Defense Center. Individuals must be U.S. Citizens or U.S. Nationals (no exceptions) or eligible to be a U.S. Citizen or U.S. National to be hired in this position.\n\nApplicants who have not yet completed a Security Clearance must be able to obtain one in a reasonable amount of time.\n\nApplicants must have or be able to obtain a high school diploma, GED, or other equivalent qualification, and two years of job related experience to be hired.]" time="0.379"><properties><property name="score" value="0.758418" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[HARRY POTTER and the Order of the Phoenix is a 2007 British-American fantasy adventure film directed by David Yates and distributed by Warner Bros. Pictures. It is based on the novel of the same name by J. K. Rowling. The film, which is the fifth instalment in the Harry Potter film series, was written by Michael Goldenberg and produced by David Heyman and David Barron.\n\nThe film stars Daniel Radcliffe as Harry Potter, alongside Rupert Grint and Emma Watson as Harry\u2019s best friends Ron Weasley and Hermione Granger.\n\nThe story follows Harry\u2019s fifth year at Hogwarts as the Ministry of Magic is in denial of Lord Voldemort\u2019s return. Harry must uncover the truth, with the help of his friends, and confront Voldemort.\n\nThe film began production in early 2007 and was released in theatres in the United Kingdom and United States on 12 July 2007, grossing a total of $292 million at the worldwide box office.\n\nThe film was nominated for two BAFTA Film Awards in 2008.\n\nFollowing a Harry Potter fan\u2019s dream that Harry\u2019s late headmaster Albus Dumbledore is alive, and in a critical condition at the Ministry of Magic, Harry Potter and his friends Ron Weasley and Hermione Granger, decide to rescue him, as the school year comes to a close.\n\nOn the night of their attempt to break into the Ministry, Ministry of Magic employee Delores Umbridge slashes Rubeus Hagrid\u2019s hand with a knife, accusing him of stealing her kitten.\n\nHarry, Ron, and Hermione fight the Death Eaters. Lucius Malfoy and his son Draco both try to attack Harry, but he manages to save himself. Harry, Ron and Hermione get separated, and in the chaos, Ron manages to grab the prophecy from the Ministry\u2019s Hall of Prophecies.\n\nHarry and Hermione escape the Ministry, and Ron awakes to see Harry and Hermione\u2019s signatures on the prophecy, but does not know that Harry had ripped the prophecy out and left it in the hands of his godfather, Sirius Black, before he was killed.\n\nSirius, Harry, and Hermione head to the headquarters of the Order of the Phoenix, where they meet with fellow members Remus Lupin and Nymphadora Tonks, and Sirius\u2019s brother, Regulus.\n\nThe Order is joined by the regular adult wizards and witches in the battle, as Voldemort and his Death Eaters take over the Ministry of Magic and declare martial law on the entire Wizarding community.\n\nAlbus Dumbledore appears to die in battle, but this is revealed to be a ruse, as he and Severus Snape attack Voldemort and Lucius Malfoy, and attempt to take the prophecy from Ron. Lucius disarms Dumbledore, and an enraged Bellatrix kills him.\n\nBellatrix and Narcissa Malfoy stand by their husbands\u2019 sides. Albus Dumbledore\u2019s portrait is replaced with one of Snape. Harry, Ron, and Hermione are rescued by Order members. Voldemort and the Death Eaters leave the Ministry.\n\nHarry, Ron, and Hermione are told by Remus Lupin that all of the other Order members have been killed. Harry attempts to repair his damaged wand. He is visited by Snape, who tells Harry that the boy\u2019s wand is irreparably damaged and needs to be destroyed, as Voldemort has become aware that the wand is of a \u201cunique\u201d nature.\n\nThe two engage in a fierce duel in which Snape calls on his master to save him. Harry is unaffected by the curse due to his ability to cast a shield charm. He manages to shield himself and fight back, and in his distraction, Snape accidentally breaks his neck and dies.\n\nHarry meets with Dumbledore\u2019s portrait, who reveals to Harry that the boy\u2019s mother died to save him, and Harry is filled with his mother\u2019s love. Harry reveals that he feels angry and confused at this revelation.\n\nHarry also learns that the reason that Voldemort has gone to such great lengths to kill him is that Harry is a Horcrux, a piece of Voldemort\u2019s soul that resides in Harry\u2019s body.\n\nHarry then leaves Dumbledore\u2019s portrait and meets with Ron and Hermione, who have just been told that the students and staff are to evacuate the school, as the Death Eaters have declared that Hogwarts is no longer safe.\n\nHarry, Ron, and Hermione are joined by Remus Lupin, Nymphadora Tonks, and several other members of the Order of the Phoenix, and they apparate to 12 Grimmauld Place, the headquarters of the Order.\n\nThe Battle of the Department of Mysteries is followed by the Death Eaters taking over the Ministry of Magic, as they believe the prophecy to be a key to Voldemort\u2019s victory. Harry returns to Hogwarts to retrieve the prophecy from Voldemort.\n\nHe, Ron, and Hermione get ambushed by Death Eaters, and when Harry goes after the prophecies, he ends up dueling with Voldemort.\n\nHarry calls upon the remaining strength of his mother\u2019s love, and as Voldemort\u2019s Killing Curse rebounds upon him and hits Harry, the battle is ended, and the school is cleared of the Death Eaters.\n\nHarry wakes up to find Dumbledore, Sirius, and Remus in the hospital wing, as well as his friends and the rest of the school, and he realizes that he is safe.\n\nDumbledore then proceeds to give Harry his restored invisibility cloak, explaining to Harry that the Invisibility Cloak is one of the Deathly Hallows. Harry then says goodbye to his friends, as he leaves with Dumbledore to destroy the seven horcruxes that contain fragments of Voldemort\u2019s soul, which will make him immortal.\n\nThe film ends with Harry and Dumbledore leaving the school in a car, accompanied by Professor Minerva McGonagall.\n\nI liked this movie as it is full of action and adventure. The plot is great as well as the dialogue. It is a well made movie and it is very entertaining.\n\nThis movie is definitely a must-watch, as it has plenty of action as well as being very humorous.\n\nAdvertisements]" time="0.792"><properties><property name="score" value="0.00871626285" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00871626 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00871626
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Hush, little baby, don't you cry\n\nI know a thing or two that will make you happy,\n\nIf you will only come with me.\n\n\n\nHush, little baby, don't you cry\n\nI know a thing or two that will make you happy,\n\nIf you will only come with me.\n\n\n\nIn my bag there's a beautiful surprise,\n\nIf you will only come with me.\n\n\n\nOn my back I'll show you the sights\n\nThere's a rainbow in your eyes,\n\nThere's a sweet, sweet lullaby\n\nIn your mother's smile.\n\n\n\nOn my back I'll show you the sights\n\nThere's a rainbow in your eyes,\n\nThere's a sweet, sweet lullaby\n\nIn your mother's smile.\n\n\n\nHush, little baby, don't you cry\n\nI know a thing or two that will make you happy,\n\nIf you will only come with me.\n\n\n\nIn my bag there's a beautiful surprise,\n\nIf you will only come with me.\n\n\n\nOn my back I'll show you the sights\n\nThere's a rainbow in your eyes,\n\nThere's a sweet, sweet lullaby\n\nIn your mother's smile.\n\n\n\nIn my bag there's a beautiful surprise,\n\nIf you will only come with me.\n\n\n\nIf you will only come with me.\n\n\n\nOn my back I'll show you the sights\n\nThere's a rainbow in your eyes,\n\nThere's a sweet, sweet lullaby\n\nIn your mother's smile.\n\n\n\nIf you will only come with me.]" time="0.332"><properties><property name="score" value="0.0026515888" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Mileage : 19,038 (77,223)\n\n: 19,038 (77,223) Transmission : 4-Speed Automatic\n\n: 4-Speed Automatic Exterior Color : Green\n\n: Green Interior Color : Light Blue\n\n: Light Blue Engine : 351\n\n: 351 VIN : #B9QWL214742\n\n: #B9QWL214742 Stock Number : 96988\n\n: 96988 Fuel: Gasoline\n\n1954 Ford Crown Victoria\n\nThis Ford is a very nice car, we are selling it at a fraction of the cost of building it! The motor is a very desirable 351 V8 and is equipped with a nice sounding Holley 650 carburetor. It runs well and has plenty of power. The trans is an automatic C4 and shifts smooth. This Ford is in great shape, the only exterior rust that I could see was on the door bottoms and they are easy to replace. Interior is in very nice shape, new headliner, new seats, new carpet and a nice newer steering wheel. It has power brakes, power steering, air conditioning and power top. These cars are extremely rare to find in this condition and price. If your looking for a car that is cool and nice to drive then this is it.]" time="0.002"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Create our team or join our team.\n\nIf you are an organization, brand, or personality and you want to take your show to the next level then get in touch! Email us at team@geekarmy.com and we will get right back to you.\n\nCreate a new Team\n\nSimply sign in with your username and password. If you do not have an account you can create one here.\n\nAfter signing in you will be able to create a new Team. You will be able to add a short name, a full name, a URL and a description. You will also be able to upload a logo for your team and a picture for the team members.\n\nEdit an existing Team\n\nSimply sign in with your username and password. If you do not have an account you can create one here.\n\nSelect the team you wish to edit from the My Teams page. From there you will be able to edit the team name, upload a new logo, a picture for the team members, and a URL and description. You will also be able to add members to your team.\n\nSearch for a team\n\nTo find a team click on the Teams Tab and you will be able to search by a number of different criteria including team name, brand name, member count, and popularity.\n\nAfter you find a team you are interested in, simply click the button at the top of the page to see more information about the team.\n\nJoin a team\n\nOnce you find a team you are interested in, simply click on the Join button and you will be taken to the join page. Here you will be able to apply to join the team.\n\nAfter you apply you will be sent a confirmation email. The email will contain a link for you to confirm your join request.\n\nAll of our applications are manually reviewed and you will be sent an email to notify you whether you have been approved or not.]" time="0.382"><properties><property name="score" value="0.023352776" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[John Mayer Just Made A Fool Of Himself In An Interview With The New York Times\n\nBy James Wilson-Taylor\n\n"We love to focus on my flaws and make them bigger than they are."\n\nJohn Mayer has come out fighting in a new interview with the New York Times, discussing a range of topics including the ghostwriting controversy, his upcoming tour with the Dead & Company and the end of the line for the John Mayer Trio.\n\nThe article details a frank conversation with the singer, in which he shares his honest thoughts on everything from his troubled past, to his use of social media, to the over-analytical nature of modern day music criticism.\n\nThe interview was conducted as a two-day workshop with NYU's music journalism department, which of course meant that the whole thing was promptly picked over by the internet on Tuesday night.\n\nHere's a selection of the choicest cuts:\n\nHis Vocal Fry Controversy:\n\n"The most controversial thing I\u2019ve done recently is affect a slightly looser, lower register on some songs, which I think makes the songs more interesting."\n\nOn Taking Himself Less Seriously:\n\n"I remember thinking I have a platform and I have a microphone and I have a position of power, so let me try to change some things, maybe for the better. And people did not like that. I remember having this conversation where somebody said to me, \u2018When you are perceived as yourself, people have a hard time relating to that.\u2019 And I said, \u2018I think you are misperceiving yourself to be someone who has a choice.\u2019 I\u2019m not saying this like, \u2018Hey, world, my message is this, and you\u2019re going to like it.\u2019 That\u2019s not what it\u2019s about. It\u2019s about the moment in which you are caught off guard, and you\u2019re on tour and you\u2019re not doing what you\u2019re supposed to be doing, but you\u2019re still getting a check."\n\nOn The Benefits Of Ghostwriting:\n\n"I don\u2019t have any beef with the world. I\u2019ve got a bunch of kids and a beautiful girlfriend and a house that I love and that\u2019s not an accident. And I\u2019ve worked for that and I\u2019ve gotten that because I\u2019m an easygoing guy who really enjoys life. And I\u2019ve always been super-vigilant about my ability to access joy."\n\nOn Being A 'Bubblegum Pop Star':\n\n"I was, for a very brief period of time, a bubblegum pop star. I was in the No. 1 pop band of the late-\u201990s, early 2000s. I\u2019ve had 18 or 19 top 10 songs. I have the right to call myself a singer, I guess. But I would never want to turn my back on being a guitar player and a songwriter. And the reason why is because I have a fan base that loves me for being a guitar player and a songwriter, and it\u2019s very separate from the people who like my pop songs."\n\nHis Concert Review Regrets:\n\n"I was like, \u2018Look, we\u2019re going to be under these bright lights, and it\u2019s going to be this one moment in time where we\u2019re going to play it for you. And we want to give you the most you can get for your dollar.\u2019 And then I think I had a bad couple of years. And I lost myself and tried to get myself back, and now I\u2019m playing shows where, like, I\u2019m not having a good time."\n\nOn Live Music Criticism:\n\n"I think we\u2019re overintellectualizing music. The discussion about music is so myopic and minuscule. \u2018He did this, and it\u2019s a disservice to this particular song.\u2019 And I\u2019m like, well, maybe you don\u2019t like this song. If you don\u2019t like it, just don\u2019t buy it. But that\u2019s not the way it works anymore. So I think we\u2019ve been eating the meat and spitting out the bones. You just want to get the marrow."\n\nThe New York Times concludes by highlighting the vocal coaching he undertook in 2015 in order to overcome his vocal issues:\n\n"I went and saw a vocal coach who I had seen when I was on my 'John Mayer's Journey Continues' world tour. She was a big hero of mine. She\u2019s the one who said to me, 'John, you just don\u2019t like how you sound. Why don\u2019t you do something about it?' I said, 'I can\u2019t afford to do anything about it.\u2019 She said, 'That\u2019s not true.\u2019 "\n\nWatch our video of John's recent live cover of 'A Hard Day's Night' here:]" time="0.395"><properties><property name="score" value="0.019235214" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01923521 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01923521
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[COLD SPRING, Ky. (WKYT) - The Kentucky Department of Fish and Wildlife Resources says an investigation into the shooting of a horse at the Country Pleasures horse farm has been completed.\n\nAccording to KDFWR, a citation has been issued to a person involved in the incident. The citation will be mailed to the person's last known address. The citation is for the willful waste of wildlife.\n\nThe investigation by KDFWR has revealed that on June 11th, 2013, three horses were shot on a farm off of Logan Road in Bath County. One horse, a white and gray Paint Mare was found dead. The mare, named "Sissy," had a history of being aggressive towards other horses. A chest wound indicated the horse had been shot at close range.\n\nThe second horse, a dark brown and white mare named "Bonnie," had been shot in the rump. Bonnie was treated by a veterinarian for the wound, and released. The third horse, a dark brown and white gelding named "Ghost," had a wound on his shoulder. He was treated by a veterinarian and released.\n\nKDFWR says the investigation concluded that the shooting of the horses was accidental.\n\nKDFWR says no additional charges will be filed in this case.]" time="0.323"><properties><property name="score" value="0.15971425" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Please enable Javascript to watch this video\n\nST. CHARLES, MO (KPLR) - The now former police chief of St. Charles has been arrested for drunk driving. A spokesperson for the St. Charles Police Department says Officer Robert Hertzell was on duty and was driving a marked police vehicle.\n\nSt. Charles Police Chief David Kinkead has put Hertzell on unpaid administrative leave and has initiated an internal investigation.\n\nSt. Charles Mayor Sally Faith says Hertzell will remain on unpaid leave until the investigation is complete.\n\nChief Kinkead released a statement saying, \u201cI was very disappointed to learn about this incident. As a police chief, I hold myself and my command staff to the highest standard. I expect my officers to be role models and to demonstrate professionalism and respect. We have a lot of hard working men and women in the St. Charles Police Department and they are to be commended for their work on a daily basis. The actions of one officer, however, is not reflective of the entire command staff or the great work that our officers perform each day. We must continue to move forward with the work that we have been doing to create a safe and vibrant community for all of our residents and visitors.\u201d\n\nHertzell has been with the St. Charles Police Department since 1995.]" time="0.399"><properties><property name="score" value="0.24069703" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24069703 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24069703
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[What happened\n\nShares of Applied Optoelectronics Inc (NASDAQ:AAOI) were getting hammered on Thursday after the networking specialist reported a quarterly loss and revenue that missed estimates. The news sent the stock down 15% at the time of this writing, putting it on pace to be the stock's worst day since late 2016.\n\nSo what\n\nInvestors were expecting Applied Optoelectronics to lose money in the fourth quarter, as it has lost money in each of the past two quarters. But the loss this time around was bigger than expected, with Applied Optoelectronics reporting a non-GAAP net loss of $0.40 per share on a 14% decline in revenue to $93.9 million. Analysts, on average, were only looking for a loss of $0.33 per share on $92.1 million in revenue.\n\nNow what\n\nCEO Paul E. Jacobs called the results a "solid performance" and said the company's overall sales were "driven by market growth" and its plan to "increase long-term shareholder value." Applied Optoelectronics also noted that its total customer backlog rose 20% year over year to $347 million, which is more than analysts were looking for.\n\nWith the company's stock now trading down 45% over the past year, however, it will need to show much more than "solid performance" to prove that its turnaround is working. To start with, it needs to stop the losses and start producing profits again. If it can do that, then the rise in the backlog will be a positive sign, and investors may start to take a fresh look at the company again.]" time="2.579"><properties><property name="score" value="1.0768692" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[These two teams have met eight times before with the Houston Dynamo winning five, the most recent meeting coming in last season\u2019s knockout round where Houston won 1-0 in Dallas.\n\nPROBABLE LINEUPS\n\nFC Dallas (4-4-2): Hartman; Loyd, John, Benitez, Morrow; Castillo, Jackson, Michel, Shea; Perez, Cooper.\n\n\n\nHouston Dynamo (4-3-3): Hall; Ashe, Taylor, Horst, Chabala; Moffat, Boswell, Creavalle; Bruin, Weaver, Davis.\n\n\n\nDID YOU KNOW?\n\nThis is the fourth time Dallas has made it to the semifinals. They've reached the final twice, losing to the New England Revolution in 2005 and D.C. United in 2007.\n\nDallas has won the U.S. Open Cup five times, the last coming in 1997. They are the only team in MLS with five Open Cup championships.\n\nDallas has reached the quarterfinals in three of the last four seasons.\n\nOnly one other team, the New England Revolution, has more postseason appearances (8) in the last eight seasons than the Dynamo.\n\nThe Dynamo\u2019s last win in the quarterfinals was over FC Dallas in 2008 when the Dynamo won 2-0 at Robertson Stadium.\n\nThe Dynamo\u2019s last two wins in the quarterfinals came on the road. They defeated Seattle Sounders FC 2-0 at Starfire Sports Complex in 2012, and the Portland Timbers 1-0 at PGE Park in 2011.\n\nForward Will Bruin has scored 12 goals in his last 18 matches in all competitions, including six in his last eight matches in MLS play.\n\nSuspended : None\n\n: None Suspended after next caution : None\n\n: None International duty : None\n\n: None Injury Report: None\n\nProjected Starting XI: Kevin Hartman (GK), Zach Loyd, Matt Hedges, George John, Michel, Jackson, Andrew Jacobson, Fabian Castillo, David Ferreira, Brek Shea, Kenny Cooper\n\nNotes: FC Dallas are undefeated in eight games at home this season. The last time they were shutout at home was against Real Salt Lake in May.]" time="0.353"><properties><property name="score" value="0.00085421436" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00085421 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00085421
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Sorcerous Origins\n\nUnbound Dancer\n\nUnbound Dancer\n\nSometimes called veils, a particular style of dancer that have sprung up in different cultures across the planes.\n\nCeaseless Dance\n\nAt 1st level you learn a ritual that allows you to spend 8 hours dancing and stamping out a particular pattern. This can be done during a short rest and while you do this you can spend up to half your sorcerer level (rounded up) in sorcery points.\n\nYou must finish a long rest before you can perform this dance again.\n\nWhen you complete the dance you gain the following benefits:\n\nYou have a base movement speed of 15 feet and your maximum movement speed increases by 5 feet.\n\nYou can add half your proficiency bonus (rounded up) to all dexterity ability checks.\n\nYou gain resistance to poison damage.\n\nYour skin becomes extremely smooth and soft and you have advantage on all charisma ability checks.\n\nYou have a +1 bonus to AC.\n\nThe following additional effects apply based on the number of sorcery points you spent on this ability:\n\n4-7 sorcery points: At the end of each of your turns you gain 5 feet of movement.\n\n8-11 sorcery points: You gain resistance to fire and cold damage.\n\n12-15 sorcery points: You gain a flying speed of 30 feet.\n\n16-19 sorcery points: You gain a second resistance to fire and cold damage.\n\n20 or more sorcery points: At the end of each of your turns you gain 10 feet of movement.\n\nPerform the Dance\n\nYou can only perform this dance once per long rest.\n\nStarting at 6th level you gain the ability to copy other creatures movements. You can use your action to study a creature within 5 feet of you for up to one minute. You can use your bonus action to then attempt to imitate that creature for one minute, using one of your known dance forms.\n\nYou must complete a long rest before you can use this ability again.\n\nExpanded Dance Forms\n\nAt 14th level you gain two additional dance forms. These can be from the expanded list on the next page. You can only perform each of these dances once per long rest.\n\nDance Forms\n\nDancing Viper: While dancing you can spend up to 4 sorcery points on the following effects:\n\n2 sorcery points: Gain a burrow speed of 20 feet.\n\n4 sorcery points: Gain a climbing speed of 30 feet.\n\n6 sorcery points: You gain resistance to piercing and poison damage.\n\n8 sorcery points: Gain a fly speed of 20 feet.\n\nDancing Tiger: While dancing you can spend up to 6 sorcery points on the following effects:\n\n4 sorcery points: You gain a climb speed of 30 feet.\n\n6 sorcery points: Your unarmed strikes are considered magical and gain the light property.\n\n8 sorcery points: You gain advantage on all dexterity ability checks.\n\n10 sorcery points: You gain resistance to slashing damage.\n\n12 sorcery points: Your movement speed increases by 10 feet.\n\nDancing Monkey: While dancing you can spend up to 6 sorcery points on the following effects:\n\n4 sorcery points: You gain a climb]" time="0.333"><properties><property name="score" value="0.09245077" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[It's hard to imagine a wittier book than one subtitled A Primer on the Tactics of Scientific Research. But, then, David M. Kaplan and Robert M. May are not your ordinary scientists. At one time or another, they've all but single-handedly invented chaos theory, championed the concept of selfish genes, coined the phrase "keystone species," and discovered the homeotic genes responsible for the formation of the vertebrate body plan. For sheer force of intellect, they're among the world's most eminent biologists.\n\nYou might, then, think that there would be little for these geniuses to learn from a primer in scientific methodology. But, as it turns out, that's just not so. In the same style of mordant humor that makes "The Ant and the Peacock" one of the best-selling books on evolutionary biology, Kaplan and May delightfully explain why it's difficult for a scientist to break away from deeply ingrained habits of thought.\n\nThey also introduce the problem of citation errors--a problem that has become all too apparent in the aftermath of The Bell Curve, whose authors committed a blizzard of them, citing everything from studies that were never performed to nonexistent journals. Kaplan and May suggest ways to prevent citation errors and to identify them when they do occur. They reveal that it's possible to fabricate a scientific journal, and to fool people into believing it's real.\n\nBut they don't confine their attention to egregious examples of scientific malfeasance. On the contrary, "The Art of Scientific Research" is written as a series of serious and not-so-serious instructions on how to conduct research, how to get it published, and how to cite it accurately. There's even a section on the art of collaboration, complete with sage advice on how to make it work. "The Art of Scientific Research" is a book for anyone who does science, or wants to.]" time="0.298"><properties><property name="score" value="0.069214545" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.06921455 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.06921455
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Today, in the form of yet another unfortunate casualty of homelessness, a man\u2019s dead body was found on the street just outside of a McDonalds. Just a few hundred meters from the student dorms, where a guy was recently stabbed to death.\n\nI\u2019m really getting sick and tired of living in this city, and I\u2019m beginning to seriously think about moving somewhere else. A friend of mine has been living in Boston for the past 2 years, and he\u2019s constantly telling me how amazing Boston is, and how beautiful it is there.\n\nI\u2019m going to head to Boston for the summer, just so I can get a better idea of what it\u2019s like living there. I\u2019m really starting to lose interest in living here, and I want to try out living somewhere else before I settle on doing so. If Boston is not the place for me, I want to at least have an idea of where I should move.\n\nI do think, however, that Boston might be the place for me, and I\u2019m going to be there for the summer, and maybe even beyond. That is what I\u2019m hoping for at least, but we\u2019ll see how it goes. I think I\u2019m going to take a long trip back to India during this time, as well.\n\nI\u2019m going to try to take a lot of pictures, and post them up here on the blog. I will be a bit busy with work and school and my internship, so I don\u2019t know how much time I will have to do that, but I will do my best.]" time="0.352"><properties><property name="score" value="0.26352748" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Our friends over at Road and Track have the scoop on what will be the new Mustang. You can read the entire article here, but it goes something like this.\n\nFord Mustang will have a larger, more powerful engine with a V8. A V6 will be offered, but as a two-seater.\n\nThe V8 will be a 5.0 liter, not a 3.7, and the V6 will have the same displacement as the current 3.7, but with the variable valve timing engine from the Ecoboost engine.\n\nIt will be called the Mustang GT, and is the car most of us are interested in.\n\nThe rear-drive GT model will be gone, replaced by an all-wheel drive GT.\n\nFord\u2019s CVT will be the only transmission.\n\nTo be honest, I\u2019m disappointed. The Mustang has always been about high performance.\n\nWhat is the reason for the V8 to lose power? Will we even feel the change? It is possible the V6 will make the most horsepower of all Mustang models, while still being smaller than the 5.0.\n\nDoes anyone want an all-wheel drive Mustang? Sure, you could argue that AWD will help with acceleration in the snow, but it\u2019s pretty rare for the Northeast to get that much snow, and I don\u2019t need all-wheel drive for an off-road trip to the Catskills.\n\nThe only reason I would consider buying an all-wheel drive Mustang is for the style. I think it will look very good.\n\nSo what do you guys think? Are you upset like I am, or are you okay with the changes?]" time="0.292"><properties><property name="score" value="0.16126394" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.16126394 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.16126394
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[La Asamblea, organo pol\xedtico m\xe1ximo de la Administraci\xf3n Municipal, ejerce su funcionamiento en dos periodos:\n\na) Asamblea Ordinaria.\n\nb) Asamblea Extraordinaria.\n\nSe encarga de:\n\na) Intervenir en la conformaci\xf3n de las Autoridades de los Organismos Locales, ejerciendo la tutela de la Ley Org\xe1nica del R\xe9gimen Electoral y del Sufragio, Ley Org\xe1nica de los Partidos Pol\xedticos y dem\xe1s leyes y disposiciones aplicables.\n\nb) Establecer los niveles de las remuneraciones mensuales y de prestaciones de los servidores p\xfablicos municipales, por cualquier concepto.\n\nc) Aprobar el Plan Anual de Gobierno Municipal, el Presupuesto Municipal y su Reglamento.\n\nd) Resolver las quejas, reclamos y peticiones de los habitantes de la Municipalidad de Hualqui.\n\ne) Dictar las normas a que debe sujetarse la actividad administrativa del Municipio, en su ordenamiento jur\xeddico interno y en sus relaciones con otras Administraciones P\xfablicas.\n\nf) Elegir a sus integrantes y reglamentar su funcionamiento interno.\n\ng) Autorizar la emisi\xf3n de los t\xedtulos representativos de la deuda p\xfablica municipal.\n\nh) Dictar resoluciones administrativas que no impliquen la creaci\xf3n, modificaci\xf3n o supresi\xf3n de tributos municipales.\n\ni) Establecer el r\xe9gimen general para la designaci\xf3n de personas naturales o jur\xeddicas, como encargadas de la prestaci\xf3n de servicios p\xfablicos municipales, as\xed como el r\xe9gimen de contrataci\xf3n y supervisi\xf3n de dichas personas.\n\nj) Dictar resoluci\xf3n de acuerdo con el contenido de los proyectos de acuerdo presentados por la Contralor\xeda General del Municipio, as\xed como en el caso de la resoluci\xf3n de la auditor\xeda de las cuentas municipales.\n\nk) Dictar resoluciones que contengan las decisiones y pol\xedticas municipales, las cuales sean de trascendencia y sean definitivas, y que deban ser obedecidas por todos los habitantes del Municipio.\n\nl) Autorizar el otorgamiento de exenciones tributarias, por resoluci\xf3n motivada de la misma Asamblea.\n\nm) Dictar las normas sobre las sanciones a los concejales o autoridades de los organismos y empresas municipales que cometan irregularidades en la gesti\xf3n de la Municipalidad.\n\nn) Dictar resoluci\xf3n sobre las sanciones a los servidores p\xfablicos de la Municipalidad.\n\no) Elaborar el proyecto de Ordenanzas Municipales y otros reglamentos administrativos]" time="0.279"><properties><property name="score" value="0.0022160064" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Australian Energy Regulator highlights South Australian electricity network overspend\n\nThe Australian Energy Regulator has released a draft report highlighting the network cost of electricity distribution in South Australia. The report contains the results of an investigation into South Australian electricity distribution costs undertaken by the Australian Energy Regulator (AER).\n\nThe AER\u2019s report found that the electricity distribution networks in South Australia, namely ElectraNet and SA Power Networks, are materially overspending compared to the amount of revenue they receive from consumers.\n\nThe report states that network costs in South Australia have been growing rapidly, due to a range of factors, including but not limited to:\n\nLow and decreasing real term retail revenue\n\nPoor use of time based network costs\n\nTime based revenue regulation\n\nChanging end-user demand for electricity\n\nInvestments in the network that are not supported by regulation.\n\nThe report further states that distribution charges represent around a quarter of the total cost of electricity, and are ultimately passed on to consumers through higher electricity bills. The report notes that the three largest state owned electricity distribution companies (including ElectraNet and SA Power Networks) have all seen rapid increases in their distribution costs since 2013.\n\nThe report recommends that the South Australian Government take action to:\n\nUndertake an urgent review of electricity retail regulation\n\nUndertake an urgent review of the existing regulation of distribution charges\n\nExamine mechanisms to enable local distribution networks to invest in assets that improve reliability for customers, and facilitate the integration of renewable energy into the network\n\nThe report also recommends that the Australian Energy Regulator should seek to work with industry to seek additional reforms to be considered by the Australian Energy Market Commission (AEMC).\n\nThe report is open for submissions and can be found here.\n\nMore information on how energy networks operate and cost can be found here.\n\nSee our website for further information on energy and power regulation.]" time="0.334"><properties><property name="score" value="0.09953839" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.09953839 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.09953839
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A special thanks to all the people who have read this story and have offered me constructive criticism.\n\nA Big Thanks to The Prankster and Sage, also to Herr and themuseforlove for providing such helpful and encouraging critiques.\n\nEnjoy.\n\nHis life had been pretty good lately. The old man had finally started letting him do more things on his own, such as make deals with the city of Chicago.\n\nAt the moment he was in his office getting a briefing from Mr. Fredrickson, his assistant.\n\n"The latest bounty is on something that is causing a lot of damage to the people in the city. It's probably best to explain the damage to you in person," Fredrickson suggested.\n\nThey both headed to the police station. Fredrickson had a theory as to what was causing the damage and had contacted the police.\n\nFredrickson's theory turned out to be correct. It was a monster, and it had been causing a lot of damage and injuries, but they were on the right track to capturing the monster.\n\n"You mean that thing is going to be mine," the old man said when he got word that the monster had been captured.\n\n"Yes sir, we are on our way to get it now," the officer informed him.\n\n"I'll meet you at the stadium," the old man said.\n\n"You want to come to the stadium," Fredrickson asked.\n\n"I do, I want to see this thing," the old man said with a grin.\n\n"Why," Fredrickson asked.\n\n"I just want to see it," the old man answered.\n\nAs the two walked back to the old man's car Fredrickson suggested he do something a little different with the bounty this time.\n\n"This thing is more dangerous than the last two that were captured, why do you want to go see it," Fredrickson inquired.\n\n"Let's just say that I want to make sure that the right person is getting the bounty," the old man answered.\n\n"Fine, I'll call them and tell them to make sure to bring the creature in the arena," Fredrickson said.\n\n"Good, call them now," the old man said.\n\nFredrickson called and told the team that they were bringing in the monster and it was going to be brought into the arena and they had to get the area ready.\n\nAfter the call was made, the old man and Fredrickson drove to the arena.\n\nWhen they got there the old man went to the back area and took off his suit and put on a set of referee's gear.\n\n"You sure you want to do this," Fredrickson asked.\n\n"I'm sure, now go call them and tell them we're ready," the old man ordered.\n\nFredrickson called and then the two waited for the team to show up.\n\nAfter a few minutes the team showed up with the monster in tow.\n\n"It looks mean," Fredrickson said as the team pulled the creature into the arena.\n\n"It does look mean," the old man replied.\n\nAs the two watched the creature in the arena the old man asked a few questions of the men.\n\n"When did it show up here," he asked.\n\n"It came in about six months ago," the leader of the team answered.\n\n"How did you capture it," the old man asked.\n\n"We don't know, we just heard a scream and when we went to check on it, it was already bound up," the leader answered.\n\n"Do you have a picture of what the thing looks like," the old man inquired.\n\n"Yes, we have a picture of it," the leader answered.\n\n"May I see it," the old man asked.\n\nThe leader handed the old man a picture of the creature.\n\n"This doesn't look like the same one," the old man said as he looked at the picture.\n\n"We don't know, maybe this is a different one," the leader suggested.\n\n"This looks more like the picture of the monster I fought a long time ago," the old man said as he handed the picture back.\n\n"It's not the same thing, the one you fought was green and this one is yellow," the leader said.\n\n"Yes, I know what I'm talking about," the old man said.\n\n"If it's not the same thing then why are you concerned," the leader asked.\n\n"This monster could be very dangerous, why haven't you done more research," the old man inquired.\n\n"I don't know," the leader admitted.\n\n"You need to study this thing, do some research and if you can't find anything, then maybe you should move it to another city," the old man suggested.\n\n"I'll talk to my superiors," the leader said.\n\n"Good," the old man replied.\n\n"I'm sure that I can find more information if I can get this one back to my lab," Fredrickson said.\n\n"I'm sure you can," the old man replied.\n\nThe team was about to move the creature into the arena to meet with their local hero when a man walked up and started talking to the leader.\n\nThe old man looked at the man and recognized him as a former wrestler, and a very dangerous one at that.\n\n"Hey, that guy is the one who can beat this monster," the former wrestler said.\n\n"How can you be sure," the leader asked.\n\n"I can beat this monster because I once fought a monster like this one and he defeated it," the former wrestler explained.\n\n"Why don't you do it," the leader suggested.\n\n"Fine, but I want the same money that you were going to give the other guy," the former wrestler requested.\n\n"Okay, let's get this over with," the leader said.\n\n"Yes sir," the former wrestler said.\n\nThe former wrestler walked over to the monster and started talking to it. The monster got angry and threw a punch at him.\n\n"It's angry," Fredrickson said.\n\n"I can see that," the old man replied.\n\n"If he can't beat it, we can always use it," Fredrickson said.\n\n"Let's see what happens," the old man said.\n\nThe former wrestler dodged the punch and was able to get his arms around the creature's neck and was able to pin it to the ground.\n\n"This could be bad," Fredrickson said.\n\n"It's not going to be bad," the old man replied.\n\nThe former wrestler held the creature down and then twisted its head around until it snapped off.\n\n"That's one dangerous man," Fredrickson said.\n\n"He is, let's go talk to him," the old man said.\n\n"Okay," Fredrickson said.\n\nThe two walked over to the former wrestler and talked to him.\n\n"You're good, I want to talk to you," the old man said.\n\n"I'm listening," the former wrestler said.\n\n"What are you doing now," the old man asked.\n\n"I'm working on the docks," the former wrestler answered.\n\n"I have a friend that owns a gym, and I'm sure that I could get him to help you out," the old man suggested.\n\n"If I go to this gym, who will I be fighting," the former wrestler asked.\n\n"That depends on who you think is the right person," the old man answered.\n\n"I know, but how do]" time="0.589"><properties><property name="score" value="0.0041048239" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u201cJurassic World\u201d is going bigger, with bigger stars and a bigger budget.\n\nJ.A. Bayona (\u201cA Monster Calls\u201d) is in final negotiations to direct the sequel to \u201cJurassic World,\u201d the hit dino tentpole that earned $1.67 billion worldwide last summer. Colin Trevorrow and Derek Connolly, who penned the script for \u201cJurassic World,\u201d penned the script for the sequel.\n\nChris Pratt and Bryce Dallas Howard are both expected to return, but not necessarily as the leads. Frank Marshall and Pat Crowley are producing the pic.\n\nWhile Bayona and Trevorrow are considered to be a package, the studio is trying to decide whether to retain Trevorrow as a producer or have Bayona work with an experienced producer. That will likely be decided in the next week, with a new writer possibly coming aboard, but for now Bayona is poised to make his English-language feature directing debut.\n\nPlot details are vague, but sources say the film will follow in the footsteps of 2015\u2019s \u201cJurassic World\u201d in focusing on the next generation of the dino franchise. The follow-up will be produced by Frank Marshall and Patrick Crowley. The movie is set for release on June 22, 2018.\n\nBayona broke out in Hollywood with his 2007 thriller \u201cThe Orphanage,\u201d and directed the ghost story \u201cThe Impossible,\u201d which earned star Naomi Watts an Oscar nomination.\n\nBayona is repped by WME, Anonymous Content and attorney Marielle Tenghe.\n\nDeadline Hollywood first reported the news.]" time="0.302"><properties><property name="score" value="0.000805595" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00080559 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00080559
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Jules "GhostOf" Wang is the jungler for Team Dragon Knights.\n\nBiography\n\nJules \u201cGhostOf\u201d Wang hails from Nanjing, China. He was introduced to League of Legends by a friend in his last year of high school. From the moment he started playing he was hooked on the game and quickly moved into playing professionally.\n\n2015 Preseason\n\nOn November 24, 2014 it was announced that along with Cloud9 Tempest's LCS roster and Nientonsoh, they would be the main team at the new Cloud9 Challenger roster.[1] After that he played in some amateur tournaments along with the rest of the Cloud9 Challenger roster.\n\n2015 Season\n\nAfter playing for Cloud9 Challenger in the NACS Spring Qualifier, GhostOf joined Team Dragon Knights in February, when the team was invited to the Spring Season of NACS. They finished in third place in the regular season, with a 6-4 record. In the playoffs, they lost in the semifinals to eventual tournament winner Renegades, but won the third place match against Cloud9 Tempest to secure a spot in the summer promotion tournament. However, they were unable to advance to the summer split, as they lost to Team 8 in the first round of their promotion match-up.\n\nTeam Dragon Knights competed in the Summer Promotion Tournament, where they lost 3-0 to Team Fusion in the semifinals. The team also lost their placement matches against Team Coast, meaning that they would be playing in the 2016 NACS Spring Season.\n\n2016 Season\n\nAfter winning the NACS Summer Qualifier, Team Dragon Knights qualified for the 2016 NA LCS Spring Season. In the spring season, they posted a 6-12 record in the round robin and did not qualify for playoffs. However, with the disqualification of Renegades (due to visa issues), TDK received the top seed into the Summer Promotion Tournament, where they were eliminated in the first round by Team Dignitas.\n\nTrivia\n\nLoves to watch anime.\n\nTournament Results\n\nInterviews\n\nRedirects\n\nThe following pages redirect here. There are three types of pages that may appear on this list:\n\nNames formerly used by the player in competition\n\nNicknames or alternative spellings or capitalizations of the player's name\n\nCommon typos that are frequently searched for\n\nThe list is generated automatically. To request an addition to the list, you may use this form.\n\n\n\nNo results found]" time="0.281"><properties><property name="score" value="0.05994906" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05994906 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05994906
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[To compare the electrochemistry of a one-step and a two-step biosynthetic pathway, the co-culture of methanogenic archaea and the acetogenic bacterium Butyrivibrio fibrisolvens was examined. Acetate production from glucose in batch culture was investigated, comparing cells from co-culture with pure B. fibrisolvens and pure Methanosarcina barkeri cells. After 22 h, glucose was depleted in pure M. barkeri cultures but acetate production was not complete. After 22 h, glucose was depleted and glucose uptake and acetate production were completely ceased in pure B. fibrisolvens cultures. When cells from the two pure cultures were co-cultured, the cells from M. barkeri appeared dead in the co-culture after approximately 10 h. Cell growth and acetate production occurred in the co-culture, but was lower than the growth rate and the acetate yield in pure B. fibrisolvens cultures. Pure M. barkeri cells grown with pure B. fibrisolvens cells exhibited no growth after 8 h, but some cells were still viable. However, after 18 h all M. barkeri cells were dead and the co-culture was dominated by pure B. fibrisolvens cells. The results indicated that co-culturing of M. barkeri cells with B. fibrisolvens was not an efficient way of acetate production. Acetate production was possible when pure B. fibrisolvens cells were first grown to a certain population and then M. barkeri cells were added. However, complete utilization of glucose was not possible in such co-culture. In this study, the electrode setup was not optimized to detect early anaerobic cells.]" time="0.305"><properties><property name="score" value="1.1745116" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.1745116 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.1745116
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[If your personal philosophy is a little bit Taoist and a little bit Marxist, there's a new place in LA to scratch that particular philosophical itch. Tao Mao is the only East-meets-West neo-communist tiki bar in LA, a three-story Chinatown bordello of poi dogs and palm trees. To get there, you enter from a rear alley and walk past the washboard abs of dancers in the Bumpin' Uglies Go-Go Bar to the karaoke bar called Red 7, and from there climb a red-lit staircase to the restaurant.\n\nTao Mao, "the great origin," is the Chinese name for the Milky Way galaxy, as seen from the Earth. But it's also the name of a star in that galaxy. And in Mandarin, Tao Mao is pronounced "Dow Mao," which sounds like "D.M.A.," or "doctor of philosophy." And that is exactly what Tao Mao is\u2014a tiki bar where all the drinks have the names of philosophers.\n\nYou may be wondering: Is Tao Mao a tiki bar for philosophers? Or a bar for philosophers that serves tiki drinks? Or is it both? Does it matter?\n\nActually, no, it doesn't. Tao Mao is a philosophical tiki bar, that's all you need to know. The more you think about it, the less sense it makes.\n\nBefore I try to explain Tao Mao, I should mention that the bartender told me the bar's name is pronounced "Dow Mao." And he is a white dude. And yet... all the cocktail names are in Mandarin. And he only speaks English. So what the fuck do I know? Maybe I'm the crazy one.\n\nI can tell you that the people who seem most at home at Tao Mao are little clusters of friends\u2014mainly white dudes who look like they'd be hanging out at some over-designed tiki bar that was actually inspired by Tao Mao. For example, I met two TV writers who were there for the first time. The owner was there with his mom. The first time I visited, the woman in the next booth to me was there with her sister, and]" time="0.253"><properties><property name="score" value="0.7393639" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.7393639 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.7393639
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Boeing to Cease Orders for Canadian 737 Max 8\n\nThe sudden grounding of Boeing\u2019s 737 Max aircraft is causing a major disruption to the global airline industry.\n\nThis morning, Canadian plane manufacturer Bombardier announced that it was ending its contract to sell 75 of its CSeries aircraft to the lessor, and parent company of Norwegian Air Shuttle.\n\nAnd now, it has been revealed that U.S. aerospace giant Boeing has cancelled its orders for the Canadian plane, putting a hold on any future deliveries.\n\nThe grounding of the Max model of the aircraft has thrown the airline industry into turmoil. While Boeing does not have a huge presence in Canada, it is estimated that the company has invested $6.4 billion into the country in the last two years alone.\n\nIn a statement, Boeing said it \u201ccancelled a previously announced purchase order for 16 Next-Generation 737-800 passenger aircraft from a U.S. customer and added a new order for 16 Next-Generation 737-900ER passenger aircraft from the same customer.\u201d\n\nIt added, \u201cthis change resulted in a reduction of eight 737-8 MAX deliveries from the previously announced 64 deliveries through 2023.\u201d\n\nWith the order having been cancelled, it is unclear if it will be restored in the future. Boeing said the cancellation of the order was part of its routine actions \u201cin response to market opportunities, customer preferences, and our results in a competitive environment.\u201d\n\nBoeing says it remains committed to its relationship with Canada, but the news comes amid concern over the safety of the aircraft. The model was involved in two deadly crashes in Indonesia and Ethiopia, where 346 people died. The cause of the crashes remains unclear, but both involved issues with the new anti-stall system.\n\nAfter the Ethiopian crash, U.S. President Donald Trump said the plane was \u201ccertainly\u201d unsafe to fly.\n\nFollowing the grounding of the aircraft, Boeing has grounded its 737 Max planes across the globe. In addition, countries and airlines have pulled their planes from the skies.\n\nCanadian airline WestJet has also removed its Max models from its fleet, as did Air Canada and Lufthansa.\n\n\u201cThe decision to temporarily remove our Max 8 fleet from service was made as a precaution and is consistent with actions by regulators around the world, including the FAA,\u201d said WestJet in a statement.\n\n\u201cWhile we have faith in the safety and airworthiness of our Max 8 aircraft, this temporary action is as a precaution while we await the findings from both the FAA and Boeing\u2019s ongoing investigations into the cause of the Ethiopian Airlines Flight 302 crash.\u201d\n\nFeatured Image: Pixabay]" time="0.268"><properties><property name="score" value="0.0006888607" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00068886 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00068886
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Image Credit: Angie B., Albuquerque, NM\n\nPeople feel alone when they don't have a purpose. They feel like they are nothing when they don't have something to do. They feel insecure because they feel like their life doesn't have a meaning. Without these feelings people will feel like they are a nobody. They will feel like their life is worthless. Without a purpose to live for it will be hard for people to be happy and be themselves. When people have no purpose to life they can be so unhappy. These feelings come up in people when they are very upset. People are less likely to be happy when they are alone. With being alone it makes it harder to have fun. Without fun in your life it makes it harder to have a positive attitude. With a positive attitude people will be able to live without fear. They will be able to live like they are in a good mood. With having a good mood people will not be sad and they will feel good about themselves. People will also feel happy when they have a good life. When people feel good about their life it will help people have a positive attitude. They will also be able to have a better life. It will be easier to have a better life without bad feelings. When people have a bad life it will make it harder for them to be happy. This is because their life is not the way they want it. It is very hard for people to be happy when they don't have the life they want. Without having the life they want they will not be happy. People who have a positive attitude will not feel so sad when their life isn't the way they want it. With having a positive attitude people will be able to feel happy. When they are happy it will help them to live a better life. With a better life they will be happier. It will be hard for people to be happy when their life isn't the way they want it. This is because people feel like their life is going wrong. When people feel like their life is going wrong they are less likely to be happy. People who are happy are more likely to be happy. When people are happy they will not be sad. People will not be sad when they are happy. With having a good attitude it will help people be happy. It will also help people to have a good life. People who have a good attitude will feel good about themselves. They will feel good about their life and will have a good life. With a good life they will feel good about themselves. People who feel good about themselves will not feel so sad. This is because they have a good life. They also have good friends. Having good friends will help people be happy. With having good friends people will be happier. People will be happier with good friends. They will also be happier with a good life. With a good life and good friends people will feel happy. It will be hard for people to be happy without a good life. With a good life people will be happier. It will also be hard for people to be happy without good friends. Without good friends people will feel less happy. This is because they have no one to talk to. People with a good life and good friends will feel more happy. It will be easy for people to be happy with a good life and good friends.]" time="0.302"><properties><property name="score" value="0.00064430764" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Court rules out taking blood samples for cell phone surveillance\n\nIn the United States, the Supreme Court ruled out taking blood samples for cell phone surveillance, the second verdict in just a few days.\n\nThe Supreme Court in Washington (USA) ruled that the police is not allowed to search a person's body for a cell phone's location and information.\n\nIt was decided in a 4-to-3 vote. This is the second verdict in a week in which the Supreme Court ruled that blood samples must not be taken from a person arrested for driving under the influence of alcohol.\n\nAccording to the relevant law, the police can take a blood sample for alcohol from an arrested person if there are grounds for suspicion. It also specifies that if a person refuses, they can be forcibly taken.\n\nA man was arrested for driving under the influence of alcohol in 2011. He was ordered to give blood samples. He refused, but the police took the samples forcibly. The court found out that the defendant was under the influence of alcohol. He appealed, but his appeal was rejected in 2012. He then appealed to the Supreme Court.\n\nIn a 4-to-3 vote, the Supreme Court overturned the verdict and ordered the verdict to be re-tried.\n\nIn the meantime, the verdicts are difficult for police. They can't take blood samples from suspects in alcohol-related accidents, nor take blood samples of suspected drug addicts, nor use DNA to find out the suspects in rape cases. They have to be very careful about searching people on the street.\n\nOther websites also commented on the news.]" time="0.262"><properties><property name="score" value="0.12889217" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Another Apple Exec Talks About Bringing Down The Cost Of Macs\n\nOn the heels of some recent remarks by Apple\u2019s Phil Schiller about the company\u2019s view on entry-level pricing, the current vice president of worldwide marketing, Phil Schiller, was quoted today in a Wall Street Journal article about PC prices.\n\nSchiller says that for the sake of keeping PC prices down, the platform needs to avoid fragmentation by maintaining one version of Windows that\u2019s supported by all vendors. \u201cThat helps the consumer know that if I buy a PC in the next six months, it\u2019s going to run that software. That\u2019s good for consumers, and it helps keep prices down,\u201d he told the newspaper.\n\nThose remarks are similar to what Schiller had to say about Apple\u2019s Mac sales earlier this month, when he told analysts during a conference call that the company\u2019s philosophy is to not \u201cgive customers a lot of choices.\u201d\n\nHe also said that Apple has taken a different approach to pricing compared to its competitors. \u201cIt\u2019s like when you go into a restaurant, you know what the food is going to cost. You don\u2019t have to go through five steps of saying I want the steak for this much money, the chicken for this much money, the pasta for this much money.\u201d\n\n\u201cWe\u2019re not trying to segment or isolate ourselves from anybody,\u201d Schiller said. \u201cIt\u2019s more like, if you want a Mac, this is the price. If you want a PC, go over here.\u201d\n\n[Source]]" time="0.316"><properties><property name="score" value="0.004273567" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00427357 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00427357
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[OK, this is all you need to know about this whole "Ryan Fitzpatrick's against the Browns" narrative that is now in full force, after his dismal performance against the Browns last year, and has been growing in fervor ever since news of his re-signing broke last week:\n\nIt's not going to happen again.\n\nYou may not believe it now, and it may not be true on Sunday when the Browns take on the Bucs in their Week 1 matchup. But just like the Browns have a way of winning the games they're supposed to, Fitzpatrick has a way of having performances like he did against the Browns last year.\n\nIt just happens in reverse.\n\nThe defense was ranked 30th in the league in pass defense and would give up more yards in the first quarter than in the entire game the year before, yet it's Fitzpatrick who throws for 5,367 yards and 40 touchdowns that year. That's not a typo. And it's not because he was the quarterback of the future and Josh Gordon was the No. 1 receiver of the future, either. (We'll ignore the fact that the Browns traded for Jason Campbell at the end of the season to play quarterback and traded away Trent Richardson for basically nothing.)\n\nFitzpatrick and the Browns were matched up against each other in the third week of the 2012 season, and by that point in the season Fitzpatrick had thrown for 4,008 yards and 27 touchdowns in just 12 games. He finished the season with an astronomical 8.18 yards per attempt, which was the highest in NFL history. (Since 2001, at least.) He averaged two touchdowns per game for the first three weeks of that season before throwing just five more in the final nine games.\n\nAnd that was in his first season with the Bucs. They acquired him on the last day of August, after he'd spent the last few months being cut and re-signed by the Bills, which was the latest example of the Bills treating him like a starting quarterback without actually starting him. When the Bucs traded for him, it was widely considered a sign that they'd be moving on from Josh Freeman, but Fitzpatrick's job was only to hold the fort. He didn't even start his first game until the Bucs' eighth game of the season.\n\nThis time around, Fitzpatrick is more than holding the fort. The Bucs have put him on the short list of best quarterbacks in the NFL, with his name appearing on every single MVP ballot last year, and after a few years of analysts treating him like a highly replaceable backup, he has emerged as a bonafide starter. And like most No. 1 quarterbacks, he also seems to thrive against certain teams.\n\nIt seems like a good rule of thumb to get out of the way when he's playing his best.\n\nThe Bucs will almost definitely start out slow against the Browns on Sunday, but they're not going to go through another slow start and blow a lead against the Browns for a second time. It just won't happen.\n\nThis is a different year, a different Browns team, and a different quarterback. It's also a different Ryan Fitzpatrick.]" time="0.283"><properties><property name="score" value="0.11429942" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.11429942 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.11429942
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Get daily updates directly to your inbox Subscribe Thank you for subscribing We have more newsletters Show me See our privacy notice Could not subscribe, try again later Invalid Email\n\nSunderland AFC striker Steven Fletcher has had his \xa320,000 Bentley vandalised and stolen, sparking a massive police hunt.\n\nThe \xa345,000 luxury motor, which was parked up outside his home, was spotted being driven away by an offender, believed to be male, wearing a black crash helmet and driving a silver Ford Mondeo.\n\nPolice say it was not a random attack and is being treated as a targeted theft.\n\nThe car has the registration number CN55 ANT and Sunderland AFC can confirm the vehicle belongs to Fletcher.\n\nThe vehicle is a black Bentley Continental GT Speed with blacked out windows.\n\nA spokeswoman for Northumbria Police said: \u201cWe received a report of a car theft in Sunderland on Monday night.\n\n\u201cThe vehicle was parked outside a house and was seen being driven away by a man, who was wearing a black crash helmet.\n\n\u201cThe vehicle was a Bentley Continental GT Speed with blacked out windows.\n\n\u201cThe car had the registration number CN55 ANT.\n\n\u201cThis was not a random incident. It was a targeted theft.\n\n\u201cWe are keen to hear from anyone who has any information about this incident, or who has been offered a similar vehicle for sale.\n\n\u201cWe are particularly keen to hear from anyone who saw the vehicle between 9.30pm and 10pm on Monday night.\u201d\n\nThe theft of Fletcher\u2019s Bentley follows the theft of Sunderland\u2019s team bus in 2008.\n\nThe club\u2019s coach was stolen from outside the Stadium of Light on the evening of the final game of the season against Fulham.\n\nA club spokesman said at the time: \u201cWe\u2019re concerned and disappointed that someone could stoop so low as to steal the team bus and all of the club\u2019s transport plans.\n\n\u201cThis is an act that should shame football fans.\n\n\u201cWe would appeal to whoever stole the bus to think again and drop it back to us.\u201d\n\nAnyone with information is asked to contact Northumbria Police on 101 ext 69191.]" time="0.305"><properties><property name="score" value="0.0015565493" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00155655 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00155655
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Cross-posted at The Huffington Post.\n\nThe recent announcement that, for the first time in three decades, a new strain of avian influenza is spreading from one species to another is concerning but not, as some news outlets have claimed, evidence of a \u201cfatal pandemic in the making.\u201d A strain of H5N1 avian influenza (called H5N1-V) was detected in two apparently healthy wild ducks found in Germany. These ducks, according to the World Health Organization, most likely caught the virus from chickens, because H5N1-V has not previously been detected in wild birds, and H5N1 has not previously been found circulating among wild birds anywhere in the world. The two ducks apparently had not recently come into contact with any chickens. The H5N1-V strain found in the ducks is one of at least 14 genetically distinct H5N1 subtypes. While the H5N1-V strain can infect chickens, it cannot efficiently spread among them or to other species.\n\nH5N1 is an avian influenza virus, meaning that it naturally infects birds. Over the past 14 years, H5N1 has caused at least 555 infections and 282 deaths in humans. While those numbers are higher than any other human infection since influenza was first identified in humans in 1918, they are still a small fraction of the estimated 5 billion to 8 billion birds that have been infected with H5N1 over the past decade. The World Health Organization says that \u201cit is difficult to estimate accurately the number of cases that have gone undetected.\u201d Since the virus has spread to so many different countries, it is likely that many cases have gone undetected. Nevertheless, the case-fatality rate (defined as the percentage of people who die from a given disease) from H5N1 in humans is estimated at 60 percent. It is difficult to compare H5N1\u2019s case-fatality rate to those of other viruses. The case-fatality rate from the H1N1 influenza virus that caused the 1918 influenza pandemic, which killed an estimated 50 million to 100 million people worldwide, was only 2.5 percent, yet that virus killed about 2 percent of the world\u2019s population.\n\nGiven the high death toll, it is important to find the best ways to limit the spread of H5N]" time="0.307"><properties><property name="score" value="0.023710491" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02371049 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02371049
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[As word spread of the new church\u2019s intentions, many Muslims came to have a look. \u201cThey were surprised to see Christians.\u201d\n\nKoberg said he was surprised to see the modest construction was built as quickly as it was.\n\n\u201cWe have enough of everything we need. We have enough food, we have shelter, and there is security. We\u2019ve built what we could,\u201d said Mohammed. \u201cThey are very good, very nice. We\u2019re working together.\u201d\n\nBut Muslim leaders in the area are concerned that the church is being built on a spot where a mosque stood for about 80 years.\n\nEarlier this year, tensions between Christians and Muslims flared up when a Catholic hospital in the nearby city of Bauchi shut down its maternity ward, arguing that the government did not give it enough money to operate. As Muslims felt that the ward\u2019s closing was unfair, they attacked the hospital, which is run by the Italian-based congregation of Daughters of Mary Immaculate.\n\nKoberg said he was surprised that no one has reacted to the construction of the church so far.\n\n\u201cNobody has said anything.\u201d\n\nThe Protestants in Maiduguri had been looking for a new place to worship for months. They are not the only Christians in town, but they are the only ones without a church. Now they can freely worship their God.]" time="0.297"><properties><property name="score" value="0.034441873" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03444187 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03444187
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Bungie has confirmed a new competitive mode for Destiny 2, with a new ranking system and playlists.\n\nFollowing the release of the Curse of Osiris expansion, Destiny 2 will receive some new updates to the Crucible, as well as the addition of private matches for the first time. In a recent blog post on Bungie's website, it was confirmed that Crucible rank is returning to Destiny 2, and that it'll be more straightforward than it was before.\n\n"We believe that to earn your highest rewards, you should be playing the most challenging activities possible for your skill level," the post reads. "With that in mind, we\u2019re making the following changes to the player investment required to reach your highest rank:\n\n- Strike-specific rewards (Medallions, Boots, Class Items, etc.) will no longer be tied to your highest achieved rank\n\n- You will be required to reach a specific rank (HM5) to earn the Nightfall-specific rewards\n\n- You will be required to reach a specific rank (HM5) to earn the Trials of the Nine reward weapons\n\n"In addition to the above changes, we\u2019re also increasing the overall player investment in the Crucible by requiring a minimum Light of 251 to participate in the most challenging endgame activities."\n\nIn the same post, Bungie has confirmed a new ranking system and matchmaking for the Crucible, which will include new playlists.\n\n"To celebrate our launch of private matches and the new matchmaking system, we\u2019re implementing a new system for ranking up in the Crucible. The highest rank you can achieve in Competitive play is now \u201cLegend,\u201d and your Glory will be available to view on our new Competitive playlist HUD. Glory earned in the Competitive playlist will be used to rank up within this new system. We\u2019ll continue to expand on these improvements in the coming months."\n\nIt's interesting that the new rank system is being implemented for just the Competitive playlist, as well as the fact that your Glory is limited to a specific playlist. Hopefully, this doesn't mean there will be no more way to rank up in the Crucible outside of Competitive.\n\nAs part of the changes to the Crucible, Bungie is adding Private Matches to Destiny 2, which will be coming with the Curse of Osiris expansion in December.\n\n"If you\u2019ve played our April Update, you\u2019ve had a taste of what a competitive, matchmade experience can be like in Destiny 2. Now, we\u2019re ready to give you the power to host your own private Crucible matches. This new feature will become available in the next update."\n\nPrivate matches can be played with two to twelve players, and will have matchmaking, as well as private lobbies. There will be a wide range of options available to players, with "full playlist and customization support". Private matches will also come with their own rewards.\n\nPrivate matches will be available to all players who own Destiny 2 and have access to Curse of Osiris. You'll be able to make them as accessible as you like, whether it's making it a full-scale party affair, or something more intimate. Whatever your needs are, we\u2019re looking forward to you showing us what you\u2019re made of in your own custom arenas."\n\nDestiny 2 is available now on Xbox One and PlayStation 4.\n\nSource: Bungie]" time="0.290"><properties><property name="score" value="0.019297436" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01929744 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01929744
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Dear Reader, As you can imagine, more people are reading The Jerusalem Post than ever before. Nevertheless, traditional business models are no longer sustainable and high-quality publications, like ours, are being forced to look for new ways to keep going. Unlike many other news organizations, we have not put up a paywall. We want to keep our journalism open and accessible and be able to keep providing you with news and analyses from the frontlines of Israel, the Middle East and the Jewish World.\n\nThe proposal for a binational state on Israel\u2019s future borders with the Palestinians, put forth by outgoing Prime Minister Ehud Olmert, is no longer an acceptable solution, former Knesset speaker Avraham Burg said Wednesday.\n\n\n\nSpeaking in an interview with Channel 10, Burg said that the proposal, which the Olmert presented last week to Palestinian Authority President Mahmoud Abbas, was \u201cna\xefve and counterproductive.\u201d\n\n\n\n\n\nJPOST VIDEOS THAT MIGHT INTEREST YOU:\n\n\u201cIsraelis don\u2019t want to live in a binational state. One can\u2019t create a state of Jews and Arabs, and not even a state that is a nation of all its citizens,\u201d Burg said. \u201cI don\u2019t see any logic in it, even less so now than five years ago.\u201dThe former Kadima party leader argued that a similar situation exists in Ireland, with the Irish living alongside the English, but not in a single state.Similarly, he said, one could not build a future Palestinian state within the borders of Israel, but one can build a state of all its citizens in the West Bank, Gaza Strip and eastern Jerusalem.If the Israeli government doesn\u2019t agree to this, he warned, the two-state solution is no longer attainable.\u201cWhat we need is an understanding that [an agreement with the Palestinians] will be built on borders and not on a state of all its citizens. We\u2019ll build two states on the 1967 borders, one Jewish and one Palestinian,\u201d Burg said.\u201cIsraelis need to know that [in the future] there will be two states,\u201d he continued. \u201cThe Palestinian people needs to know that [in the future] there will be a Palestinian state.\u201dThe two-state solution is the only way to prevent the State of Israel from becoming the State of the Jewish people, the Knesset speaker warned. \u201cThe future of the State of Israel depends on the existence of two states,\u201d he said.\u201cI\u2019m for a binational state only as a stage, not as a solution,\u201d he added. \u201cIn a binational state, we will never live together, but there will be an agreement. If there\u2019s no agreement, there will be a civil war. We have to prepare for a binational state as a transition stage to the two-state solution.\u201dWhen asked about the present leadership\u2019s decision to allow MK Otniel Schneller (Kadima) to bring a vote of no-confidence in Defense Minister Ehud Barak, Burg accused Barak of \u201centhusiastic nationalism\u201d and of being \u201cna\xefve.\u201d\n\nJoin Jerusalem Post Premium Plus now for just $5 and upgrade your experience with an ads-free website and exclusive content. Click here>>\n\n\n\n]" time="0.296"><properties><property name="score" value="0.0013231566" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00132316 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00132316
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Yet another reason why we love Mary Tyler Moore: The Golden Girl will donate the proceeds of her upcoming appearance on Dancing With the Stars to St. Jude Children's Research Hospital.\n\nMoore's reps confirmed that the donation will come from the profits of Moore's Dancing With the Stars' appearance, in which she and professional dance partner Tristan MacManus perform a cha-cha to Donna Summer's "Hot Stuff."\n\nWatch Mary Tyler Moore's 'Hot Stuff' Dancing With the Stars Performance\n\n"Mary Tyler Moore and her team have been supportive of St. Jude Children's Research Hospital for many years and she will be donating a portion of her proceeds from Dancing with the Stars to support St. Jude," the charity said in a statement to E! News. "Her support is critical to the hospital and we are grateful for her help."\n\nMoore is competing on the show's 12th season with former General Hospital star Ingo Rademacher. Last night, Moore and Rademacher scored the first 10 of the season from judge Len Goodman.\n\nWhile Moore will donate her Dancing With the Stars appearance, some celebrities don't -- even though that's what's requested. They still get a share of the show's profits from voting. Last year, Katie Holmes said she wouldn't do Dancing With the Stars but she still did. She did donate the appearance fee she would have received from the show to the Children's Hospital of Los Angeles.\n\nIn 2010, Jane Seymour donated the proceeds of her Dancing With the Stars appearance to the Cedars-Sinai Medical Center. Also in 2010, season 11 winner Donny Osmond donated his Dancing With the Stars appearance fee to Children's Miracle Network Hospitals.\n\nDancing With the Stars airs Mondays at 8/7c on ABC.]" time="0.365"><properties><property name="score" value="0.016494771" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01649477 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01649477
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[PHILADELPHIA (CBS) \u2013 The 76ers fell to 5-12 overall and 0-5 at home with a 99-94 loss to the Milwaukee Bucks.\n\nThe Bucks outscored the Sixers 22-16 in the fourth quarter to overcome an 18 point deficit.\n\nHollis Thompson led the Sixers with a season high 21 points off the bench.\n\n\u201cI\u2019m happy for him. I think he\u2019s earned the opportunity to get more minutes. I thought he was a pretty complete player tonight, he guarded, he rebounded. I think he\u2019s taking the first step,\u201d Sixers coach Brett Brown said.\n\nThe Sixers held a seven point lead after one quarter but couldn\u2019t hold the momentum.\n\n\u201cWe had such an amazing first quarter. We really put a dent in their defensive scheme,\u201d Brown said.\n\nBucks coach Jason Kidd, who played with the Sixers for a short time, on a night where his team set a franchise record with 14 three pointers made.\n\n\u201cWe were missing a lot early and then the last quarter we really played well and got it going. We were able to put some big points up and get some stops when we needed it,\u201d Kidd said.\n\nMichael Carter-Williams led the Sixers with 19 points and six assists.]" time="0.275"><properties><property name="score" value="0.08012316" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08012316 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08012316
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[...Rather than simple self-help, this book represents what it should be - a collaborative work between the writer and his/her therapist to ensure maximum understanding and success. - Robert M. Corry, M.D., in his review in Psychotherapy\n\n\u2026Clear, practical, and insightful. - Frederick Chapman, M.D., Harvard Medical School\n\nDavid Cohen, M.D. has written a manual on depression that will help many who suffer with this debilitating condition to recognize that there is hope for recovery. More importantly, his description of effective treatments available today is evidence of the tremendous advances in this field. He has done a wonderful job in providing the reader with easy to understand information about depression and how to overcome it. - Daniel J. Vitiello, M.D.\n\nEditorial Board Member, Journal of Affective Disorders\n\n...Presents a wealth of ideas that are written in an easy to read and accessible style. - Library Journal\n\n...From description to treatment, there is something in this book for all readers. - John Guilford, M.D., Clinical Professor of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC\n\n...Dr. Cohen's book is the first on the market to deal in detail with the nonmedical therapies available for the treatment of depression and to be accessible to both patients and their families. It is a valuable contribution to the literature and deserves to be widely read. - E.E. Riley, Ph.D., in his Foreword\n\n...Cohen discusses in simple terms the pathophysiology of depression, the cognitive/behavioral theories of depression, the treatment of depression, and provides information about organizations that may be able to help. The author's descriptions of medications, both antidepressants and anti-anxiety medications, are accurate and detailed. The reader can feel confident that the medication section is accurate, without the endless descriptions found in other books. The key point to remember is that the medications are not the "cure" for depression. Instead, they are used to provide a way of breaking through a "state of learned helplessness" and providing a method to help the patient engage in a treatment program. This is the key point in the book. In order to help those suffering with depression, Dr. Cohen believes that the medical profession has a responsibility to refer patients to a "team" which will help them get over their depression and learn to cope with the problem. This book will give the layperson a much-needed introduction to the field of depression, the various treatments, and how they work. It is written in an easy-to-understand language and provides references for the reader to pursue if the reader wishes to know more about the topic. - Richard H. Price, Ph.D., Past President, Academy of Cognitive Therapy\n\n...All those who are dealing with depression will appreciate this practical guide. It is written in a clear, direct manner. Those who are serious about becoming well will find in Dr. Cohen a knowledgeable and empathic guide. - Rev. Marybeth Twichell, Ph.D.\n\nThe excerpt from the Foreword, "The Practical Guide for Persons With Depression," by Dr. E.E. Riley is reprinted with permission of the author. The excerpt from the Foreword, "A Friend to Help Along the Way," by Dr. Daniel J. Vitiello is reprinted with permission of the author. The excerpt from the Foreword, "The Working Alliance," by Dr. Robert M. Corry is reprinted with permission of the author. The excerpt from the Foreword, "A Different Perspective on Depression," by Dr. John Guilford is reprinted with permission of the author. The excerpt from the Foreword, "Keeping the Ball Rolling," by Dr. Frederick Chapman is reprinted with permission of the author. The excerpt from the Foreword, "A Review of Common Medications," by Dr. Richard H. Price is reprinted with permission of the author. The excerpt from the Foreword, "Excerpts from 'Depression - What Every Clinician Should Know'," by Rev. Marybeth Twichell is reprinted with permission of the author. The excerpt from the Foreword, "Fantastic Resource for Persons Who are Coping with Depression," by Dr. Daniel J. Vitiello is reprinted with permission of the author. The excerpt from the Foreword, "The Treatment of Depression," by Rev. Marybeth Twichell is reprinted with permission of the author. The excerpt from the Foreword, "Dr. Cohen's Story of Success," by Dr. E.E. Riley is reprinted with permission of the author. The excerpt from the Foreword, "Respecting Depression and its Sufferers," by Dr. Robert M. Corry is reprinted with permission of the author. The excerpt from the Foreword, "A New Paradigm of Depression," by Dr. John Guilford is reprinted with permission of the author. The excerpt from the Foreword, "Facing Depression Together," by Dr. Frederick Chapman is reprinted with permission of the author. The excerpt from the Foreword, "Depression: The Last Great Challenge," by Dr. Richard H. Price is reprinted with permission of the author.]" time="0.388"><properties><property name="score" value="0.061329633" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[City workers fill up sandbags for residents after torrential rains on January 21, 2019 in Biloxi, Mississippi. Getty Images\n\nThe storms killed at least six people across the U.S. Gulf Coast.\n\nTropical Storm Barry formed on Thursday evening, and at 11 p.m. ET it was a tropical depression, according to the National Hurricane Center.\n\nBut it's expected to regain strength as it continues to move across the warm waters of the Gulf of Mexico.\n\nThe storm, which has maximum sustained winds of 45 mph, is expected to dump anywhere between 4 to 8 inches of rain across Louisiana and neighboring states.\n\nThe National Hurricane Center issued a hurricane warning for southeastern Louisiana and coastal Mississippi as the storm nears land.\n\nLouisiana Governor John Bel Edwards declared a state of emergency on Thursday.\n\n"We will do all that we can to help people prepare for this storm," Edwards said at a news conference.\n\nHe added: "I urge all Louisianians to remain vigilant and to stay informed on weather conditions and possible storm impacts through the entire weekend."\n\nEdwards warned residents to be prepared for potential road flooding and power outages.\n\nThe Weather Channel reported that flooding from the storm is a concern for a number of towns along the Louisiana coastline, including Lafayette and Morgan City.\n\nThe NHC says that "life-threatening storm surge is likely along portions of the Mississippi and southeastern Louisiana coastlines" as the storm nears landfall on Saturday night.\n\nWeather models have]" time="0.349"><properties><property name="score" value="0.16388403" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.16388403 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.16388403
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[As global oil prices continue to rise, some observers are warning that rising gas prices may cause a major economic downturn in 2008. What's more, the recent natural gas pipeline explosion in California, which prompted a moratorium on new development, will exacerbate the problem.\n\nOver the next five years, the United States will have to import nearly half of the energy it uses, according to the most recent forecast by the U.S. Energy Information Administration. As of now, the United States is the largest energy importer in the world, importing more energy than any other country. We import 3.5 million barrels of oil per day, and more than 80 percent of our oil comes from foreign countries. This puts us at the mercy of OPEC nations, and increasingly Russia, who we are now trying to court to invest in our own energy infrastructure.\n\nThis dependence is a matter of great concern for many energy analysts. Some say that it's time to cut our losses and invest in the most energy-efficient technology possible while we still can.\n\nOur continued dependence on foreign oil could have a long-term impact on the economy, they say, because the price of oil will continue to rise with the demand, and the price of energy could skyrocket in the next decade.\n\n'We Need to Start Thinking Now'\n\n"Energy is not just a topic that's come up in the last few months," says Matthew Ranson, an analyst with the American Council for an Energy-Efficient Economy. "It's been discussed in a serious way for decades now."\n\nAccording to Ranson, for a long time, people weren't really paying attention to energy issues in this country. But then, he says, "the economy collapsed in the last year or so and the [energy] debate started up again in full force."\n\nBut even now, he says, "we need to start thinking about it now. We can't just wait."\n\nThe economy will be hurt most by high energy prices, says Ranson. "Energy, unlike other goods and services, is necessary for people to have jobs and make a living and grow the economy," he says.\n\nThe crisis is already in the works. "Gas prices are expected to increase at the rate of $3 a year," Ranson says. "At some point, it's going to make people reconsider car ownership, which we are seeing already."\n\nOther analysts have noted that the worst economic effects will come in the next few years as oil prices begin to hit consumers' wallets.\n\n"It's really important for people to understand that we don't have to sit around and wait for it to hit us," Ranson says. "We can do things now to change the way we make energy choices."\n\nThe United States needs to cut back on our reliance on oil, he says, and start developing clean, domestic energy resources like solar and wind power.\n\n"We need to think differently about the choices that we're making," he says. "If we have a choice to import oil from places that don't like us, or if we have a choice to invest in clean domestic energy that's good for us, we need to make the choice."\n\nThe Golden Years\n\nRanson admits that it's not going to be easy to move toward a clean energy economy. But there are things that can be done, such as improving efficiency and investing in new energy technologies. "We can't do everything at once," he says.\n\nTo help reduce energy demand, Congress has passed a law to require the federal government to improve energy efficiency in its buildings.\n\nThere are also efforts under way to address the energy crisis in cities, where people can be more dependent on energy, according to Ranson.\n\n"A lot of cities are thinking about this in different ways," he says. "In New York, they're talking about ways to reduce car ownership, like getting people out of cars and into public transportation, making public transportation more convenient, and adding bike paths. You can start with that and see what happens."\n\nThe Natural Gas Supply\n\nAnother important energy issue to keep an eye on is the country's natural gas supply. Natural gas accounts for nearly 20 percent of the country's energy, and nearly 60 percent of the nation's electricity generation.\n\n"We don't really have a clear understanding of how the supply of natural gas will be affected by what's going on in California," says Fred Millar, senior fellow at the Washington-based think tank, Energy Security Initiative.\n\nMillar believes that the California situation may signal "troubles ahead" for the country's natural gas supply. "There are real questions about how much natural gas is going to be produced by the industry in the coming years," he says.\n\nThere's been a dramatic drop in natural gas prices in the last few years, and that has encouraged a lot of companies to start new drilling operations, says Millar. But natural gas prices were going up last week, Millar says, and "the question now is, has the bubble burst?"\n\nA recent explosion at a Southern California natural gas pipeline, which took the lives of two workers, has put a halt to natural gas production in the state. The pipeline was owned by the Texas-based company Sempra Energy, and the blast occurred near Bakersfield. It is still unclear what caused the explosion.\n\nThe blast caused a temporary halt to the development of the Puente Valley Pipeline, a major new pipeline project.\n\nMillar says that the halt on the pipeline will have a major effect on the state's energy supplies. "It could cause a major problem for California's electricity supplies," he says.\n\nMillar adds that the price of natural gas is likely to rise in the coming weeks and months because of the halt.\n\nOil and the Economy\n\nHigh energy prices are also a major concern for economists. "The most immediate effect of a large price increase is inflation," says David Hughes, a geologist who has written extensively on energy issues. "We can expect energy prices to increase for gasoline, electricity, natural gas, and other fossil fuels."\n\nBut economists are still debating how the economy will be affected. Some economists say that higher energy prices could have a positive impact on the economy, while others say the impact could be negative.\n\n"It's too early to tell," says Millar. "We're still in the stage where the price increases are in the process of playing out."\n\n"The economy is more fragile than it was in the 1970s, and energy is more integrated into the economy, and prices are higher," says Ranson.\n\nBut he believes that the economy is better positioned to deal with energy prices now than it was in the 1970s. "I don't think the impact of high energy prices will be nearly as bad this time," he says.\n\nA slowdown in the economy and a possible recession, Ranson says, could cause energy prices to spike even more.\n\nBut even if the economy takes a downturn, Ranson says that energy prices will keep going up. "People may stop spending on some things," he says, "but energy prices are going to keep going up."\n\nRanson says that people will have to make choices about how they live, and the government will have to decide how much of a subsidy it's willing to provide for the alternative energy industry.\n\nHughes believes that, ultimately, high energy prices will bring about some kind of economic crisis. "In my view, this is a symptom of a much bigger problem, which is our oil-based economy," he says. "We can no longer afford the fossil fuel based economy we have had for the past century."\n\nCopyright 2007 E&E Publishing. All Rights Reserved.]" time="0.667"><properties><property name="score" value="0.38877105" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I\u2019m back in Shoreditch and work starts again tomorrow so I\u2019m trying to get things sorted before that. However, this was my second big trip of the year and I\u2019m feeling a bit worn out. It feels like it was longer than a week though.\n\nI went to Seoul with Jess for two weeks. We flew to Seoul Incheon on Cathay Pacific and stayed at the Hyatt in Seoul Station, just outside the hotel station (it was actually our last day before we flew out). We visited the Han River and the Hongdae area (including bars, restaurants and music venues) and went to the Seoul Film Festival. We spent a lot of time walking around too as we don\u2019t really know the city that well and were pretty tired by the end of each day.\n\nWe visited a temple near Cheongdam called Angukdaegyo which was beautiful. We also visited the grounds of the 63 Building which is quite close to the hotel. The following day, we went to Jogyesa Temple which is where the head of the Jogye Order of Korean Buddhism has his residence. We also went to Cheongwadae which is the residence of the President of Korea and the Blue House. I really wanted to go inside the Blue House but it was closed when we were there. The area around the Blue House was really beautiful.\n\nWe had a really nice lunch at the Daehangno area. We had a really nice lunch at the Dongmyo Station near Gyeongbokgung Palace. The area is quite nice. We then went to Insadong where there were lots of small shops. We also visited Namsangol Hanok Village and had a nice lunch at the Hanok Village. It was also near Gyeonghuigung. We walked up the hills near Gyeonghuigung, which were quite steep and also quite a nice walk. We also visited Seoul Tower which was lovely and there was a great view of Seoul.\n\nWe then travelled to Busan for a day to see the Ulsan Bijudong Cable Car and to take the ferry to Geoje Island. Busan was nice and I can definitely see why people live there. There was a great view of the coast from the cable car. There were quite a lot of islands in Geoje Island. We stayed in the Geoje Island Ferry Cruise which is a small hotel. It was very pleasant there and the food was good. We walked around the island and saw the Minho lighthouse. It was quite cloudy so we couldn\u2019t see the islands around. We stayed for dinner and saw the sunset before we returned to Busan.\n\nOur next destination was Jeju Island. We flew from Busan to Jeju Island on a flight that took about 1 hour. There was also a harbour just outside the hotel. We stayed at the Full Moon Hotel. It was quite beautiful. We visited Hallasan Mountain and the Jeju Haenyeo Museum of Women\u2019s Contributions to Life in the Jeju Island in which there was a lovely view of Hallasan Mountain. We also visited Samcheok Beach. We had a great dinner at the Full Moon Hotel in the Samcheok Bay. There was a beautiful view of the moon rising over the beach from our room.\n\nThe next day, we went to Seongsan Ilchulbong Peak, which was very beautiful. It is a volcanic crater on a small island that was completely formed from lava. It was cloudy and rainy while we were there. We went to Seogwipo and had a lovely lunch at Jin Jin Gop. We had a really nice seafood lunch and it was just a couple of minutes away from Seogwipo station. We went to the Seogwipo Lotte Shopping Center and bought some gifts.\n\nWe then went to Hallim Park. It was a very hot day but it was very pleasant there. We went on a cable car to Mount Baekhwa, which was really nice. It is the highest mountain on Jeju Island and the views were nice. We also went to Mokcheongyeon cave and we visited the memorial museum and the huge cave. The cave was really nice and it was a good experience. We then went to Jeju Olle Trail which is a series of pathways that cross Jeju Island. They have been designed to showcase the most beautiful spots on Jeju. We went to the Jeju Olle trail which was near the entrance of Hallim Park. The weather was really nice so it was pleasant to be outside.\n\nWe went to Seongsan Sunrise Peak which was a nice place to see the sunrise. There was a really nice sunset too. The weather was very nice and it was a pleasant place to be. We also went to Mt Sine, which was very pretty. It was a bit foggy and we couldn\u2019t see Mt Halla but it was a nice walk. We also went to the 7 treasures of Jeju which was nice. We then went to Biyang-ri, Seogwipo, which was a bit more rural and very nice.\n\nOur last destination was the Jeju World Cup Stadium. It was a really nice stadium with lots of seating. It had lots of places to eat and drink too.\n\nWe then flew back to Seoul to fly home. It was a lovely place and I can definitely see why people would want to live there.]" time="0.325"><properties><property name="score" value="0.031310197" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In her interview with Popnography, Kate Micucci discussed her two new projects, BoJack Horseman and another animated series on Yahoo! Screen called Other Space. Other Space will be an anthology comedy following the crew of the space shuttle Venturi 2, created by Paul Feig.\n\nOther Space will be the first show I do where the cast is mostly male. I\u2019m a big feminist and I\u2019m not sure how I feel about that, but my character, Natalie, is the only girl on the ship and the youngest, which makes her feel isolated from the rest of the crew. She\u2019s shy and reserved. She\u2019s a huge sci-fi nerd and very book smart but not street smart. She\u2019s obsessed with books and fantasy but there are too many people on the ship and she has a hard time focusing.\n\nKate plays one of the main characters, Natalie, a woman with aspirations of space travel who works on the shuttle, Venturi 2. The series has been compared to an early 90s show called Space Cases, which also takes place on a space shuttle, however, it seems that Other Space will be a little bit more adult and will likely also delve into the science fiction genre as well as the comedy. Micucci will be joined by a great ensemble of actors including The Hunger Games actor, Sam Richardson, as Commander Glen. Richardson and Micucci previously worked together on Saturday Night Live, and Kate shared how much she loves working with him.\n\nI love working with Sam. He\u2019s so wonderful. He\u2019s so cute. I think my character Natalie really brings him out of his shell. She\u2019s the only one who really has the courage to push him. I think she also brings out a really kind, sensitive side in him that he probably doesn\u2019t have a lot of. It\u2019s been a really lovely experience to get to work with him. He\u2019s just a very warm, kind person.\n\nAlso joining the cast are Rebecca Romijn as the ambitious first officer, Kelly, and Enrico Colantoni as Captain Zalian. Other Space will be directed by Joe Russo and will be a half hour comedy show with ten episodes. The show is set to premiere on Yahoo! Screen on April 14, 2015.]" time="0.286"><properties><property name="score" value="0.030943943" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03094394 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03094394
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Der Pr\xe4sident des Verfassungsschutzes, Hans-Georg Maa\xdfen, ist von Bundeskanzlerin Angela Merkel (CDU) entlassen worden. Wie das Bundeskabinett am Mittwoch nach Teilnehmerangaben beschloss, wird Maa\xdfen zum Innen-Staatssekret\xe4r im Bundesinnenministerium bef\xf6rdert. Seine bisherige Stellvertreterin, Pr\xe4sidentin des Bundesamtes f\xfcr Verfassungsschutz (BfV), Susann Wimmer, wird dann seinen Posten als Beh\xf6rdenleiter \xfcbernehmen. Wie die "S\xfcddeutsche Zeitung" berichtet, haben die drei Parteichefs der Gro\xdfen Koalition, Angela Merkel (CDU), Horst Seehofer (CSU) und Andrea Nahles (SPD), die Personalie Maa\xdfen am Dienstagabend einstimmig beschlossen. Merkel habe demnach in einem "Auftragskommando" an die drei Parteichefs auf die schnelle L\xf6sung gedrungen. Im Laufe des Tages soll der Bundestag Maa\xdfen noch abschlie\xdfend \xfcber die Bef\xf6rderung abstimmen.\n\nMaa\xdfen soll dann als Staatssekret\xe4r f\xfcr europ\xe4ische und internationale Aussagen im Bundesinnenministerium eingesetzt werden, wie es am Mittwoch aus Regierungskreisen hie\xdf. Demnach wird er Staatssekret\xe4r f\xfcr die Bereiche Bauen, Wohnen und Energie.\n\nMerkel hatte am Dienstag erkl\xe4rt, die Koalition wolle den Fall Maa\xdfen noch heute abschlie\xdfend kl\xe4ren. Nachdem der Verfassungsschutzpr\xe4sident angeblich Zweifel an den Aussagen des j\xfcdischen Mannes ge\xe4u\xdfert hatte, der in Chemnitz gefilmt worden war, hatte der "Spiegel" berichtet, Maa\xdfen habe die AfD-Spitze in Sachsen gewarnt, eine Einbindung des Verfassungsschutzes in die Aufarbeitung des Chemnitzer T\xf6tungsdeliktes anzustreben. Zudem soll Maa\xdfen im Zusammenhang mit den Vorf\xe4llen in Chemnitz gegen\xfcber der "Bild"-Zeitung gesagt haben, dass ein Video von dem \xdcbergriff auf einen Mann "gef\xe4lscht" sein k\xf6nnte. Die Generalstaatsanwaltschaft Dresden bezeichnete diese Aussagen zu einem angeblichen Fake-Video als "irref\xfchrend".\n\nAm Dienstag hatte der Fall Maa\xdfen bereits f\xfcr Unruhe in der Bundesregierung gesorgt, nachdem das Kabinett offenbar \xfcberraschend \xfcber die Zukunft des Verfassungsschutzpr\xe4sidenten entschieden hatte. Nach Informationen von NDR, WDR und "S\xfcddeutscher Zeitung" sollen SPD-Chefin Nahles und CSU-Chef Seehofer die Entscheidung der Kanzlerin zum sofortigen Rauswurf Maa\xdfens umgehend blockiert haben. Laut Informationen der "S\xfcddeutschen Zeitung" hat Merkel den Koalitionspartnern gegen\xfcber zudem ihren Willen bekr\xe4ftigt, Maa\xdfen als Staatssekret\xe4r in ihrem Kabinett zu halten. Merkel sei ver\xe4rgert gewesen \xfcber die Weigerung der SPD-Parteispitze, den konservativen Kritiker der Migrationspolitik als Staatssekret\xe4r im Innenministerium zu akzeptieren, schreibt die Zeitung unter Berufung auf SPD-Kreise.\n\nMaas: "Irrelevante Debatte"\n\nVor dem Hintergrund der Debatte um Maa\xdfen hat Au\xdfenminister Heiko Maas (SPD) die Bundesregierung aufgefordert, eine "tiefgreifende und un\xfcbersehbare Antwort auf die Herausforderungen der Migration und die Probleme mit der Integration" zu geben. "Es geht nicht um eine Personaldiskussion, sondern um das Schicksal der Demokratie", sagte Maas am Mittwoch in Berlin. Die Debatte \xfcber Maa\xdfen sei nicht nur eine rein parteipolitische, sondern vor allem eine "irrelevante".\n\nDas Verh\xe4ltnis der gro\xdfen Koalition zueinander sei "durch die Vorg\xe4nge in der letzten Woche in keiner Weise verbessert", sagte Maas. "Was wir in den letzten Tagen erlebt haben, ist ein erschreckender Mangel an Selbstverst\xe4ndnis, der manchmal nur noch unterstreicht, wie wenig sich die gro\xdfe Koalition selbst wertsch\xe4tzt." Dass es "in den vergangenen Wochen" dar\xfcber diskutiert worden sei, "ob sich Maa\xdfen noch halten l\xe4sst", k\xf6nne niemanden erfreuen. Die Entscheidung, Maa\xdfen entlassen zu wollen, sei dar\xfcber hinaus von Personaldebatten \xfcberlagert worden.\n\nAufgeregte Stimmen\n\nBei der Debatte zum Haushalt des Bundesinnenministeriums im Bundestag wurde im Anschluss an die Haushaltsrede von Minister Horst Seehofer (CSU) die Stimmung in den Reihen der Regierungsparteien am Mittwoch sehr aufgeregt. Die Opposition im Bundestag sieht in den Spannungen der Koalition \xfcber die Zukunft des Verfassungsschutzpr\xe4sidenten Hans-Georg Maa\xdfen auch ein eigenes Versagen beim Streit.\n\n"F\xfcr das, was hier gerade passiert, tragen Sie alle, die Sie hier sitzen, die politische Verantwortung", sagte die SPD-Fraktionsvorsitzende Andrea Nahles. "Sie tragen daf\xfcr die Verantwortung, dass es in dieser Woche \xfcberhaupt zu einem solchen Haushaltsgesetz kommen kann, wie Sie es hier machen." Nahles forderte Seehofer auf, die Vorg\xe4nge \xfcber Maa\xdfen zu erkl\xe4ren, weil sie sich selbst von der Regierung verraten f\xfchle. "Die Regierung und die politische F\xfchrung dieses Landes muss jetzt den Weg der Einheit beschreiten", forderte sie.\n\nKritik \xfcbte Nahles daran, dass das Bundesinnenministerium bei der Einrichtung von Erstaufnahmeeinrichtungen in Anforderungen an die jeweiligen Bundesl\xe4nder nun "weich" geworden sei. Zudem gebe es zu wenig Pl\xe4tze f\xfcr die Abschiebung abgelehnter Asylbewerber und zu wenig R\xfcckf\xfchrungen nach Afghanistan. Es sei ein "Skandal", dass so viele Menschen in Deutschland festsitzen.\n\nAfD: Maa\xdfen soll Verfassungsschutz-Chef bleiben\n\nDie AfD h\xe4lt dagegen. Fraktionschef Alexander Gauland begr\xfc\xdfte Maa\xdfen als neuen Staatssekret\xe4r im Innenministerium. Er sei \xfcberzeugt, dass Maa\xdfen in der neuen Funktion seine Erfahrungen als Pr\xe4sident des Verfassungsschutzes in die Politik einbringen k\xf6nne, sagte]" time="0.947"><properties><property name="score" value="0.018274187" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Establishing a GitHub Account\n\nLog into your UCSC Gmail account. If you need to create a new UCSC Gmail account, visit this webpage. Once you have logged into your UCSC Gmail account, you can begin the process of creating a GitHub account. Please use your UCSC username as your GitHub username.\n\nTo create a GitHub account:\n\nIn the upper-right corner of the Gmail interface, click the menu icon, then click Settings. On the left side of the settings window, click Accounts and Import. In the lower-left corner of the Accounts and Import window, click Create an account. In the first field, enter your GitHub username. This is your UCSC username. In the second field, enter a GitHub password. This will be your username@github.com email address. In the third field, enter a password for your GitHub account. Please remember to remember this password. This password is only to access your GitHub account from the web. To access your account on your local machine, you will still need to use SSH. In the last field, enter your email address. This will be the email address your collaborators will use to send you commits and other notifications. Click the Sign Up button.\n\nYour UCSC GitHub account will be created. To access your new GitHub account, simply visit GitHub.com and log in with your GitHub username and password.\n\nSet up your GitHub Account\n\nIf you want to allow others to view or contribute to your project, you will need to set up your account to allow this.\n\nTo set up your GitHub account, go to the project you want to contribute to, click on the "Settings" button in the upper right corner of the GitHub page, and under "GitHub profile" click "Edit". In the profile settings, you will see the "Contributions" tab. You can change the settings in this tab to either allow others to contribute to your project or to view your contributions to others' projects. Click on the "Next" button to save your changes.\n\nGitHub provides a detailed guide for the contribution settings here.]" time="0.354"><properties><property name="score" value="0.0327382" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Myanmar currency and coins\n\nMyanmar Banknotes\n\nMyanmar has a local currency, the Kyat, or K, named after King Thibaw, a former king of Burma. The kyat was introduced in 1923, replacing the Indian rupee which had been in use in Burma for about two centuries. One kyat is subdivided into 100 pyas, and one kyat is subdivided into 100 cents. Coins have been minted in denominations of 5, 10, 25, 50, 100, 500 and 1000 kyats, and 1, 5, 10 and 25 pyas, though the highest four denominations are rarely used.\n\nThe coins and notes currently in circulation are:\n\nBanknotes Coins\n\nKyat\n\n50, 100, 500, 1000 Kyat\n\n5, 10, 25, 50, 100, 500 Pyas\n\n1, 5, 10, 25, 50, 100 Cents\n\n50, 100, 500, 1000 Cents\n\n5, 10, 25, 50, 100\n\nCheck out the latest exchange rates!\n\nMyanmar Currency History\n\nDuring the last half of the 19th century, large quantities of Indian coins circulated in Burma. In 1885, Burma began to issue its own coinage, in a new decimal system. The rupee and the double rupee were equivalent to one kyat. These coins were not for circulation outside of Burma and were not legal tender in India. A similar coinage was issued in the last year of the 19th century, using slightly different weights and diameters for the three silver coins and for the copper coins.\n\nDuring World War I, the Burmese Government began issuing a series of paper notes for 1, 5, 10, 20, 100 and 1000 rupees. They were overprinted on banknotes of the Imperial Bank of India, the currency used for exchange in Burma until the mid-1930s.\n\nDuring the 1920s, the paper money of several countries was in circulation in Burma. Since the demand for small denomination notes was greatest, the British Government began to issue India notes in 1925. They were of low denomination, being in the denominations of 5, 10 and 20 rupees. The existing paper money was then demonetised.\n\nIn 1940, the Japanese occupied Burma and issued their own notes in place of the British issues. These notes continued to be in use until 1945, when the British re-established control of the country. In 1942, emergency notes were introduced, in the denominations of 1, 5, 10, 20 and 100 rupees. These notes were overprinted on paper notes issued by the Reserve Bank of India.\n\nIn 1946, a new series of notes was issued in Burma. This consisted of Indian notes issued by the Reserve Bank of India, overprinted B.E.P. and the State Bank of Burma. These were in denominations of 1, 5, 10, 20, 100 and 1000 rupees.\n\nThe present series of notes began in 1951. These notes are in denominations of 1, 5, 10, 20, 50, 100, 500, 1000 and 5000 kyats.\n\nThe "Burmese" rupee, issued by the British between 1885 and 1896, was a fixed exchange rate at 1 shilling 4 pence (two and one-third rupees).\n\nThe U.S. dollar was established as the national currency of Burma in 1885 and is still the predominant currency in use in Myanmar.\n\nBanking in Myanmar\n\nMyanmar has an international banking system, with at least 7 major banks operating there. These include the state-owned Myanmar Foreign Trade Bank (MFTB) and the private Myanmar Economic Bank (MEB), National Bank of Commerce (NBC), Myanma Foreign Trade Bank (MFTB), Myanma Investment and Commercial Bank (MICB), Myanmar Mayflower Bank (MMB), Myanma Ahlia Bank (MAB), and Myanma Security Bank (MSB).\n\nMost commercial banks use the SWIFT system to transfer funds, and many banks in Myanmar accept electronic banking services through mobile phone banking, Internet banking, and ATMs. Some smaller banks still deal only in cash, but since cash is used mainly for larger transactions and shopping, and with so many ATMs in service now, it is no longer a problem.\n\n\n\nMyanmar currency info\n\nMyanmar info\n\nGuide to Myanmar\n\nCurrency information on country homepages]" time="0.351"><properties><property name="score" value="0.0232709" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0232709 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0232709
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This week at Marvel there\u2019s an \u201cArmor Wars\u201d as the New Warriors reunite! Will the Illuminati save our universe from the all-powerful \u201cManhattan Projects\u201d? And that\u2019s just the beginning! The Big 2 also has its second full week of August books, including DC\u2019s \u201cInjustice: Gods Among Us\u201d #11, \u201cTrinity of Sin: Pandora\u201d #3, and \u201cBatman Eternal\u201d #19.\n\nDC has the following this week: \u201cGreen Lantern\u201d #24, \u201cInjustice: Gods Among Us\u201d #11, \u201cThe Flash\u201d #24, \u201cJustice League of America\u201d #9, \u201cBatman and Robin\u201d #24, \u201cDetective Comics\u201d #24, \u201cRed Hood and the Outlaws\u201d #24, \u201cCatwoman\u201d #24, \u201cTeen Titans\u201d #24, \u201cThe Green Team: Teen Trillionaires\u201d #3, \u201cNew 52: Future\u201d #3, \u201cThe Movement\u201d #6, \u201cStormwatch\u201d #24, \u201cHarley Quinn\u201d #7, \u201cHe-Man: The Eternity War\u201d #2, \u201cInjustice: Gods Among Us\u201d #12, \u201cTrinity of Sin: The Phantom Stranger\u201d #19, \u201cSuperman/Wonder Woman\u201d #8, \u201cDeathstroke\u201d #24, \u201cSinestro\u201d #3, \u201cAll-Star Western\u201d #24, \u201cWorlds\u2019 Finest\u201d #19, \u201cThe Multiversity\u201d #1, \u201cBatgirl\u201d #24, \u201cGreen Lantern Corps\u201d #24, \u201cNew Suicide Squad\u201d #9, \u201cEarth 2\u201d #22, \u201cCatwoman\u201d #25, \u201cThe Green Team: Teen Trillionaires\u201d #4, \u201cConstantine\u201d #4, \u201cThe Movement\u201d #7, \u201cJustice League Dark\u201d #24, \u201cGreen Lantern New Guardians\u201d #24, \u201cRed Lanterns\u201d #24, \u201cAquaman\u201d #24, \u201cWonder Woman\u201d #24, \u201cHe-Man: The Eternity War\u201d #3, \u201cBatman \u201966\u201d #12, \u201cAll-Star Western\u201d #25, \u201cAction Comics\u201d #24, \u201cTeen Titans\u201d #25, \u201cCatwoman\u201d #25, \u201cStormwatch\u201d #25, \u201cBatgirl\u201d #25, \u201cAll-Star Western\u201d #26, \u201cHarley Quinn\u201d #8, \u201cDeathstroke\u201d #25, \u201cAquaman\u201d #25, \u201cJustice League 3000\u201d #8, \u201cSupergirl\u201d #24, \u201cSmallville Season 11\u201d #10, \u201cBatman \u201966\u201d #13, \u201cSuperman/Wonder Woman\u201d #9, \u201cSwamp Thing\u201d #24]" time="3.483"><properties><property name="score" value="0.40437907" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[FIG. 1 is a perspective view of a virtual reality system in accordance with a preferred embodiment of the present invention;\n\nFIG. 2 is a top plan view of the virtual reality system of FIG. 1;\n\nFIG. 3 is a front plan view of the virtual reality system of FIG. 1;\n\nFIG. 4 is a side elevational view of the virtual reality system of FIG. 1;\n\nFIG. 5 is a perspective view of a two-handed tracking device in accordance with a preferred embodiment of the present invention;\n\nFIG. 6 is a perspective view of the two-handed tracking device of FIG. 5 with an array of LEDs mounted thereto;\n\nFIG. 7 is a perspective view of a three-dimensional position sensing device in accordance with a preferred embodiment of the present invention;\n\nFIG. 8 is a perspective view of a two-handed tracking device in accordance with another preferred embodiment of the present invention;\n\nFIG. 9 is a perspective view of a three-dimensional position sensing device in accordance with another preferred embodiment of the present invention;\n\nFIG. 10 is a perspective view of a three-dimensional position sensing device in accordance with another preferred embodiment of the present invention;\n\nFIG. 11 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 12 is a top plan view of the virtual reality system of FIG. 11;\n\nFIG. 13 is a front plan view of the virtual reality system of FIG. 11;\n\nFIG. 14 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 15 is a top plan view of the virtual reality system of FIG. 14;\n\nFIG. 16 is a front plan view of the virtual reality system of FIG. 14;\n\nFIG. 17 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 18 is a top plan view of the virtual reality system of FIG. 17;\n\nFIG. 19 is a front plan view of the virtual reality system of FIG. 17;\n\nFIG. 20 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 21 is a top plan view of the virtual reality system of FIG. 20;\n\nFIG. 22 is a front plan view of the virtual reality system of FIG. 20;\n\nFIG. 23 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 24 is a top plan view of the virtual reality system of FIG. 23;\n\nFIG. 25 is a front plan view of the virtual reality system of FIG. 23;\n\nFIG. 26 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 27 is a top plan view of the virtual reality system of FIG. 26;\n\nFIG. 28 is a front plan view of the virtual reality system of FIG. 26;\n\nFIG. 29 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 30 is a top plan view of the virtual reality system of FIG. 29;\n\nFIG. 31 is a front plan view of the virtual reality system of FIG. 29;\n\nFIG. 32 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 33 is a top plan view of the virtual reality system of FIG. 32;\n\nFIG. 34 is a front plan view of the virtual reality system of FIG. 32;\n\nFIG. 35 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 36 is a top plan view of the virtual reality system of FIG. 35;\n\nFIG. 37 is a front plan view of the virtual reality system of FIG. 35;\n\nFIG. 38 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 39 is a top plan view of the virtual reality system of FIG. 38;\n\nFIG. 40 is a front plan view of the virtual reality system of FIG. 38;\n\nFIG. 41 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 42 is a top plan view of the virtual reality system of FIG. 41;\n\nFIG. 43 is a front plan view of the virtual reality system of FIG. 41;\n\nFIG. 44 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 45 is a top plan view of the virtual reality system of FIG. 44;\n\nFIG. 46 is a front plan view of the virtual reality system of FIG. 44;\n\nFIG. 47 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 48 is a top plan view of the virtual reality system of FIG. 47;\n\nFIG. 49 is a front plan view of the virtual reality system of FIG. 47;\n\nFIG. 50 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 51 is a top plan view of the virtual reality system of FIG. 50;\n\nFIG. 52 is a front plan view of the virtual reality system of FIG. 50;\n\nFIG. 53 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 54 is a top plan view of the virtual reality system of FIG. 53;\n\nFIG. 55 is a front plan view of the virtual reality system of FIG. 53;\n\nFIG. 56 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 57 is a top plan view of the virtual reality system of FIG. 56;\n\nFIG. 58 is a front plan view of the virtual reality system of FIG. 56;\n\nFIG. 59 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 60 is a top plan view of the virtual reality system of FIG. 59;\n\nFIG. 61 is a front plan view of the virtual reality system of FIG. 59;\n\nFIG. 62 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 63 is a top plan view of the virtual reality system of FIG. 62;\n\nFIG. 64 is a front plan view of the virtual reality system of FIG. 62;\n\nFIG. 65 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 66 is a top plan view of the virtual reality system of FIG. 65;\n\nFIG. 67 is a front plan view of the virtual reality system of FIG. 65;\n\nFIG. 68 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 69 is a top plan view of the virtual reality system of FIG. 68;\n\nFIG. 70 is a front plan view of the virtual reality system of FIG. 68;\n\nFIG. 71 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 72 is a top plan view of the virtual reality system of FIG. 71;\n\nFIG. 73 is a front plan view of the virtual reality system of FIG. 71;\n\nFIG. 74 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 75 is a top plan view of the virtual reality system of FIG. 74;\n\nFIG. 76 is a front plan view of the virtual reality system of FIG. 74;\n\nFIG. 77 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 78 is a top plan view of the virtual reality system of FIG. 77;\n\nFIG. 79 is a front plan view of the virtual reality system of FIG. 77;\n\nFIG. 80 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 81 is a top plan view of the virtual reality system of FIG. 80;\n\nFIG. 82 is a front plan view of the virtual reality system of FIG. 80;\n\nFIG. 83 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 84 is a top plan view of the virtual reality system of FIG. 83;\n\nFIG. 85 is a front plan view of the virtual reality system of FIG. 83;\n\nFIG. 86 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 87 is a top plan view of the virtual reality system of FIG. 86;\n\nFIG. 88 is a front plan view of the virtual reality system of FIG. 86;\n\nFIG. 89 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 90 is a top plan view of the virtual reality system of FIG. 89;\n\nFIG. 91 is a front plan view of the virtual reality system of FIG. 89;\n\nFIG. 92 is a perspective view of a virtual reality system in accordance with another preferred embodiment of the present invention;\n\nFIG. 93 is a top plan view of the virtual reality system of FIG.]" time="0.768"><properties><property name="score" value="0.00030366504" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[To show their support for Venezuela, five prominent Tibetan Buddhist teachers from the United States will be joining a gathering in Caracas, Venezuela on September 24, 2015. The purpose of this gathering is to support the effort of the Venezuelan people to bring peace and prosperity to the country.\n\nWe will be holding teachings and prayers in three different locations. The first event will be held at 1:30 p.m. at the Cine Teatro Teresa Carreno in Caracas. This venue can seat 900 people. The second and third events will be held at the Jos\xe9 Antonio Paez Theatre, which can seat around 400 people.\n\nIf you are in Venezuela, please attend one of these events. And if you cannot come in person, please join us in spirit by thinking prayers for Venezuela, especially during the times of the teaching and prayers.\n\nThis event is being organized by Geshe Tsultrim Gyeltsen, president of the Foundation for the Preservation of the Mahayana Tradition (FPMT). He will be joined by other FPMT teachers, including Ven. Robina Courtin, Ven. Tenzin Chonyi, Ven. Tsondue Tsomo, and Ven. Marta Meana.\n\nThe event is being supported by the Embassy of the Bolivarian Republic of Venezuela to the United States, and the Embassy of the Bolivarian Republic of Venezuela to the United Nations.]" time="0.314"><properties><property name="score" value="0.17115499" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[more-in\n\nJust ahead of the International Yoga Day on June 21, the Gujarat High Court on Monday observed that the Prime Minister Narendra Modi-led government's decision to declare June 21 as International Yoga Day was against the spirit of the Constitution.\n\nHearing a PIL against the Centre's decision, the High Court said that though there was nothing wrong in promoting yoga, but that should not be at the cost of other forms of physical exercise. The Centre's decision to declare International Yoga Day was against the spirit of Article 51A (h) of the Constitution, which emphasises on the promotion of scientific temper, humanism and the spirit of inquiry and reform.\n\n"We will have to consider various aspects like whether the decision to declare June 21 as International Yoga Day is against the Constitution of India. A decision has to be taken as to whether scientific temper, humanism and spirit of inquiry is being followed by the Centre or not," observed Justice A.J. Desai.\n\nS.P. Tamang, the petitioner, had sought a direction to the Centre to hold scientific discussions before declaring a holiday. The petitioner also questioned the need for declaring June 21 as International Yoga Day and claimed that various festivals and events were already being celebrated by India on the same day.]" time="0.307"><properties><property name="score" value="0.61524624" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Schools\n\n\nThis report focuses on the experiences of LGBT youth in the nation's public and private schools. This report shows that anti-LGBT victimization in school is a serious problem for a large number of students. It also provides data on other forms of bullying and discriminatory treatment that LGBT students experience. Some of the findings of this report are particularly disturbing. For example, over half (53.1 percent) of LGBT students experienced feeling unsafe in school because of their sexual orientation, over one-quarter (26.1 percent) because of their gender expression, and over one-third (35.2 percent) because of both their sexual orientation and gender expression. This harassment and discrimination takes a toll on these students' well-being. The impact of the harassment and discrimination experienced by LGBT students is serious. LGBT students were more likely than non-LGBT students to report several adverse outcomes. For example, they were more likely than non-LGBT students to report high levels of depression (33.1 percent of LGBT students compared to 19.8 percent of non-LGBT students), to have seriously considered attempting suicide (32.2 percent of LGBT students compared to 13.2 percent of non-LGBT students), and to have made a suicide attempt (21.8 percent of LGBT students compared to 4.3 percent of non-LGBT students). Students who were more highly victimized were also more likely to experience these negative outcomes. For example, compared to students who experienced little or no anti-LGBT victimization, students who experienced a great deal of anti-LGBT victimization were more than three times as likely to have been threatened or injured with a weapon on school property (10.0 percent compared to 3.6 percent), more than three times as likely to have been threatened or injured with a weapon off school property (14.7 percent compared to 4.3 percent), more than three times as likely to have experienced school violence (35.2 percent compared to 10.6 percent), more than four times as likely to have attempted suicide (25.0 percent compared to 5.7 percent), and more than six times as likely to have made a suicide attempt that required treatment from a doctor or nurse (10.4 percent compared to 1.8 percent).\n\nIntroduction\n\n\nThis report presents data from the National School Climate Survey (NCS), which collected data from over 7,000 lesbian, gay, bisexual, and transgender (LGBT) students ages 13\u201321 in public and private schools in every state and the District of Columbia during the spring of 2015. The report focuses on the experiences of LGBT students in public schools, but private school students' experiences are briefly discussed to provide context and additional information about the experiences of LGBT students in schools across the country.1 This report also includes a limited analysis of the data on the experiences of bisexual youth. This report provides the first national data on LGBT students' experiences in our nation's schools.\n\n\nLGBT students face a number of serious challenges at school, and this report provides a comprehensive look at the extent of the problem and its impact on LGBT students. Many LGBT students have experienced verbal harassment, physical assault, and sexual violence at school. For example, over half (53.1 percent) of LGBT students have felt unsafe at school because of their sexual orientation, over one-quarter (26.1 percent) because of their gender expression, and over one-third (35.2 percent) because of both their sexual orientation and gender expression. In addition, over one-third (35.2 percent) of LGBT students have been verbally harassed and 19.6 percent have been physically attacked at school in the past year because of their sexual orientation or gender expression. These figures are even higher for transgender students: over half (53.8 percent) have felt unsafe at school because of their gender expression and over one-third (36.2 percent) because of their gender identity. Furthermore, over one-quarter (27.2 percent) of LGBT students have missed at least one entire day of school in the past month because they felt unsafe or uncomfortable, and the prevalence of truancy increases further for transgender students: 40.1 percent of transgender students have missed at least one day of school in the past month because they felt unsafe or uncomfortable.\n\n\nThis report also shows that the harassment and discrimination that LGBT students experience can lead to serious and negative outcomes for these students, including lower school engagement, lower levels of happiness and life satisfaction, and higher levels of depression and even higher levels of suicidal behavior. Over one-third (34.7 percent) of LGBT students reported missing school for at least one day during the month before the survey because they felt unsafe or uncomfortable. Students who experienced more victimization because of their LGBT status were also more likely to report this type of adverse outcome. For example, compared to students who experienced little or no victimization, students who experienced a great deal of victimization were almost four times as likely to have missed at least one day of school in the month before the survey because they felt unsafe or uncomfortable (45.6 percent compared to 12.3 percent).\n\n\nThe negative impact of this victimization on LGBT students can be seen in their reports of lower levels of engagement in school activities, lower levels of happiness and life satisfaction, and higher levels of depression. LGBT students who experienced high levels of victimization because of their sexual orientation, gender expression, or both were more likely than students who experienced low levels of victimization to feel that they could not be themselves at school (68.6 percent compared to 42.2 percent) and to feel unhappy or depressed at school (40.7 percent compared to 19.5 percent). Students who experienced high levels of victimization because of their sexual orientation, gender expression, or both were also more likely to report symptoms of depression than students who experienced low levels of victimization. For example, compared to students who experienced little or no victimization, students who experienced high levels of victimization were almost twice as likely to report feeling unhappy or depressed (38.7 percent compared to 20.2 percent) and almost three times as likely to report feeling less happy than other students (14.3 percent compared to 5.4 percent).\n\n\nData from the 2015 NCS show that many students still face serious and pervasive mistreatment and discrimination at school. These experiences can have a serious negative impact on students' well-being. This is especially true for transgender and gender non-conforming students who are most likely to]" time="0.680"><properties><property name="score" value="0.0367353925" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The band's creative soul and ringleader, Robert Pollard, reflects on the wild success of Guided By Voices as well as his own triumphs and tragedies.\n\nRobert Pollard \u2014 the creative soul and ringleader of Guided By Voices \u2014 is a living embodiment of the enduring power of rock \u2018n\u2019 roll. Pollard, whose band just released its 15th album, August By Cake, has lived a life that\u2019s been as varied as it has been eventful. From crafting classic lo-fi pop records and guiding his beloved group to victory after victory for over two decades, to overcoming multiple tragedies that threatened to undo him, Pollard has endured and endured well.\n\nFrom rock \u2018n\u2019 roll heartbreak to musical triumphs and to the stories of his childhood friends who took their own lives, the tales behind Pollard\u2019s life are as varied as the songs he\u2019s written over the years. They\u2019re full of sweetness, heartache and inspiration \u2014 the kind that only music can provide.\n\nHere, Pollard reflects on the enduring and wonderful power of rock \u2018n\u2019 roll.\n\nOn being inspired by Bob Dylan\n\n\u201cHe made rock \u2018n\u2019 roll feel alive to me, you know? He just did things no one else was doing. The first time I heard his music, I was just in awe of it. I thought he was one of the only people doing something different in music and it really inspired me to make a rock band.\u201d\n\nOn working at Tower Records\n\n\u201cI worked at Tower Records on Sunset Boulevard in the Eighties. I was in a band that was signed to a major label and we were going to go on tour. We were going to make our first big move out to L.A. and the band broke up in Pittsburgh. I was heartbroken. I went to L.A. anyway and got a job at Tower and the band started to do really well in Pittsburgh. I started to realize that I was being a moron by working at a job that didn\u2019t have anything to do with music. I should have been playing music.\n\n\u201cThen, I met people that worked at the store \u2014 people that worked in the music section \u2014 and they were people that were into the same kind of music that I was. They were all very into the new wave thing that was going on at that time and I was very into the punk scene and I was discovering all this underground music. That was a good time because I was discovering so many great bands and all these great people.\u201d\n\nOn putting together Guided By Voices\n\n\u201cI was living in this little house on Cass Avenue in Detroit and I would just record these songs in the basement. I didn\u2019t think anyone would be interested. I just thought I was doing this for myself. Then, people started calling me and saying they wanted to play on the songs and asking if I could make copies of them. Eventually, I had enough to make a record. I was putting the band together around the same time.\n\n\u201cIn the beginning, it was just one song. The whole point was to just have one song on a compilation of different artists from Michigan. That was the point of the whole thing. It was like, \u2018Oh, that\u2019s fun. That\u2019s really fun. Let\u2019s do another song.\u2019 It just became something else. Then, I started working with the other people. The other people were my friends. My friends were just my buddies that I\u2019d played music with. The first couple of years was just me and my buddies doing these songs. Then, it started to become a bigger thing and we started to tour and it became something else. It just turned into something else. It was an accident that it happened.\u201d\n\nOn his songwriting approach\n\n\u201cMy songs have always come from an unconscious, naive place. I really have to focus on a song and work on a song in order for it to have a definite melody or a definite idea. The words, I kind of write more like a novel and I try to write songs that work like a story. When I\u2019m doing them, I\u2019m trying to do it like a movie. I\u2019m trying to think of it in terms of a movie and I\u2019m trying to create characters and set the scenes and tell the story and make it a little bit deeper than what you would normally expect from a pop song. I\u2019m trying to take it to a different level in some ways. That\u2019s always been my goal and that\u2019s always been my style.\n\n\u201cI don\u2019t think I\u2019m trying to reinvent the wheel, I just think that I\u2019m trying to take things that are already in existence and make them bigger and more beautiful and a little more complete. I don\u2019t know. I don\u2019t really try to analyze it that much. I\u2019ve always written songs in the same way and the only thing that\u2019s changed is the way I record them. I used to record them all on a boombox and then, as we went along, we started to get more and more into studio work.\u201d\n\nOn recording songs at home\n\n\u201cI like to record in a place that\u2019s not a studio. I\u2019ve always liked to record in a place where I could have access to as much stuff as possible. I really enjoy it when I have a lot of cool things to play with. I always like to record at home. I think it\u2019s important to make the place you record at like a laboratory, you know? I like to have it be a lab. If I could, I\u2019d have every piece of equipment ever made and be able to put it all in one room and be able to experiment with every sound I could possibly make. It\u2019s so much fun and it\u2019s so much work at the same time, too. I love it.\u201d\n\nOn his songwriting process\n\n\u201cThe way I work, I just keep track of my thoughts and feelings. I think about it when I\u2019m walking or when I\u2019m eating or I\u2019m just doing stuff. I just keep track of stuff and I write down a lot of notes and I try to pay attention to things. My life is so boring, really, you know? I don\u2019t do anything that exciting. I just pay attention to things and I think about stuff and I write down little ideas. I do that all the time. I write little ideas all the time and I just try to remember them and try to put them in a folder.\n\n\u201cIt\u2019s kind of like a filing system. The filing system is in my head. I try to remember everything I think about and I try to write it down and then, eventually, it becomes a song. Then, I try to look at the songs that are done and I try to pick the ones that seem to be the best and start thinking about them in terms of a story or a character or a scenario or something that would be entertaining. I have to think about all the things that are going on in my life and try to piece things together like a collage.\n\n\u201cThen, when it comes to the recording, I\u2019m thinking about the whole thing as a complete package. I\u2019m thinking about the sound of it and I\u2019m thinking about how I\u2019m going to mix the album and everything. I\u2019m thinking about the lyrics and the voice. Everything is kind of part of a bigger thing and the sound and the performance is really important.\u201d\n\nOn keeping it simple\n\n\u201cIt\u2019s easier to write when you\u2019re just keeping it simple. When you start to complicate things, it becomes too big of a thing to think about. That\u2019s when the song becomes too precious and you can\u2019t finish it or you start getting scared of it or something like that. Then, you get caught up in the emotion of it and you can\u2019t do it. You have to remember that it\u2019s just something you\u2019re doing to pass the time. It\u2019s just something you\u2019re doing for fun. That\u2019s what it is for me. It\u2019s just fun. I\u2019m not trying to be any big shot or anything like that. I\u2019m just trying to do something that\u2019s fun and I\u2019m just trying to make something that\u2019s going to give me some satisfaction. I\u2019m just trying to do something that\u2019s going to be fun to listen to and fun to make.\u201d\n\nOn his songwriting being like therapy\n\n\u201cYeah. I\u2019m not trying to be a serious writer or anything like that. I\u2019m not trying to be pretentious at all. I just want to make a record that I\u2019d like to listen to.\u201d\n\nOn the joy of performing\n\n\u201cIt\u2019s a good feeling, you know? There\u2019s something very satisfying about it. You just can\u2019t stop it, you know? I\u2019ve been doing it for so long and it just doesn\u2019t go away. You can\u2019t stop it. I just keep on doing it and I can\u2019t stop it. I think that\u2019s the reason why I do it, you know?\u201d\n\nOn discovering The Beatles\n\n\u201cThe Beatles made]" time="0.660"><properties><property name="score" value="0.172153851" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.17215385 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.17215385
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[CHICAGO (AP) \u2014 An American Airlines pilot has been removed from flying duties after he temporarily parked a plane on a taxiway where four other airliners were waiting to take off at Chicago's O'Hare International Airport.\n\nAn investigation into the Saturday incident is ongoing, airline spokesman Ross Feinstein said Sunday.\n\nFeinstein said the pilot has been taken off flying duty "pending the outcome of the investigation." He didn't specify how long the pilot would be grounded.\n\nNo other crew members were disciplined, and the incident won't affect the scheduling of the roughly 3,000 flights a day the airline operates around the world, Feinstein said.\n\nHe declined to release the name of the pilot or the number of years he had been flying for the airline.\n\nThe Chicago Department of Aviation said in a statement that the pilot of the American Airlines plane, which had arrived from Nashville, Tenn., was supposed to go to a designated taxiway but instead went to a parallel taxiway where four other airliners were waiting for clearance to take off.\n\nIt wasn't immediately clear how close the plane came to taking off.\n\nAccording to radar information cited in the aviation department statement, the aircraft came within 100 feet of an aircraft on the ground and approximately 200 feet from another aircraft.\n\nThe aviation department is investigating the incident along with the Federal Aviation Administration.\n\nAmerican Airlines has endured two crashes this year and five in 2015. Saturday's incident is unlikely to do much to allay the fears of passengers and the traveling public.\n\n"It's obviously one of those things that happen occasionally. It's a pretty serious mistake," said Henry Harteveldt, founder of the Atmosphere Research Group. "It's a reminder that airline pilots are human beings and that despite their extensive training, sometimes they make mistakes."\n\n___\n\nAssociated Press writer Don Babwin contributed to this report.]" time="0.298"><properties><property name="score" value="0.067948416" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.06794842 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.06794842
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[As a manufacturer, it is easy to produce one-of-a-kind pieces, but even easier to make a product for everyone, because every piece is made to the same specifications. What happens when you decide to make a new product and to have a bigger impact? You might think that you have to start with an already existing product and create something new. But this is not always true.\n\nSometimes you need to start from scratch and create something new \u2013 a new form, a new material, new applications or new customer experiences. This is what happened when Ikea created the L\xd6MSK light collection \u2013 a range of products made of plaster and leather, using two materials that we usually associate with other products.\n\nL\xd6MSK: it\xb4s easy being a one-of-a-kind light\n\nTwo elements were the starting point of the L\xd6MSK light collection: an existing material and a very unusual use for it. Plaster and leather are very traditional materials that are linked to very different products. We know plaster for its use in wallpapers, ceilings and sculptures, but it is not very common to use it in products such as lights or furniture. Leather has a much stronger association with leather goods, clothes, bags or shoes. And in fact, leather is one of the most used materials in the furniture industry.\n\nTwo products, plaster and leather, that are very common to different types of industries but never used together.\n\nIkea wanted to combine these two materials in a collection of lights, lamps and other decorative elements, in order to make a complete lighting system that can be easily incorporated into any interior and made more personal.\n\nA creative team started exploring ways of using these two materials in a complete lighting collection. They started experimenting with different elements such as the light bulb and the suspension, to combine them and to make sure they can adapt to the maximum number of situations. The development of the light was not a process of making a more perfect product, but rather a process of exploring new ways of using existing products.\n\nAs a result, they developed three series of products. One made of plaster and leather, and two others made of plaster. The leather light is one of the most surprising elements in the collection, as it is hard to believe that this kind of leather is the same that we see in jackets or shoes.\n\nThe leather used in the light is dyed in different colours in order to add interest to the design and it is used to create the \u201cU\u201d shape that holds the light bulb. This element was designed to be a flexible element in the light, allowing the user to change the direction of the light and adapt it to different uses.\n\nFinally, the leather light can also be suspended with a wire, making it ideal for reading lights.\n\nThe second series, made of plaster, is the plateroom series, and the third series is a collection of lamps made of plaster with different shades. The aim was to use plaster to make different types of lamps that can adapt to the different sizes of space. This is achieved by combining the plaster with different shades and creating elements such as the plateroom bench and the plateroom table, with different dimensions and shades.\n\nThere is an important message that Ikea wants to communicate with this collection: that it is possible to create something new and original.\n\nYou need to start with something simple but at the same time creative and unusual. This is what Ikea wants to achieve with this collection: creating a new product that is easy to understand and appreciate, but at the same time has an innovative design and can be used in different types of interior.\n\nThis can be achieved by starting with a very simple element and having an open mind, as the designers did with this collection. Ikea has created a very unusual product that is adaptable to different situations and can be adapted to any kind of interior or architecture.]" time="0.350"><properties><property name="score" value="0.0032056293" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Jubal Early\n\nJubal Anderson Early (July 14, 1816July 2, 1894) was a Confederate general in the American Civil War and a politician after the war. Although he served almost the entire war in the eastern theater, his most significant contributions were in the Valley Campaigns of 1864, which ended in the stalemate at Petersburg, Virginia, and the capture of the Union garrison at Lynchburg, Virginia. Early is considered among the best Confederate generals who never served in the Army of Northern Virginia.\n\nEarly was born in Southampton County, Virginia, the seventh of ten children of Ruth (Anderson) Early and Judge John Early, a former governor of Virginia and member of the United States Congress. In 1825, Early attended Charlotte Hall Military Academy. He graduated second in his class at the United States Military Academy at West Point in 1838, placing him above such future generals as Stonewall Jackson and Ulysses S. Grant.\n\nEarly was appointed a second lieutenant in the 4th U.S. Artillery. He served as an aide to General Winfield Scott in the War with Mexico and fought in the Battle of Molino del Rey and the Battle of Chapultepec. Early served as the acting chief of artillery in the assault on the city of Mexico, and received two brevets for his bravery in these battles. He was one of the first officers to enter Mexico City, and he served as an artillery instructor at West Point from 1847 to 1852. Early served as a major in the United States Army in the Seminole Wars in 1855, and as a captain in the United States Dragoons in 1858.\n\nEarly entered the Virginia Military Institute in 1852, and became a professor of mathematics at the Institute, where he taught until the Civil War. He was known for his severity as a disciplinarian. Early became known as a superb military tactician and administrator, as well as an able administrator and strategist.\n\nIn 1860, Early entered politics, running as a Democrat for one of the two seats in the Virginia House of Delegates from Southampton County, but he was defeated. The state seceded from the Union on April 17, 1861, and Early was commissioned as a colonel of artillery in the Virginia militia on May 14. When Virginia militia units were activated for Confederate service, Early was appointed a brigadier general of Virginia forces on May 27.\n\nEarly initially commanded a brigade in the brigade of Brig. Gen. Richard B. Garnett. When Garnett died at the Battle of Mill Springs, Early was promoted to brigadier general on January 16, 1862. His brigade was assigned to Maj. Gen. Edmund Kirby Smith's division in the Army of Northern Virginia. Early fought in the Peninsula Campaign, including the Siege of Yorktown, during which his brigade was an important factor in repulsing a Union assault on the right flank of the Confederate entrenchments at Savage's Station. Early received praise for his actions at Hanover Court House.\n\nEarly distinguished himself during the Seven Days Battles. He received his commission as a major in the Confederate Regular Army on June 9, 1862, but was later returned to his previous rank of colonel in the reserves. During the Northern Virginia Campaign, he received plaudits for his actions at the Second Battle of Bull Run.\n\nEarly was promoted to brigadier general in the Confederate regular army on October 11, 1862. He was given command of a brigade in Maj. Gen. Robert E. Rodes's division of A.P. Hill's III Corps. During the Maryland Campaign, Early performed well at the Battle of South Mountain.\n\nDuring the Battle of Fredericksburg, Early was severely wounded in the right thigh and temporarily assigned to administrative duties. He returned to the field in time to defeat Union Maj. Gen. Joseph Hooker's offensive at the Battle of Chancellorsville. At Chancellorsville, Early performed ably in combat and earned praise for his conduct as a brigade commander. Early was sent to western Virginia, where he defeated Union Maj. Gen. William S. Rosecrans at the Battle of Mill Springs. After Chancellorsville, Early was promoted to the permanent rank of brigadier general in the Confederate Regular Army on May 21, 1863, and given command of a division.\n\nEarly fought under Maj. Gen. Thomas J. "Stonewall" Jackson during the Valley Campaigns of 1864. Early's old brigade was reassigned to Maj. Gen. Richard H. Anderson. The Second Battle of Kernstown was his most significant contribution during the Valley Campaigns. Following the Valley Campaigns, Early was assigned to Maj. Gen. John C. Breckinridge's command in the Shenandoah Valley.\n\nHe conducted the Valley Campaigns of 1864. Following Early's victory at the Battle of Lynchburg in June 1864, Early's army became separated by Union Maj. Gen. David Hunter's raid. Hunter's force was driven from the Valley in the Battle of Lynchburg by Early's troops. During the Valley Campaigns, Early defeated Union Maj. Gen. George Crook at the Battle of Rutherford's Farm and the Battle of Tom's Brook, drove Maj. Gen. David Hunter from the Valley in the Second Battle of Kernstown, and defeated Union Maj. Gen. Philip Sheridan at the Third Battle of Winchester.\n\nEarly defeated Union Maj. Gen. David Hunter's Valley Campaign in the Second Battle of Kernstown in July 1864. He then crossed into Maryland and threatened Washington, D.C., forcing Grant to send reinforcements to the capital area. During the subsequent Valley Campaigns of 1864, Early defeated Maj. Gen. Philip Sheridan at the Battle of Opequon, the Third Battle of Winchester, and the Battle of Fisher's Hill. Sheridan's victory at the Battle of Cedar Creek forced Early to retreat back to the Valley.\n\nEarly was assigned to the Department of the West and ordered to reinforce the Confederate Army of Tennessee, but Maj. Gen. John C. Breckinridge convinced him to resist Maj. Gen. William T. Sherman's advance. At the beginning of the Atlanta Campaign, Early was given command of the newly created Third Corps of the Army of Tennessee. During the Battle of Resaca, he launched an unsuccessful assault against a Union fortification on the western bank of the Oostenaula River, suffering heavy casualties. During the subsequent battles of Adairsville and Cassville, his corps attempted to flank Union Maj. Gen. William T. Sherman's left flank, but his subordinates were slow in attacking and failed to coordinate their movements with other Confederate forces. After the Confederates suffered defeat at the Battle of Peachtree Creek, Early retreated with his corps to Lovejoy's Station. He ordered Maj. Gen. Benjamin F. Cheatham's division to open the Battle of Atlanta by attacking the Union force under Maj. Gen. James B. McPherson. Early was in the town of Marietta when he learned that Lt. Gen. John B. Hood was wounded during the Battle of Atlanta, and he returned to Atlanta to take command of the army.\n\nDuring the subsequent Siege of Atlanta, the Army of Tennessee lacked provisions and was forced to withdraw from Atlanta. The army was defeated during the subsequent pursuit, and Early's corps was heavily engaged at the Battle of Ezra Church. In November 1864, the Army of Tennessee was reorganized and Early was given command of the new Second Corps. At the Battle of Franklin, he was killed by a shot through the heart, and his corps suffered significant casualties. The Second Corps was commanded by Maj. Gen. William B. Bate after Early's death. Bate was also wounded and captured, and the corps was virtually destroyed. Bate's capture led to another shakeup of the army's command structure, and Lt. Gen. Alexander P. Stewart assumed command of the Second Corps.\n\nEarly was buried at the Old Methodist Cemetery in Alexandria, Virginia, but the cemetery closed and his remains were moved to Richmond National Cemetery.\n\nThe Virginia Historical Society operates the Jubal Early Memorial Cemetery near New Market, Virginia, where he is buried.\n\nEarly was known as "Old Jubal" to his men and "Fighting Joe" to his friends. Confederate General Robert E. Lee was a friend of Early's, and named his youngest son, Jubal Anderson, after him.\n\nIn the film "Gettysburg", Early was portrayed by actor Martin Sheen. The movie presented Early as a vain, glory-seeking but weak commander who bickered with fellow Confederate generals Joseph E. Johnston and James Longstreet over who was in command of the Army of Tennessee.\n\nHe is also featured in Jeff Shaara's "The Last Full Measure" trilogy, where he is portrayed by Jon Voight.\n\nThe James River Squadron was a Confederate Navy organization during the American Civil War which operated on the James River, Virginia.\n\n\n\n\n]" time="0.643"><properties><property name="score" value="0.5225493513333334" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.52254935 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.52254935
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Colorimetric Detection of Bovine Serum Albumin by Sodium Dodecyl Sulfate-Boronate Affinity Chromatography with Conventional Staining: Optimization by Factorial Design\n\nD. J. Lindstedt, F. C. Hanft, and J. P. Weese\n\nCereal Chemistry\n\nVolume 67(4), 380-383\n\nJune 1990\n\nThe detection of serum albumin in bovine milk by sodium dodecyl sulfate-borate affinity chromatography was investigated with the use of Con A stain. After optimization, it was determined that a total of 6.6 ml of bovine plasma (0.5 mg protein/ml) and 1.2 ml of milk sample were sufficient for the analysis of 0.2 ml of milk. A total of 35 ml of buffer A (20 mM sodium phosphate pH 7.0) containing sodium dodecyl sulfate, boronate, Con A, and 0.5 M sodium sulfate were added to an 8 \xd7 100 mm borosilicate glass column. Bovine plasma and milk samples were passed through the column at a flow rate of 1.5 ml/min. The flow-through was collected and fractions were obtained by passing 1.5 ml of fresh buffer A through the column. Bovine serum albumin was detected in the fractions after staining with the Con A. The mean recovery was 2.78 \xb1 0.01% for bovine plasma and 1.28 \xb1 0.07% for bovine milk.\n\nGo to the article in Cereal Chemistry\n\nKeywords: Milk and dairy products, Bioactive compounds, Animals, Mammals, Bovines, Colostrum, Proteins, Bovine, Dried-milk products, Dairy products, Whole milk, Milk fat, Milk-fat globule membranes, Caseins, Sodium dodecyl sulfate, Serum albumin, Affinity chromatography, Sodium dodecyl sulfate-borate, Concanavalin A stain, Affinity chromatography, Affinity separations, Immobilized enzymes]" time="0.323"><properties><property name="score" value="0.022382112" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02238211 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02238211
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Junior Potchefstroom Boys\n\nBoys' Junior Cup\n\n04 April 2019\n\nGrade: Gauteng North (South)\n\nDivision: Pool A\n\nPool: A\n\nResults\n\nGame 1 (09:30)\n\nPlayStation/Yello Pockets v Athlone (Kingfisher Blue 2)\n\nWin: 3 wickets\n\nAthlone won the toss and elected to field\n\nPlayStation/Yello Pockets - 75/10 in 10 overs\n\nKhawu v Chamuhiya 2 runs\n\nChirag v Alam 8 runs\n\nQalbya v Singh 8 runs\n\nRyan v Daggupan 6 runs\n\nSantlal v Taufik 5 runs\n\nTiaan v Alam 0 runs\n\nScorecard\n\nAthlone - 68/10 in 9.4 overs\n\nAwal v Ryan 16 runs\n\nSeqib v Santlal 4 runs\n\nImran v Qalbya 4 runs\n\nShahir v Chirag 2 runs\n\nMubarak v Kole 2 runs\n\nAhmed v Chamuhiya 4 runs\n\nFarook v Kabbya 5 runs\n\nNadeem v Ahli 6 runs\n\nScorecard\n\nPoints: Athlone 2, PlayStation/Yello Pockets 2\n\nGame 2 (10:15)\n\nClub Greenheights v Kelvin Stars (Kingfisher Blue 1)\n\nWin: 0 wickets\n\nKelvin Stars won the toss and elected to bat\n\nKelvin Stars - 131/6 in 20 overs\n\nAsela v Johnson 7 runs\n\nSmith v Shakoor 5 runs\n\nPaliwal v Hallahan 4 runs\n\nDipoo v Dabhi 4 runs\n\nFernando v Dabhi 3 runs\n\nJo v Rajoo 9 runs\n\nStrydom v Kumar 10 runs\n\nGoswami v Basheer 1 run\n\nScorecard\n\nClub Greenheights - 76/6 in 12 overs\n\nVusumuzi v Smith 16 runs\n\nAubrey v Jo 6 runs\n\nAlen v Fernando 3 runs\n\nChase v Dabhi 3 runs\n\nHaque v Johnson 3 runs\n\nNjoo v Fernando 4 runs\n\nAhmed v Dabhi 1 run\n\nSheehy v Gupta 3 runs\n\nScorecard\n\nPoints: Kelvin Stars 2, Club Greenheights 2\n\nGame 3 (11:00)\n\nClub Greenheights v Athlone (Kingfisher Blue 2)\n\nWin: 3 wickets\n\nAthlone won the toss and elected to bat\n\nAthlone - 90/7 in 10 overs\n\nAwal v Chamuhiya 2 runs\n\nSeqib v Chase 5 runs\n\nAhmed v Njoo 1 run\n\nFarook v Sheehy 0 runs\n\nAhmed v Basheer 3 runs\n\nShahir v Singh 1 run\n\nFernando v Dabhi 2 runs\n\nMubarak v Kumar 0 runs\n\nScorecard\n\nClub Greenheights - 92/3 in 9.2 overs\n\nVusumuzi v Dabhi 9 runs\n\nAubrey v Kumar 7 runs\n\nChase v Seqib 1 run\n\nAhmed v Fernando 3 runs\n\nKeshi v Gupta 5 runs\n\nNjoo v Patel 2 runs\n\nSheehy v Rajoo 3 runs\n\nHaque v Ahmed 1 run\n\nScorecard\n\nPoints: Athlone 2, Club Greenheights 2\n\nGame 4 (12:00)\n\nPlayStation/Yello Pockets v Kelvin Stars (Kingfisher Blue 1)\n\nWin: 3 wickets\n\nKelvin Stars won the toss and elected to bat\n\nKelvin Stars - 72/10 in 10 overs\n\nDabhi v Sheehy 0 runs\n\nSmith v Hasan 5 runs\n\nPaliwal v Rahman 1 run\n\nFernando v Hasan 5 runs\n\nJo v Chase 2 runs\n\nDipoo v Njoo 1 run\n\nDabhi v Shaheed 5 runs\n\nSmith v Shaheed 3 runs\n\nScorecard\n\nPlayStation/Yello Pockets - 76/4 in 8.4 overs\n\nKhawu v Dabhi 10 runs\n\nChamuhiya v Smith 7 runs\n\nAhli v Dabhi 2 runs\n\nRyan v Dipoo 4 runs\n\nSantlal v Shaheed 7 runs\n\nQalbya v Fernando 5 runs\n\nTiaan v Jo 1 run\n\nKole v Fernando 2 runs\n\nScorecard\n\nPoints: Kelvin Stars 2, PlayStation/Yello Pockets 2\n\nGame 5 (13:00)\n\nPlayStation/Yello Pockets v Kelvin Stars (Kingfisher Blue 2)\n\nWin: 0 wickets\n\nKelvin Stars won the toss and elected to bat\n\nKelvin Stars - 95/7 in 10 overs\n\nAhmed v Chamuhiya 0 runs\n\nFarook v Aucho 3 runs\n\nAhmed v Aucho 5 runs\n\nShahir v Chamuhiya 5 runs\n\nFernando v Aucho 2 runs\n\nMubarak v Hasan 5 runs\n\nSmith v Hasan 0 runs\n\nDabhi v Njoo 1 run\n\nScorecard\n\nPlayStation/Yello Pockets - 98/5 in 8.4 overs\n\nKhawu v Ahmed 3 runs\n\nChamuhiya v Farook 7 runs\n\nAhli v Hasan 7 runs\n\nRyan v Shaheed 3 runs\n\nSantlal v Fernando 3 runs\n\nQalbya v Shaheed 7 runs\n\nTiaan v Dabhi 3 runs\n\nKole v Dabhi 3 runs\n\nScorecard\n\nPoints: Kelvin Stars 2, PlayStation/Yello Pockets 2\n\nGame 6 (14:00)\n\nClub Greenheights v Athlone (Kingfisher Blue 2)\n\nWin: 3 wickets\n\nAthlone won the toss and elected to bat\n\nAthlone - 89/9 in 10 overs\n\nAwal v Shaheed 3 runs\n\nAhmed v Dabhi 1 run\n\nShahir v Rajoo 3 runs\n\nFarook v Shaheed 2 runs\n\nAhmed v Patel 3 runs]" time="0.335"><properties><property name="score" value="0.07794613" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Andr\xe9 Le N\xf4tre \u2013 Andr\xe9 Le N\xf4tre, also known as Le N\xf4tre, was a landscape architect, responsible for the design of the gardens of many of the most famous French ch\xe2teaux of the 17th century, including Versailles. He is popularly known as the father of the profession and he was born in Paris, the son of Pierre Le N\xf4tre, a painter of miniatures and Marie Le N\xf4tre. He was trained in his fathers occupation, he did some paintings by the time he was sixteen. He travelled to Italy with Pierre Berchet in 1640, and worked with the architect Jacques Lemercier, from 1646 he was occupied with architectural drawing for the Louvre. He was made a member of the Acad\xe9mie at Mans in 1650, Le N\xf4tres first known landscape project was at the ch\xe2teau of Vaux-le-Vicomte, for his distant relative, Nicolas Fouquet. Here he was more open to the imagination, transforming the plan into a Picturesque and Romantic garden. His work showed a tendency towards the natural and asymmetrical, Le N\xf4tre was unable to visit Italy on account of wars with the Italian states. His influence was limited to parts of the northeast of France, Le N\xf4tres first projects in this style were done for the court of the prince de Cond\xe9. The ch\xe2teau of Chantilly, belonging to the princess of Cond\xe9, Fran\xe7ois, Le N\xf4tre achieved the most at the Ch\xe2teau de Saint-Germain-en-Laye, for Louis XIV and his duc de Bourgogne, later the duc dOrl\xe9ans. Le N\xf4tre created a estate at Marly, and, at the Trianon, for the young Louis XIV. His work transformed the old fort into a palace, more suitable for the residence of the king. He is also responsible for the landscapes of the gardens of the Ch\xe2teau de Maisons and Ch\xe2teau de Saint-Cloud, Le N\xf4tre died in 1681, and was succeeded by his son Jean-Charles Le N\xf4tre, to whom he had taught his encyclopedic style, and his son-in-law Fran\xe7ois Dunan. The design of the gardens of the Ch\xe2teau de Marly was a project of Le N\xf4tres. They were designed to be seen from the top of the terrace, the perspectives and size of the gardens were calculated to surprise the spectators. Le N\xf4tre planned the gardens following the Renaissance principles of regularity, symmetry and he was also responsible for the modifications made to the original plan, done by Charles Le Brun and the gardener Martin Charbonnier, who remade the terrace and the parterres. The final result was the ancestor of modern formal gardens, in 1660 and 1661, Le N\xf4tre built two mansions on the Place Royale in Paris, for the jewellers Louis de Lancy and Balthazar Claquin. In 1664, Le N\xf4tre and Claude Perrault collaborated on a project for the west side of the Louvre. Le N\xf4tres last landscape was the garden around the ch\xe2teau de Sceaux, a project which was incomplete at the time of his death in 1681\n\n9. Gardens of Versailles \u2013 The Gardens of Versailles occupy part of what was once the Domaine royal de Versailles, the royal demesne of the ch\xe2teau of Versailles. Situated to the west of the palace, the gardens cover some 800 hectares of land, in addition to the meticulous manicured lawns, parterres of flowers, and sculptures are the fountains, which are located throughout the garden. Dating from the time of Louis XIV and still using much of the network of hydraulics as was used during the Ancien R\xe9gime. On weekends from spring to early autumn, the administration of the museum sponsors the Grandes Eaux \u2013 spectacles during which all the fountains in the gardens are in full play. In 1979, the gardens along with the ch\xe2teau were inscribed on the UNESCO World Heritage List, one of thirty-one such designations in France. With Louis XIII\u2019s final purchase of lands from Jean-Fran\xe7ois de Gondi in 1632 and his assumption of the role of Versailles in the 1630s. Records indicate that late in the decade Claude Mollet and Hilaire Masson designed the gardens and this early layout, which has survived in the so-called Du Bus plan of c.1662, shows an established topography along which lines of the gardens evolved. This is evidenced in the definition of the main east-west. From this point forward, the expansion of the gardens of Versailles followed the expansions of the ch\xe2teau, accordingly, Louis XIVs building campaigns apply to the gardens as well. At every stage the prescribed tour was managed, under the Sun Kings directions. First building campaign In 1662, minor modifications to the ch\xe2teau were undertaken, existing bosquets and parterres were expanded and new ones created. Most significant among the creations at this time were the Orangerie, the Versailles Orangery, which was designed by Louis Le Vau, was located south of the ch\xe2teau, a situation that took advantage of the natural slope of the hill. It provided an area in which orange trees were kept during the winter months. The Grotte de Th\xe9tys, which was located to the north of the ch\xe2teau, formed part of the iconography of the ch\xe2teau, the grotto would be completed during the second building campaign. By 1664, the gardens had evolved to the point that Louis XIV inaugurated the gardens with the f\xeate galante called Les Plaisirs de l\u2019\xcele Enchant\xe9e. The event, which officially was to celebrate his mother, Anne d\u2019Autriche, guests were regaled with fabulous entertainments in the gardens over a period of one week. As a result of this f\xeate \u2013 particularly the lack of housing for guests, Louis realized the shortcomings of Versailles and began to expand the ch\xe2teau and the gardens once again. With this new phase of construction, the gardens assumed the topographical and iconological design vocabulary that would remain in force until the 18th century. \u201d\n\n10. French language \u2013 French is a Romance language of the Indo-European family. It descended from the Vulgar Latin of the Roman Empire, as did all Romance languages, French has evolved from Gallo-Romance, the spoken Latin in Gaul, and more specifically in Northern Gaul. Its closest relatives are the other langues do\xefl\u2014languages historically spoken in northern France and in southern Belgium, French was also influenced by native Celtic languages of Northern Roman Gaul like Gallia Belgica and by the Frankish language of the post-Roman Frankish invaders. Today, owing to Frances past overseas expansion, there are numerous French-based creole languages, a French-speaking person or nation may be referred to as Francophone in both English and French. French is a language in 29 countries, most of which are members of la francophonie. As of 2015, 40% of the population is in Europe, 35% in sub-Saharan Africa, 15% in North Africa and the Middle East, 8% in the Americas. French is the fourth-most widely spoken mother tongue in the European Union, 1/5 of Europeans who do not have French as a mother tongue speak French as a second language. As a result of French and Belgian colonialism from the 17th and 18th century onward, French was introduced to new territories in the Americas, Africa, most second-language speakers reside in Francophone Africa, in particular Gabon, Algeria, Mauritius, Senegal and Ivory Coast. In 2015, French was estimated to have 77 to 110 million native speakers, approximately 274 million people are able to speak the language. The Organisation internationale de la Francophonie estimates 700 million by 2050, in 2011, Bloomberg Businessweek ranked French the third most useful language for business, after English and Standard Mandarin Chinese. Under the Constitution of France, French has been the language of the Republic since 1992. France mandates the use of French in official government publications, public education except in specific cases, French is one of the four official languages of Switzerland and is spoken in the western part of Switzerland called Romandie, of which Geneva is the largest city. French is the language of about 23% of the Swiss population. French is also a language of Luxembourg, Monaco, and Aosta Valley, while French dialects remain spoken by minorities on the Channel Islands. A plurality of the worlds French-speaking population lives in Africa and this number does not include the people living in non-Francophone African countries who have learned French as a foreign language. Due to the rise of French in Africa, the total French-speaking population worldwide is expected to reach 700 million people in 2050, French is the fastest growing language on the continent. French is mostly a language in Africa, but it has become a first language in some urban areas, such as the region of Abidjan, Ivory Coast and in Libreville. There is not a single African French, but multiple forms that diverged through contact with various indigenous African languages, sub-Saharan Africa is the region where the French language is most likely to expand, because of the expansion of education and rapid population growth\n\n11. Garden \u2013 A garden is a planned space, usually outdoors, set aside for the display, cultivation, and enjoyment of plants and other forms of nature. The garden can incorporate both natural and man-made materials, the most common form today is known as a residential garden, but the term garden has traditionally been a more general one. Zoos,]" time="0.765"><properties><property name="score" value="0.018243998666666667" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.018244 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.018244
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[SINGAPORE - The Central Narcotics Bureau (CNB) said on Monday (June 19) that it had seized more than 80,000 methamphetamine pills worth an estimated street value of more than $3.1 million during two separate operations.\n\nIn a Facebook post on Monday, CNB said that the drugs had been seized at Tuas Checkpoint on May 24.\n\nIn the first operation, CNB officers were deployed at the checkpoint when a Singaporean male traveller was found to be acting suspiciously at about 9.15pm.\n\n"When challenged, the traveller was found to be concealing two plastic packets inside his rectum," CNB said. "Upon further search of his vehicle, officers found an additional three packets containing a total of 40,160 meth tablets hidden inside a sling bag."\n\nCNB officers arrested the 33-year-old man. He has been assessed and found to be mentally sound. He will be charged in court on Tuesday (June 20).\n\nIn a second operation that took place at about 11.45pm that day, CNB officers detected two suspicious-looking men acting suspiciously at a pedestrian walkway near the Customs, Immigration and Quarantine (CIQ) complex.\n\nAfter conducting a search, CNB officers found a total of 17,280 meth tablets hidden in the roof lining of the car.\n\nThe two men, aged 34 and 50, are Singaporeans.\n\n"Investigations are ongoing," CNB said.]" time="0.286"><properties><property name="score" value="0.814592" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Hello there! If you are new here, you might want to subscribe to the RSS feed for updates on this topic.\n\nAurorawe\n\nWith all the police man killings in the news lately it\u2019s a good thing we have the security of a president who is in complete control of his body and doesn\u2019t have to worry about a trigger happy cop.\n\nBenjamin Smith II, 34, shot dead a 34-year-old black man and a 37-year-old Hispanic man on Friday.\n\nA police chief says a gunman had told him he was \u201cupset about Black Lives Matter\u201d, and that he was targeting white people in a series of random shootings that struck fear in the heart of Chicago.\n\nThe gunman killed three people and injured 16 others, all of them apparently chosen at random, before being shot dead by police, according to authorities.\n\nPeople spoke of their terror after the shootings at various sites in the city\u2019s downtown area on Friday evening.\n\nHe shot and killed a man on the street, a train station and a fast food restaurant \u2013 his final two victims were shot in front of a Chicago police station.\n\nThe suspect was identified as a white man in his 30s, according to the Chicago police superintendent, Eddie Johnson, who said he had no information about the gunman\u2019s background.\n\nThe suspect had no criminal record, was known to police only for minor traffic violations and was not on the radar of federal law enforcement, a law enforcement official told Reuters.\n\nPolice found a weapon in the man\u2019s car, Johnson said, adding that a bomb squad had also been called to the scene.\n\nEarlier, Mayor Rahm Emanuel said in a statement: \u201cAny act of violence on a police officer is an attack on our entire community, and requires a swift and thorough investigation.\u201d\n\nWitnesses described scenes of chaos as people scattered for cover after hearing gunshots and watching police run towards the shooter, who they described as a white man.\n\n\u201cI was working, the next thing I know all these people are running and I heard gun shots. I heard at least five,\u201d said Elijah Rodriguez, 17, who works near the shooting scene.\n\nIn the chaos of the moment, a woman, also described as being in her 30s, and a man, were wounded as bystanders rushed to escape the gunfire, Johnson said.\n\nAn officer who arrived at the scene was shot in the head at point blank range, but his vest saved his life, Johnson said.\n\n(click for source)]" time="0.345"><properties><property name="score" value="0.0025570479" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00255705 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00255705
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Still loading...\n\nA B C D E F G H I J K L M N O P Q R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BM BN BO BP BQ BR BS BT BU BV BW BX BY BZ CA CB CC CD CE CF CG CH CI CJ CK CL CM CN CO CP CQ CR CS CT CU CV 1 Eintr\xe4ge bis zum 20.04.2015 \u2013 l\xf6schen bitte bei neuen Eintr\xe4gen 2 Vorname (allg.) Nachname (allg.) Verein / Firma E-Mail-Adresse Anzahl der Tickets/Ausgaben wie viel \u20ac pro Ticket? f\xfcr welche Spiele 3 Tim Wollinger Tim (TIM) Wollinger Kr\xfcger U. Wiesner GmbH u. Co. KG wollinger@krueger-wiesner.de 2 x 1. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 16,00 4 Benedikt Bauck Benedikt Bauck 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 5 Heiko Thelen Heiko Thelen 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 6 Lars Kirchner Lars Kirchner 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 7 Joachim Sch\xf6nfeld Joachim Sch\xf6nfeld 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 8 Ingo Zillmer Ingo Zillmer 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 9 Gunnar Schneider Gunnar Schneider 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 10 Heiko Nitschke Heiko Nitschke 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 11 Sebastian Thomas Sebastian Thomas 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 12 Thomas Arnold Thomas Arnold 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 13 Michael Gr\xe4f Michael Gr\xe4f 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 14 Thomas Lehn Thomas Lehn 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 15 Matthias Wojtalla Matthias Wojtalla 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 16 Max Schaap Max Schaap 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 17 Daniel Senkbeil Daniel Senkbeil 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 18 Mark B\xf6hm Mark B\xf6hm 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 19 Christian Hanusch Christian Hanusch 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 20 Stefan B\xf6lger Stefan B\xf6lger 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 21 Markus Vogl Markus Vogl 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 22 Mario Jankowski Mario Jankowski 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 23 Jens Gredele Jens Gredele 1 x 2. Reihe Stehpl\xe4tze plus Ticket auf allen Heim- und Ausw\xe4rtsspielen im Schnitt 40,00 24 Thomas Kohler Thomas Kohler 1]" time="0.489"><properties><property name="score" value="0.001645384" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Pueblo County and a water provider say they have come to a \u201cmutual understanding\u201d on a controversial decision last month that curbed water supply to a community south of Pueblo.\n\nLast month, the Colorado Springs Water Works announced it would cut water supply to two water districts that buy its water because the Pueblo Reservoir was too low to pump water into the Pueblo County\u2019s Jimmie Creek Reservoir.\n\nThat reservoir, which supplies water to about 20,000 people south of Pueblo, had been on a rotating \u201cwater conservation\u201d restriction for more than a year.\n\nJim May, manager of the CSWW, said the restrictions were intended to help the reservoir fill faster, but the cuts to the districts south of Pueblo appeared to exacerbate the problem.\n\nAfter the announcement last month, residents and water officials in Pueblo and Pueblo County wrote to the state saying they believed the restrictions were discriminatory. They argued that residents in the water districts that purchase the water were being punished for water overuse by residents of Pueblo and Pueblo County, even though they don\u2019t buy the water.\n\nThe Pueblo County commissioners sent a letter to CSWW last month that said, in part: \u201cWe do not consider that the Pueblo Reservoir can be drained without impact to the water service area, and it is our position that this is discriminatory.\u201d\n\nThe commissioners sent another letter Tuesday saying the county is committed to working with the Colorado Springs Water Works on this issue and future water issues.\n\nCSWW agreed to issue a second letter to water districts in Pueblo and Pueblo County clarifying that water would be available.\n\nThe districts that had been receiving water have already begun taking the water again, said Dennis Tenorio, general manager of the Northern Water Users Association. He said the water districts bought a $200,000 storage tank to hold water when there is a shortage.\n\nMay said CSWW has worked with the districts to understand why the Pueblo Reservoir\u2019s level is low and how to address the problem.\n\n\u201cThere\u2019s a huge, huge amount of water being used up there,\u201d May said. \u201cBut, with this mutual understanding, I\u2019m confident we\u2019ll be able to make this a long-term fix for everyone.\u201d\n\nTim Hoover: 303-954-1626, thoover@denverpost.com or twitter.com/timhoover]" time="0.327"><properties><property name="score" value="0.0012163299" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00121633 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00121633
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[BAGHDAD \u2014 Prime Minister Haider al-Abadi on Monday presented a proposed new Cabinet to parliament for approval, which is expected to include a defense minister and an interior minister.\n\nAbadi said in a statement that a number of the ministers would remain in their posts, while some would get new assignments and one would be replaced.\n\nThe move would boost his government\u2019s credibility as it takes on the Islamic State group, which swept across much of northern and western Iraq last summer. It would also help the prime minister gain influence with a parliament elected in April.\n\nLawmakers met Monday afternoon in a closed session to hear from the prime minister and approve the new Cabinet.\n\nIraqi lawmakers already have approved acting ministers in the foreign and defense portfolios in anticipation of a new Cabinet.\n\nThe proposed new defense minister is Khaled al-Obeidi, the chief of staff of the armed forces.\n\nThe candidate for the interior portfolio is Mohammed al-Ghabban, an official in the predominantly Shiite paramilitary forces known as the Popular Mobilization Forces. The forces were created last summer after Iraq\u2019s most powerful Shiite cleric, Grand Ayatollah Ali al-Sistani, issued a fatwa, or religious decree, calling for Iraqis to fight the extremists.\n\nThe new Cabinet members will have to undergo further screening before they can be sworn in.\n\nAn aide to the prime minister told The Associated Press that the interior minister would replace Mohammed Salem al-Ghabban, who has been acting minister since March. The aide spoke on condition of anonymity because he was not authorized to speak to the media.\n\nThe process of forming the Cabinet has been drawn out, with delays because of disputes between Shiite, Sunni and Kurdish blocs over who would hold key posts.\n\nIt was not clear if the interior minister would be a Sunni or a Shiite. It also wasn\u2019t clear if the defense minister would be a Sunni or a Shiite.\n\nWhen the new Cabinet is sworn in, the president will be able to name a new Cabinet as demanded by the constitution, giving him greater leverage in the new legislature.\n\nAbadi, a Shiite, has struggled to overcome his dependence on political parties, some of which receive support from neighboring Iran.\n\nDuring the U.S. occupation, he served as minister of communications under the Shiite-led government of then-Prime Minister Nouri al-Maliki. He was tapped as prime minister last summer after his predecessor was ousted amid an Islamic State offensive that overran about a third of the country.\n\nAbadi promised to unite Iraq, which is divided among Sunnis, Shiites and Kurds, but has struggled to overcome his dependence on political parties, some of which receive support from neighboring Iran.\n\nThe State Department in Washington announced the appointment Monday of Stuart Jones, a career diplomat, as the new U.S. ambassador to Iraq, replacing Douglas Silliman.]" time="0.384"><properties><property name="score" value="0.0010398775" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00103988 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00103988
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[November 11th, 2012\n\nWhile we\u2019re waiting for the official Apple iPod nano 2G Review to come, I wanted to share my review and give you my thoughts. I\u2019ve now had the second generation of the iPod nano for about a week and wanted to give you my thoughts about it.\n\n(Last Updated: Nov 12th, 2012)\n\nThe Physical Design\n\nI think Apple got this design right with the nano. It\u2019s very thin and light, which I like. It\u2019s almost identical to the 1st gen nano, but thinner, and with a larger screen. The big deal for me is that it is so much thinner and smaller than the previous nano. I don\u2019t know why I like that so much, but it does make it so much easier to carry around.\n\nThe Screen\n\nI was initially concerned about the small size of the screen. My fear was that I wouldn\u2019t be able to see the screen as well, or that it would be harder to navigate the menus. I\u2019m very happy to report that the screen size is perfect for what I want. I think the new screen is just large enough to easily navigate menus and change songs.\n\nThe Sound Quality\n\nI was very skeptical about the new sound quality. I don\u2019t have a lot of time to listen to music, and when I do, I usually do it while at the gym. So for me, sound quality is not a huge priority, but I was concerned about it with the new nano.\n\nWell, I am very happy to say that the sound quality is much better than the first generation nano. It is not better than my 4th gen iPod touch, but it is about the same, and sounds really good to me.\n\nThe Battery Life\n\nThe battery life of the new nano is what I was most worried about. The previous nano only got about 5 hours of battery life when playing music, and this is the same battery as the first generation nano. But I was pleasantly surprised by the new nano. It only lasts about 8 hours, but that\u2019s fine for me. My goal is to carry a nano that can give me 8 hours of listening time at the gym. The only time I need longer than that is when I\u2019m traveling for work, and I have my iPhone with me for music.\n\nThe Software\n\nI\u2019m not going to go into too much detail here, but I am very happy with the new software. I think the new interface looks great and I love that I can easily make the album art fit the screen perfectly.\n\nConclusion\n\nOverall, I\u2019m very happy with the new iPod nano 2G. It is the perfect size and weight for me. It sounds good, and the battery life is good enough for me. It\u2019s nice to have an iPod that\u2019s small enough to fit in my pocket.\n\nI would definitely recommend the new iPod nano. If you already have a 1st gen nano, the only reason to upgrade is for the size.\n\nOne thing to keep in mind, is that Apple has said that]" time="0.294"><properties><property name="score" value="0.010525251" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Advanced Biological Warfare (ABW)\n\nThere is an urgent need for "offensive" biological warfare (BW) capability, to complement defensive measures against an attack with biological weapons (BW). Existing defensive measures provide only limited protection against BW, and their usefulness would be significantly reduced in some circumstances. No acceptable defenses have been developed against BW agents.\n\nThis lack of adequate defenses against biological weapons is a major vulnerability in the security of the United States. The increasing danger that biological weapons will be used for hostile purposes poses an urgent need to counter the threat.\n\nModern biological warfare could include development and use of pathogenic organisms and toxins, as well as incapacitating agents. The former might well be the only BW agent of concern because of their potential for causing mass casualties.\n\nThe widespread use of modern technology has increased the availability of biological materials for use as BW agents. Current medical knowledge has increased the potential to create and spread biological weapons. This trend is expected to continue.\n\nEarly development and testing of a pathogenic agent for use in an offensive BW program would not be easily detectable. A biological agent can be disseminated in many ways and to many places with little warning. It is difficult to effectively monitor, detect, and decontaminate a wide area after an attack.\n\nStrategic Offensive Biological Warfare\n\nStrategic offensive BW provides the United States with a major deterrent against potential adversaries. As a deterrent weapon, strategic offensive BW can have a significant impact on the overall military posture of the United States and its potential adversaries. It is in the national interest of the United States to develop a military biological capability to deter an adversary from using biological weapons.\n\nStrategic offensive BW will be used against enemy personnel or facilities to inflict maximum casualties, degrade military capability, or destroy life-sustaining resources or capabilities. In military operations, strategic offensive BW would be used as part of a coordinated effort, in conjunction with other conventional and nuclear forces, and it would require integration of tactical, operational, and strategic capabilities.\n\nStrategic offensive BW could be employed by the United States to complement and support its defensive and non-military (e.g., diplomatic, political, economic, and legal) measures in the event of a biological attack. Its primary purpose would be to minimize the impact of a biological attack on the United States or its forces. Strategic offensive BW may also have applications in countering adversaries that are seeking to develop and maintain a BW capability.\n\nNon-Strategic Offensive Biological Warfare\n\nNon-strategic offensive BW may be employed in support of specific military operations against specific adversary targets. It may also be used in support of other military operations. It would be used to complement and support defensive and non-military measures in the event of a biological attack.\n\nNon-strategic offensive BW would be limited in scope and duration, but it would still be considered offensive because it would result in the infliction of casualties. Non-strategic offensive BW would be used against specific targets, rather than against a large area. It would normally be employed in peacetime as a form of anticipatory self-defense, rather than as a weapon of last resort. Non-strategic offensive BW could be conducted clandestinely to avoid a general war.\n\nThe possession of non-strategic offensive BW capabilities would enhance the deterrent posture of the United States. It would enhance US options to counter biological threats. These options include military action and other non-military actions, which could preclude the need for a military response.\n\nThe National Military Strategy (NMS) endorses non-strategic offensive BW as a credible deterrent to aggression against US interests. The NMS identifies two levels of non-strategic offensive BW for deterrence: A highly credible threat to use BW agents in response to biological attacks or a threat to use BW agents in response to a biological attack. The NMS also identifies a low-level but still credible threat to use BW agents to counter limited biological attacks, sabotage, and hostage-taking.\n\nGlobal Issues\n\nThe US BW program is important to national security and international stability. A fundamental premise of US policy is that offensive BW capabilities are legitimate instruments of national power, especially if the United States is threatened by chemical or biological weapons. The United States has an interest in dissuading the proliferation of BW programs. The development of offensive capabilities by countries without chemical or biological weapons programs or doctrines would be destabilizing and increase the likelihood of their use. The growth of indigenous BW programs in countries with other WMD programs would have similar destabilizing effects.\n\nInternational stability is jeopardized when there is uncertainty as to whether nations will abide by international legal commitments regarding BW. The US BW program is not intended to influence foreign countries, but to demonstrate the US commitment to deter the use of biological weapons and to respond if deterrence fails. BW will be maintained as a credible deterrent, but not one that would have to be used. The United States should make clear its continued intention to pursue an effective BW program to deter adversaries, if necessary.\n\nUS non-strategic offensive BW is an important element of national power and US leadership in arms control. The US BW program plays a crucial role in US leadership in arms control. Non-strategic offensive BW is necessary for full compliance with existing and emerging arms control and non-proliferation agreements. It is important for successful implementation of the CWC, the BWC, and other regional and international agreements. This would prevent the proliferation of BW programs in countries with other WMD programs.\n\nInterdiction\n\nThe inherent characteristics of biological agents make them suitable for clandestine delivery and easy to disseminate. Biological agents could be delivered clandestinely to specific personnel or facilities in areas under control of a potential adversary, without risk to the agents\u2019 handlers.\n\nThe ability of an adversary to clandestinely deliver a biological agent makes the effectiveness of a traditional containment strategy, such as is used in the management of nuclear, chemical, and missile proliferation, problematic. A defensive strategy for biological weapons will have limited utility.\n\nInterdiction of a clandestine BW attack would require significant intelligence resources and considerable time. It would be difficult to find the attacking agent, assess the magnitude of the attack, and identify the source of the attack. If it is found, the agents are difficult to detect and are difficult to destroy. In the unlikely event that a clandestine BW attack were detected and stopped before any damage occurred, the United States would have to consider the political and military implications of conducting an extensive search for the source of the BW attack.\n\nIf an adversary does attempt to use BW, the United States would have to consider the implications of an extensive search for the source of the attack, whether it should be attempted, and what political and military actions might result. US policy is to discourage development of BW programs in countries without other WMD programs, but to take BW programs in friendly countries into account. Therefore, the United States would have to consider how the public and international community would react to the use of US resources to search for a biological attack.\n\nBiological Weapons Control\n\nUnited States policy is to discourage countries from developing and using BW and to discourage the proliferation of BW.\n\nThe United States wants to minimize the risk of WMD proliferation and to prevent or mitigate the harmful consequences of proliferation. Because BW programs are easier to develop and conceal than are nuclear, chemical, and missile programs, US policy is to take appropriate measures to minimize the risk of proliferation of BW. In the case of US friends and allies, it will consider the importance of the BW program to the defense of the country and its overall relations with that country.\n\nBiological weapons could be used in conjunction with nuclear, chemical, or other weapons. This possibility increases the potential threat posed by BW. The United States has concluded that the worldwide prohibition of BW would not eliminate the threat of their use. Although the worldwide elimination of BW is a long-term goal, there is no realistic means to reach it in the foreseeable future. The United States will continue to work toward that goal, but in the meantime it will maintain an effective BW deterrent.\n\nFormal arms control, including international verification of BW programs, would not be sufficient to prevent the clandestine development and use of BW. Biological weapons can be developed and used without a massive infrastructure. Interdiction of clandestine BW programs may not be successful. A country with both BW and chemical weapons programs would be able to attack with biological weapons without any risk of exposure of its chemical weapons program. The United States will seek to work with friendly countries to prevent proliferation of BW.\n\nThe United States would oppose a global ban on the development, possession, or use of BW because it is not a realistic possibility. Such a ban would not eliminate the threat of BW. It would be easy to evade a ban and difficult to enforce.\n\nThe United States will continue to work with the international community to reach an effective and acceptable solution to the BW problem.\n\nTechnical Issues\n\nThe United States does not want to be vulnerable to BW, and it must be able to meet the challenge of a biological attack. However, the US BW program will not be capable of protecting the United States against a chemical or nuclear attack, nor will it be able to protect against all types of biological weapons.\n\nThere is no defense against BW. The United States does not want to be vulnerable to BW. However, if an adversary did use BW, the United States would be willing to use its offensive BW capability to counter it.\n\nThere are no weapons systems or defensive measures capable of protecting against all types of biological warfare. However, a significant deterrent can be developed to dissuade potential adversaries from using BW. This would require BW programs to develop and maintain a viable capability to inflict casualties, degradation of military capability, or destruction of life-sustaining resources or capabilities.\n\nThe likelihood that a biological attack would be effective is low. The impact of biological weapons would be low compared to that of nuclear, chemical]" time="1.024"><properties><property name="score" value="0.04253287333333333" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[University of Notre Dame Australia\n\nThe University of Notre Dame Australia (formerly Notre Dame University) is an Australian Roman Catholic university established in 1989. The main campus is located at the northern end of the Monash Freeway in Craigieburn, 25 kilometres north-west of the Melbourne central business district in Victoria, Australia. The university has approximately 1,800 students.\n\nNotre Dame Australia is a tertiary institution of the Congregation of Holy Cross, a religious community of priests and brothers founded in 1837 in Le Mans, France by Father Pierre Coudrin. The Congregation of Holy Cross was formally recognised by Pope Leo XIII in 1885. In Australia the Congregation of Holy Cross established the predecessor of Notre Dame University, the Holy Cross College, at Box Hill, Victoria in 1951. Holy Cross College was incorporated as a company in 1978 and was approved by the Victorian Government as a Catholic University College in 1981.\n\nIn January 1989 the Holy Cross College and the St. Columba's Church in Bulla moved to new premises in Craigieburn. At that time the college was renamed as the Notre Dame Institute of the Arts and the College of Commerce, Science and Technology.\n\nIn 1991 the Notre Dame Institute of the Arts, the Notre Dame Institute of the Arts (Interim), the College of Commerce, Science and Technology and the Holy Cross Seminary amalgamated to become a university college.\n\nIn 1994 the Notre Dame College of Education and the College of Science amalgamated to become the Notre Dame College of Education and Science.\n\nIn 1996 the Notre Dame Institute of the Arts was amalgamated with the College of Education and Science.\n\nIn 1997 the University of Notre Dame Australia was formally established.\n\nIn 2003 the university changed its name from the University of Notre Dame Australia to Notre Dame University Australia. The change in name reflected the development of the university's research and postgraduate research and development capabilities.\n\nIn 2005 the university changed its name back to the University of Notre Dame Australia.\n\nThe university's crest was designed by Michael Malone of Pentagram, Melbourne, and is based on the "Cross of the Holy Spirit", which was designed by Leonard McCoy of the University of Notre Dame, in the United States.\n\nIn 2006 Notre Dame became the first university in Australia to gain ISO 14001 certification for its environmental management systems.\n\nIn 2008 the University of Notre Dame Australia took part in the international Interfaith Center of Beijing and in the International Symposium on the contribution of religions to sustainable development, held at Shandong University in Jinan, Shandong Province, China.\n\nThe University of Notre Dame Australia has two major sites: the Craigieburn campus and the Werribee Park campus.\n\nCraigieburn campus\n\nThe Craigieburn campus, located at the northern end of the Monash Freeway, houses the Schools of Architecture, Business, Communication and Social Sciences, Education, Health, Humanities and Law, Music, Science and Sport. The campus is also home to the University's administration and a student village.\n\nWerribee Park campus\n\nThe Werribee Park campus is home to the School of Education and Social Work. The campus is also the site of the University's Sport Centre.\n\nUniversity library\n\nThe University of Notre Dame Australia Library holds over 43,000 print volumes and over 2,000 CD-ROMs. The collection covers theology, philosophy, the arts, social sciences and sciences.\n\nThe library's periodical collection contains more than 15,000 current serials including complete runs of the major theological journals. It also holds more than 2,000 current audiovisual titles, 2,000 electronic books and 3,000 electronic journal articles. The library is fully networked to connect to the Internet and to link with all parts of the University, and all staff and students have access to its facilities. The library is a member of the Council of Regional Libraries in Victoria (CRLV) and of the National Library of Australia's Research Collections Network (RCLN).\n\nThe library also houses the university's Special Collections and the Archives, including the history of the Congregation of Holy Cross in Australia, Ireland, the United Kingdom and the United States, the history of the Holy Cross College (now the University of Notre Dame Australia), and personal papers of members of the Congregation of Holy Cross and its educational institutions. The Archives are open to the public.\n\nResearch centres and institutes\n\nThe university has research centres and institutes including the Australian Institute for Bioengineering and Nanotechnology (AIBN), the Australian Institute of Music, the National Institute for Education Development (NIEd), the Australian Institute for Indigenous Development, and the Aloysius JinEndean Lidcombe Catholic Library.\n\nThe university also has research alliances with other universities and institutions.\n\nIn 2011, the University of Notre Dame Australia was awarded the \u201cVice-Chancellor\u2019s Award for Excellence in Corporate Reporting\u201d by the Australasian Centre for Corporate Responsibility. In the same year the University of Notre Dame Australia received the second highest score in the Excellence in Learning category in the Australian Government's Excellence in Higher Education Award, a system for measuring and benchmarking universities in Australia.\n\nThe University of Notre Dame Australia has an undergraduate intake of around 1,500 students and an average intake of about 200 new postgraduate students a year.\n\nIn 2006 the University of Notre Dame Australia began offering graduate certificates and diplomas.\n\nIn 2011 the university introduced a new academic program that allowed its students to study in the United States of America.\n\nThe university has two residential colleges, Cormac and St. Brigid's.\n\nCormac College was opened in 2000, replacing the college that existed in the Werribee Park campus from 1997 to 2000. The College's name is derived from Cormac MacCarthy, the first Bishop of Melbourne, who was a brother of the Congregation of Holy Cross. The College was founded by the Rev. Brian Finn SC, a brother of the Congregation.\n\nSt. Brigid's College was opened in 2001. The College is named after St. Brigid of Kildare, who is the Patron Saint of Ireland. The College was founded by the Rev. Brian Finn SC, a brother of the Congregation.\n\nSt Brigid's and Cormac College form a community known as Cormac Brigid's. Students in the colleges form their own representative councils.\n\nThe University of Notre Dame Australia is a private university with four schools and one institute:\n\n\nThe university is governed by a board of governors, with the Bishop of the Diocese of Sandhurst as the president of the university.\n\n\n\n]" time="0.636"><properties><property name="score" value="0.36714154" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.36714154 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.36714154
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Bunny boiler\n\nA bunny boiler (sometimes bunny-boiler) is a person who is obsessed with another person to the point of stalking, harassment, or violence. It was popularised by a number of films in the 1990s including "Fatal Attraction", in which Glenn Close's character Alex Forrest is known for boiling bunnies as part of her psychosis.\n\nThe film "Fatal Attraction" featured the villain Alex Forrest, who works as a photographer and engages in an affair with her married lover, Dan Gallagher. When she discovers that Dan is having second thoughts about the affair, she begins to stalk him and his family, which culminates in an attempted seduction of Dan's daughter, which causes Alex to be murdered by Dan.\n\nIn the 2010 video game "Fatal Frame", the primary antagonist is a psychopath named Miu Hinasaki. During the course of the game, she kidnaps several young girls and holds them prisoner at her house, where she sadistically mutilates them. Throughout the game, it is implied that she has been doing this for a long time, and that many other girls have disappeared without a trace.\n\nThe trope was also used in an early episode of "Glee" when Rachel Berry was terrorised by a former classmate, Quinn Fabray. The term has been used to refer to women in many fictional works, and has been]" time="0.312"><properties><property name="score" value="0.086939484" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nEdition: Dominaria\n\n\n\nSort:\n\nRare\n\nCommon\n\nUncommon\n\nCommon (2 versions)\n\nUncommon (2 versions)\n\nRare (2 versions)\n\nCommon (1 versions)\n\nUncommon (1 versions)\n\nRare (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nUncommon (1 versions)\n\nUncommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nUncommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nUncommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nUncommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nUncommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (1 versions)\n\nCommon (]" time="0.621"><properties><property name="score" value="0.00030410064" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Abraham Bredius\n\nAbraham Bredius (1855\u20131927) was a Dutch art collector and author of art books, known for his critical approach. He was especially a specialist in Dutch old masters, and the attribution of paintings.\n\nBredius was born on 2 July 1855 in Amsterdam, the son of a diamond merchant. He studied law at the University of Amsterdam and received his doctorate in 1879. He became a member of the Amsterdam Stock Exchange in 1878. He and his brother, Pieter Frederik Bredius, ran the diamond business for a time after their father's death in 1895. In 1899 he and his brother retired from business and moved to the town of Laren. His brother committed suicide in 1905.\n\nIn 1911, Bredius published his first art book, "Rembrandt: een monografie" (Rembrandt: a monograph), a scholarly study of Rembrandt's oeuvre, based on careful research of the existing works and contemporary documentation. His other publications include "Jan Steen" (1914), "Frans Hals" (1916), "De groote schilderijen in het Mauritshuis" (The large paintings in the Mauritshuis) (1923), "A descriptive catalogue of the works of Peter Paul Rubens" (1925) and "De schilderselders in Nederland gedurende de XVIIe en XVIIIe eeuw" (The painters of the Netherlands in the 17th and 18th centuries) (1927). The last book was published posthumously by his daughter.\n\nBredius was married to a daughter of Cornelis Hofstede de Groot, the art historian. Their daughter, Wilhelmina Bredius, was also an art historian.\n\nBredius was an art collector, and owned works by such artists as Frans Hals, Rembrandt and Jan Steen. He purchased many paintings and drawings at auction, and was considered to have the best collection of old masters in the Netherlands. The collection was put up for sale after his death, and many of the paintings found their way into museum collections. Some of his books are still available, as is the catalogue of his collection.\n]" time="0.346"><properties><property name="score" value="0.036014073" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Sesalpinia\n\nSesalpinia is a genus of flowering plants in the pea family, Fabaceae. The genus is native to the Americas, where it is distributed from the southern United States (Florida, Texas) to the northernmost part of Argentina (Tucum\xe1n). Species are known by many common names, including crown-peas, princess flower, Barbados pride, guizotia, maua, grama grass, whitetick, sandburs, Mexican ticks, pinquitos, piquitos, barbas de Indias, and zorillo.\n\nThe species of "Sesalpinia" are annual or perennial herbaceous vines, often with a woody base, reaching a height of 3 m. Leaves are bipinnate or tripinnate, made up of 10-30 leaflets, often with reddish margins. Flowers are in racemes, and are usually white to pink, though yellow and lavender flowers are known. The fruit is a pod, often with a distinctive hooked beak.\n\nThe genus is currently classified in the subfamily Mimosoideae, but the taxonomy is in need of a comprehensive phylogenetic study. The five species that have been traditionally recognized in "Sesalpinia" are not monophyletic. While the closest relatives of the genus are in the tribe Ingeae in subfamily Mimosoideae, "Sesalpinia" is not most closely related to any of the genera in that tribe.\n\n\n\n\n\n\n\n\n\n]" time="3.313"><properties><property name="score" value="0.10713827" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Ion beam studies of materials\n\nIon beam studies of materials (also known as ion beam analysis or IBA) is a discipline that aims to determine the microstructure of solids. Ion beam studies of materials use mass spectrometry to study materials. Ion beam analysis is the name used for the techniques developed to study the solid materials with either a gas or a particle beam. Particle beams are commonly produced by ion guns or by secondary ion mass spectrometry. For high resolution, single particle mass spectrometry (called single particle IBA) or time of flight (TOF) instruments are employed. For many studies, electron microscopes can be used with appropriate detectors.\n\nSingle particle mass spectrometry was invented by Herb Guyer and Edward A. Heineman at Cornell University in 1953. This technique was the foundation of the field of ion beam analysis. This technique has been used to study a wide range of materials including metals, ceramics, glasses, organics and polymers.\n\nIn this technique the ion beam is focused to a small spot size on the sample, either by focusing in a magnetic or an electrostatic field or by being focused by electrostatic fields in a multielectrode system. The beam is then scanned over the surface of the sample. For each sample point, a mass spectrum of the sample material is obtained. The signals from the individual elements in the sample are then compared to each other in order to determine the composition and/or structure of the sample. This is because the signals are characteristic of the elements from which they are produced. The process of matching up the signals is called deconvolution. In this technique, the detector signal is measured only when a particle of the beam is detected.\n\nThe disadvantage of this technique is that it requires much more time to measure each sample point compared to scanning probe microscopes (which use electron beams).\n\nThe electron microscope with a detector attached to it can be used as an IBA tool. It is very useful to study the microstructure of ceramics and glasses.\n\nThe technique was developed at Cornell University and its name was coined by Thomas Vale in 1959. In electron microscope IBA, the sample is placed on a thin window and a beam of electrons is directed at it. The beam of electrons is either the electron beam itself or the secondary electron beam produced by a beam of primary electrons.\n\nWhen the electron beam is directed at the sample, some of the electrons are absorbed by the sample. This produces electrons inside the material and some ions. The ions are extracted by an electric field and are accelerated. The electrons emitted from the ions are detected. The detector may be a microchannel plate (MCP) detector or an electron multiplier.\n\nIn these systems the electron beam is accelerated between two plates. As]" time="0.301"><properties><property name="score" value="0.18067104" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A police officer suffered facial injuries when he was sprayed with acid during a "very nasty" street robbery on Monday evening.\n\nThe Metropolitan Police said a member of the public used water to wash out the officer's eyes. He has been taken to hospital.\n\nThe policeman was on duty in Clapton, east London, when he was confronted by a man who pulled a corrosive substance from a pouch and sprayed it into his face.\n\nThe officer was then forced to hand over his personal possessions.\n\nMetropolitan Police spokesman, Detective Sergeant Gary Brown said: "This was a really nasty robbery, where the officer has approached a male and been sprayed with a substance - which we believe to have been an acid - in his face.\n\n"He has then been further assaulted and had personal belongings stolen."\n\nDet Sgt Brown said police were not aware of any particular motive behind the attack, adding: "It is probably a robbery that has gone wrong."\n\nThe officer is based at Stoke Newington Police Station, in Hackney, east London, and is a member of the borough's safer transport team, which was set up to reduce crime around Hackney's taxi and private hire trades.\n\nScotland Yard said the man responsible for the attack is described as a white male, in his late teens to early 20s.\n\nHe is about 5ft 11in, slim, with short blond hair and a small, blond beard. He was wearing a red, grey and black jacket, with blue jeans and white trainers.]" time="0.318"><properties><property name="score" value="0.18647969" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.18647969 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.18647969
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[EAT-25 Test System\n\nThe Panasonic EAT-25 Test System is a complete one-box system for testing audio/video (A/V) signals, enabling designers of A/V equipment to perform critical measurements quickly and conveniently.\n\nOur comprehensive system includes EZ-25A and EZ-19A signal generators, both of which can generate the same high-quality A/V test signals, EZ-D9A dual digital pattern generator, EZ-10R high-speed data pattern recorder, and EZ-S8 data logger. You can use the system in your own lab or rent it on a daily or monthly basis through our worldwide sales network.\n\nEZ-25A\n\nThe EZ-25A signal generator can generate a wide range of test signals and is the perfect solution for designers who need to generate test signals for A/V equipment such as digital receivers, AV power amplifiers, etc.\n\nEZ-19A\n\nThe EZ-19A signal generator is ideal for designers who need to generate video test signals for the latest A/V equipment such as liquid-crystal displays (LCD), plasma displays, etc. It is also ideal for assessing test and measurement capabilities for other equipment such as laser displays and printers.\n\nEZ-D9A\n\nThe EZ-D9A is a dual digital pattern generator that can generate high-quality A/V test signals. It is ideal for use in the development of portable AV devices, as well as for assessment of measurement capabilities for other devices such as printers, etc.\n\nEZ-10R\n\nThe EZ-10R high-speed data pattern recorder is a flexible test system that can record high-speed data patterns, as well as graphic images. It can be used to measure jitter and data loss that is occurring during transmission of A/V signals, and is ideal for measuring the performance of external data-compression devices.\n\nEZ-S8\n\nThe EZ-S8 data logger can record signals such as sound and video. It is ideal for users who want to log events such as sound and video in a non-stop mode.]" time="0.301"><properties><property name="score" value="0.023086308" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Embarrassing tax mistake gives a false impression that tax gap is falling at a time when it is rising\n\nThe government\u2019s much heralded fall in the tax gap may have been boosted by an embarrassing tax \u2018error\u2019, which has skewed official figures to suggest that the amount of tax which goes unpaid is falling.\n\nHM Revenue and Customs (HMRC) has admitted that a major error in the way it handles unpaid taxes from firms using the banking system has overstated its tax gap \u2013 the amount of tax which goes unpaid \u2013 and understated the number of people working under the taxman\u2019s radar.\n\nIn a document on its website, it admitted that it has been failing to record taxes which should have been received but were not, but said it did not \u2018understate\u2019 the size of the tax gap.\n\n\u2018The effects of this error are that the statistics do not represent a full year\u2019s tax gap and do not fully represent the HMRC compliance work,\u2019 it said.\n\nThe error means that the tax gap fell from \xa335 billion in 2014/15 to \xa333.2 billion last year, when in fact the correct figure would have been \xa339.5 billion.\n\nThe mistake means that the tax gap is now out by more than \xa35 billion.\n\nThe admission follows a series of problems for the HMRC. The organisation was accused of losing sensitive personal data on more than 10 million people in an unencrypted CD in 2015, and was also accused of sending the wrong letters to half a million people.\n\nIt has also been criticised for a raid on the offices of investigative reporters at The Guardian.\n\nAn HMRC spokesperson said: \u2018It has become clear that our compliance data is not fully comparable over time, and we will not be publishing it in this form again. This does not affect the overall tax gap and our published estimates of the tax gap for the years 2014-15 and 2015-16 have not changed.\u2019\n\nA statement on the HMRC website said that the data published on 31 August \u2018estimated the total tax gap to be \xa333.2 billion for the year 2015-16. This figure represents a decrease of \xa34.7 billion on the 2014-15 tax gap of \xa338.9 billion, or a 14 per cent decrease\u2019.\n\nBut it admitted that the figure included \u2018incorrect estimates\u2019 on income tax, VAT and customs duty.\n\n\u2018We have corrected this error and published revised estimates for income tax, VAT and customs duty. These estimates now estimate the total tax gap to be \xa339.5 billion for the year 2015-16, which is an increase of \xa34.3 billion on the 2014-15 tax gap of \xa335.2 billion,\u2019 it said.\n\n\u2018This increase in the tax gap is not a true reflection of what has happened in compliance. It is because the 2015-16 estimates have included the correction of the error which has overstated the 2014-15 tax gap.\u2019]" time="0.349"><properties><property name="score" value="0.053416107" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05341611 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05341611
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[9 ATC ? What is an ATC and how do I use one? An ATC is an automatic transfer switch. It is used to transfer power to the boiler in the event of a power failure. These switches are "automatic" in the sense that they monitor the power flow through the generator and as soon as the power goes off, they engage the transfer switch (in parallel to the house breaker) to power the boiler. When the power is restored, the ATC turns off and disconnects the power to the boiler, restoring the house power. (We are not responsible for damages caused by not following these instructions). Before starting to install the system, you need to find the right place to put your ATC switch. Some considerations include: 1. You should put your ATC as close to the back of the generator as possible. This will make it easier for you to wire it up. 2. It is important to find a place that is dry. You can't use an ATC outside. It will just short out if it gets wet. 3. It needs to be in an accessible place (inside your home). It doesn't need to be near the breaker box (but it should be near a wall outlet). 4. The ATC should be installed at least 3 feet from the nearest source of water (sump pump, water heater, etc.) 5. If your generator is in a cabinet, you should put the ATC switch on the side of the cabinet so it is easy to]" time="0.324"><properties><property name="score" value="0.046559405" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The map below shows the approximate location of every reported gorilla location between October 2010 and September 2011.\n\nThe red circles show where the gorillas have been reported.\n\nTo see the previous year's map, click here.\n\nMapping gorillas is difficult because of the rugged and thick vegetation in the forests of Congo, where they are found.\n\nOften the trackers do not actually see the gorillas themselves, only hear their distinctive screams, and have to make their estimates based on signs such as footprints and vegetation trampled by the large apes.\n\nHowever, the gorilla range is thought to have expanded significantly in the last five years.\n\nThe good news is that the population is now thought to be in excess of 4,000 gorillas.\n\nThere are many more threats to gorilla survival than loss of habitat, however, and none are yet under control.\n\nThe gorilla is Africa's most threatened mammal, and faces threats from poaching and disease, in addition to the loss of their habitat, and the practice of hunting them for "bushmeat".\n\nThe Rwandan genocide of 1994 also left a terrible legacy, with the influx of refugees leaving a legacy of poaching and poverty.\n\nThe official policy of the Republic of Congo is that all gorillas should be left in peace in their natural habitat, which is now also under pressure from logging.\n\nThe WWF is helping to train a team of gorilla trackers to continue to monitor the gorillas' progress.\n\nYou can support their work by donating to the WWF.]" time="0.329"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Related articles: 1/3\n\n2/3\n\n3/3\n\nAre you looking for a way to improve your website\u2019s search engine rankings? How about better user experience? There are many ways you can accomplish both.\n\n1. Reduce your page\u2019s load time\n\nGoogle uses the page load time as one of the factors when determining your search engine rankings. You can use PageSpeed Insights to measure the page load time for any URL.\n\nYou should aim for a score of 90/100 and lower. It\u2019s worth pointing out that although this factor is being used as a ranking factor, a slow site will have a negative impact on user experience, which in turn will affect your brand image, search results, and conversions.\n\n2. Enable GZIP compression\n\nGZIP compression compresses the HTML, CSS, and JavaScript files in your web pages, which reduces the size of those files and the total data transferred to the user. Google uses this factor to determine page load time.\n\nPageSpeed Insights has a compression test that allows you to measure the level of compression achieved by your website.\n\nFor more information on how to enable GZIP compression, see this article.\n\n3. Enable HTTPS\n\nHTTP Strict Transport Security (HSTS) allows websites to tell browsers to avoid interacting with any sites except the ones that use HTTPS. This is useful in preventing man-in-the-middle attacks.\n\nAs of this writing, Google considers HTTPS as a ranking factor in its search algorithm.\n\nThe problem is that although enabling HTTPS is pretty easy (for WordPress websites), it\u2019s not so easy when you have to replace all of your URLs with HTTPS URLs, and make sure that your backlinks are using HTTPS.\n\nIf you\u2019re not ready to migrate, you can use the free tool from CloudFlare, which allows you to encrypt your WordPress website and even apply SSL to all of your images, making the switch to HTTPS easy and effective.\n\n4. Check your internal links\n\nInternal links are links that point to another page on your own website. Google uses these links to determine the value of the pages in your website, and how well your site is structured.\n\nLink-building specialists will tell you that there are a lot of ways to build good quality links.\n\nFor example, you can use social bookmarking sites, forums, and blogs. For links pointing to your website, you can ask friends, relatives, clients, and business partners to post links to your website on their websites.\n\nBut, you should do this within reason, and avoid looking like a link-building spammer.\n\n5. Include internal links in your blog posts\n\nYour blog posts should include internal links, to ensure that Google can detect the relationships between your posts. This will also improve your readers\u2019 experience by allowing them to quickly find the posts that are most relevant to them.\n\n6. Create an XML sitemap\n\nAn XML sitemap is a page on your website that contains a list of all the URLs on your website. If you\u2019ve been blogging for some time, you\u2019ve probably already created a sitemap to allow search engines to crawl your site.\n\nThe problem is that search engines do not use the sitemap file on your website to crawl your website. In other words, sitemap file is useless to search engines.\n\nFortunately, there\u2019s a free plugin from Yoast that can automatically generate an XML sitemap and also add the sitemap to your website.\n\n7. Install social sharing plugins\n\nSocial media is a great way to market your website and brand. Not only that, you can also use social media as a way to improve your search engine rankings.\n\nWhen you share your content on social media, you can make the content more accessible to your visitors. Not to mention the fact that social sharing plugins also provide users with a link to your content, which is great for SEO.\n\nSome of the best social sharing plugins for WordPress websites include Facebook, Pinterest, and Twitter.\n\n8. Install and enable W3 Total Cache\n\nW3 Total Cache can greatly improve your website\u2019s load speed by enabling caching for your website\u2019s pages, posts, and images.\n\nYou can read my review of W3 Total Cache to learn more.\n\n9. Install and enable Yoast SEO\n\nYoast SEO allows you to configure your search engine settings for each post and page on your website. It\u2019s the most powerful SEO plugin for WordPress.\n\nFor more information on how to configure Yoast SEO for optimal SEO, see my tutorial on SEO for WordPress.\n\n10. Install and configure Google XML Sitemaps\n\nThis is another free plugin from Google that generates an XML sitemap for your website. This sitemap will allow search engines to crawl your website faster and more efficiently.\n\nIt also helps you to build quality backlinks to your website. The links in the XML sitemap are much stronger than the links in your sitemap file, because they are permanent links.\n\nYou can read more about how to configure Google XML Sitemaps for optimal SEO.\n\n11. Install and enable Google Analytics\n\nGoogle Analytics is a free analytics tool from Google that lets you monitor your website\u2019s performance, including the number of visitors you\u2019re getting, where they\u2019re coming from, and what they\u2019re doing on your website.\n\nI have my own tutorial on how to configure Google Analytics for optimal SEO.\n\n12. Install and enable Google Webmaster Tools\n\nWebmaster Tools is another free tool from Google that lets you verify your website and configure a wide range of settings, including your preferred domain, how your website is indexed, what the canonical URLs are, whether you allow Google to crawl dynamic pages, whether you allow web crawlers to follow your links, and whether you allow Google to scan your pages for malware.\n\nWebmaster Tools is especially useful for websites that have a lot of dynamic pages, and pages that are indexed using non-standard URLs.\n\n13. Install and enable Google Analytics by Yoast\n\nGoogle Analytics by Yoast is another free plugin that allows you to synchronize your Google Analytics account with the most popular SEO plugin for WordPress, Yoast SEO.\n\nWith this plugin, you can easily add your Google Analytics tracking code to all your posts, pages, and sidebars, without having to manually add the tracking code for each post.\n\n14. Submit your website to Google\n\nIf you have a new website, you should submit it to Google Webmaster Tools, which will allow Google to index your website and create a site map.\n\n15. Install a contact form plugin]" time="0.656"><properties><property name="score" value="0.14917780349999998" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.1491778 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.1491778
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In today\u2019s digital age, many people look to the internet to learn about and purchase products. These include retail shoppers who look to Amazon for new toys or appliances, travelers who look to Expedia for airline tickets, and even patients who look to the internet to learn about a disease or find a doctor. This presents unique challenges for brand owners. While brand owners can claim ownership of certain content on their sites and apps, much of the internet is controlled by other entities. This includes social media sites, search engines, content syndicators, content aggregators, and other web sites. A brand owner who does not protect its name and trademarks on these sites risks losing control of its brand online.\n\nIn the past, brand owners who found a third-party using its trademarks or similar trademarks had to prove that the third-party was using the mark in a confusing manner. This required proving that the third-party\u2019s use of the mark was likely to cause confusion in the mind of the average consumer, i.e. that it was likely to be mistaken for the mark of the brand owner. Today, however, that burden of proof is no longer necessary.\n\nA little over one year ago, the Ninth Circuit Court of Appeals decided the landmark case of Global-Tech v. eBay, 562 F.3d 982 (9th Cir. 2009). The Global-Tech decision held that a plaintiff can bring a claim against a third-party for cybersquatting by using the new procedures set forth in the Anti-Cybersquatting Consumer Protection Act of 1999 (\u201cACPA\u201d). Previously, under the ACPA, a brand owner had to prove confusion to make a cybersquatting claim. Under the new regime, the burden has been placed on the third-party to show that its use of a domain name is legitimate.\n\nThe burden shift was the most significant change in the Global-Tech case. Before Global-Tech, a cybersquatting plaintiff had to prove confusion. After Global-Tech, a cybersquatting plaintiff only needs to prove that a defendant has registered a domain name similar to the plaintiff\u2019s mark with bad faith intent to profit.\n\nAccording to the Ninth Circuit, \u201cthe ACPA\u2019s [bad faith] requirement means little more than that a domain name registrant must intend to profit from the goodwill associated with the plaintiff\u2019s mark.\u201d\n\nOnce a cybersquatting plaintiff has proven this intent, a plaintiff need only show that it owns a trademark that is similar to the defendant\u2019s domain name in order to prevail on its claim. This is the essence of the burden shift. A plaintiff who successfully proves that the defendant is cybersquatting on a domain name that is similar to its trademark does not need to prove that consumers are being confused. The cybersquatter must show that its use of the domain name is legitimate.\n\nThe Global-Tech case also made it easier for a plaintiff to win a cybersquatting case because of the additional burdens placed on a defendant.\n\nFirst, the Global-Tech case made it harder for a cybersquatting defendant to defend itself on the merits. Before Global-Tech, a defendant could defend a cybersquatting claim by arguing that its use of the domain name was not confusing to consumers. However, after Global-Tech, a defendant can no longer rely on its good faith use of the domain name to show that it is not cybersquatting. Instead, a defendant must show that its use of the mark is legitimate. This has led to claims of cybersquatting where the mark and the domain name are similar, but where there is no evidence that consumers are being confused.\n\nSecond, the Global-Tech case made it easier for a cybersquatting plaintiff to obtain injunctive relief. Traditionally, a cybersquatting plaintiff had to show that it was likely to prevail on its claim in order to obtain an injunction to prevent a defendant from using its domain name. After Global-Tech, a plaintiff need only show that the defendant is likely to profit from its use of the domain name to obtain an injunction. Since an injunction may be obtained before trial, this allows plaintiffs to eliminate the use of their marks by defendants before they can defend their actions in court.\n\nThe Global-Tech case has led to a shift in the burden of proof in cybersquatting cases. This shift has created an environment where cybersquatting cases are becoming more difficult to defend.]" time="0.537"><properties><property name="score" value="0.24693155" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24693155 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24693155
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rated 5 out of 5 by Bullockie79 from The only thing better than this shirt is the price I\u2019m a bigger guy and I like to buy shirts that fit my body. This shirt is long enough in the body and the sleeves, so the shirt fits properly. I\u2019m very pleased with the weight of the shirt. It\u2019s not too heavy. So I don\u2019t get too hot.\n\nRated 5 out of 5 by kramer from great product This is the second shirt I have purchased in this style. I wear them almost every day and wash them many times. They are very durable.\n\nRated 5 out of 5 by JJG1 from Great shirt Great shirts. Great quality and material. Washes great and hangs out on the line to dry. Great with the Carhartt suspenders.\n\nRated 5 out of 5 by Bihangir from Fantastic! Awesome product, awesome quality. Will buy more for sure. I bought this on sales and even then, it is a good buy.\n\nRated 5 out of 5 by Anthony from A go-to for work, play, anywhere! Great fitting shirt, true to size. A comfortable classic for any occasion. It is heavy weight, but does not feel thick, just a nice fit.\n\nRated 5 out of 5 by Carpenter from Best dress shirts These are great shirts they fit well, they are long enough. I would recommend them to anyone.\n\nRated 5 out of 5 by KLJ93 from Great fit These shirts are great for work or everyday wear. They fit perfectly and are of very high quality.]" time="0.306"><properties><property name="score" value="0.07914479" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[One of my favourite times in the barbershop. I love conversations with guys about life, business, sex, sports and news.\n\n\n\nA friend of mine said, "The best conversations happen over a good cup of coffee".\n\n\n\nThat\u2019s what I\u2019ve done in my new book... \u2018Good Coffee, Bad Conversations\u2019.\n\n\n\nIf you\u2019ve got a few minutes, I\u2019d like to share a story with you.\n\n\n\nIn the late 90\u2019s, my business partner, Jeff \u2013 a good friend of mine and also a barber \u2013 was having problems. He was having lots of conflict with his wife and daughter and he was angry all the time.\n\n\n\nI asked him if he wanted to talk about it.\n\n\n\nHe said, \u201cNo. That would be good coffee, bad conversation.\u201d\n\n\n\nIt\u2019s true, Jeff was scared to open up and share what was really going on in his life. He was afraid of what he would hear.\n\n\n\nI remember this time because I wanted to help Jeff, but I didn\u2019t know what to do. So I did the only thing I knew how to do.\n\n\n\nI started writing.\n\n\n\nAs I wrote, I realized that coffee was a lot like conversation.\n\n\n\nA cup of coffee was good.\n\n\n\nA cup of coffee was bad.\n\n\n\nThat\u2019s when it hit me... \u2018Good Coffee, Bad Conversations\u2019.\n\n\n\nIt\u2019s about the conversations we have and how they can make or break our lives.\n\n\n\nIn my book, I show you the seven bad conversations you need to stop having. You\u2019ll also learn the seven good conversations you should start having instead.\n\n\n\nAs a bonus, I also share the six good conversations I\u2019ve had with some amazing people including Grant Cardone, Kody Deis, Andy Frisella, Gary Vaynerchuk and others.\n\n\n\nThere\u2019s more, but you\u2019ll have to read it to find out.\n\n\n\nThe book is short and concise. It\u2019]" time="0.275"><properties><property name="score" value="0.75625783" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Magic: the Gathering has launched the Dominaria campaign. Dominaria is a plane steeped in rich lore and ancient magics. The world is home to several important factions, including Benalia, home to the Knights of Benalia, and the nation of Corondor. Corondor is ruled by Baron Sengir and his brother, Baron Sardu.\n\nDominaria is also home to some of Magic\u2019s most iconic characters. The Weatherlight is crewed by a legendary host of characters, including Captain Sisay, Karn, and Teferi. But the Weatherlight\u2019s roster is far from limited to famous crew members.\n\nThis is the history of the Weatherlight\u2019s crew members who weren\u2019t famous enough to get their own card.\n\n(Special thanks to Jason Carl\u2019s Comprehensive Rules FAQ and to YSDC\u2019s flavor text wiki for their incredible flavor text sources.)\n\nVenser, Shaper Savant\n\nVenser is an artificer who discovered his latent Planeswalker abilities while recovering from an injury on the plane of Shandalar. After being recruited to join the crew of the Weatherlight, Venser eventually fell into a coma and later revived himself on the plane of Koilos.\n\nKarn, Silver Golem\n\nKarn is a silver golem who used to live on the plane of Argentum. He came aboard the Weatherlight after his homeworld was destroyed by a time riptide.\n\nAven Windreader\n\nAven Windreader is a scout who used to serve in the Feather clan of Aven, a nomadic race. She is joined on the Weatherlight by two siblings: Aven Brigadier and Aven Trooper.\n\nSisay, Captain\n\nSisay is a captain from the nation of Jamuraa, and is the Captain of the Weatherlight.\n\nSquee, Goblin Nabob\n\nSquee is a goblin on the Weatherlight crew. His fellow goblin cohorts on the crew are Rishadan Cutpurse, Rishadan Footpad, and Greel.\n\nIrina, Great Glass-Spinner\n\nIrina is an illusionist who used to serve the Imperial Court of Otaria. She was exiled after the court was overthrown and joins the Weatherlight in search of answers.\n\nSharuum the Hegemon\n\nSharuum is an artificer who, in her past life, became a planeswalker. Sharuum built a stronghold called Koilos on the plane of Koilos, and served as a guardian to the mysterious stronghold.\n\nEdric, Spymaster of Trest\n\nEdric was a spy who was arrested after his cover was blown. Edric\u2019s home nation of Trest was destroyed, and he was freed from his cell aboard the Weatherlight in exchange for his assistance on the ship\u2019s infiltration of Phyrexia.\n\nSquee, Goblin Nabob\n\nSquee is a goblin who served as the goblin court advisor to the Supreme Arbiter of the Imperial Court of Otaria. He joins the Weatherlight crew after being abandoned in Krov on Dominaria, and joins the crew in order to find a way home.\n\nTahngarth, Talruum Hero\n\nTahngarth is a Tahngarth is a minotaur who hails from the nation of Talruum. Tahngarth was captured by Sarpadian pirates and sold into slavery. He was rescued from his servitude by the crew of the Weatherlight.\n\nKarn, Silver Golem\n\nKarn was a silver golem who lived on the plane of Argentum. He boarded the Weatherlight after his homeworld was destroyed by a time riptide.\n\nKarn, Silver Golem\n\nKarn is a silver golem who used to live on the plane of Argentum. He came aboard the Weatherlight after his homeworld was destroyed by a time riptide.\n\nStarke of Rath\n\nStarke of Rath is a master thief who joins the Weatherlight crew after discovering a conspiracy to overthrow the current government of his native country of Rath.\n\nKarn, Silver Golem\n\nKarn was a silver golem who used to live on the plane of Argentum. He came aboard the Weatherlight after his homeworld was destroyed by a time riptide.\n\nGryff, Knights of Benalia\n\nGryff was a member of the Knights of Benalia who died in a battle against an Onakke Ogre. He was later revived by Tiana, Ship\u2019s Caretaker, who repurposed his damaged body as a messenger for the ship.\n\nKarn, Silver Golem\n\nKarn is a silver golem who used to live on the plane of Argentum. He came aboard the Weatherlight after his homeworld was destroyed by a time riptide.\n\nTiana, Ship\u2019s Caretaker\n\nTiana is a ship\u2019s caretaker who was attached to the Weatherlight before it was even built. She was responsible for the upkeep of the ship, including a number of tiny, flying custodians.\n\nTiana, Ship\u2019s Caretaker\n\nTiana is a ship\u2019s caretaker who was attached to the Weatherlight before it was even built. She was responsible for the upkeep of the ship, including a number of tiny, flying custodians.\n\nAven Envoy\n\nAven Envoy was a captain who used to serve in the Knights of Avon. She lost her entire company during a battle against an Onakke Ogre. Aven Envoy was revived by Tiana, Ship\u2019s Caretaker, and took up a new post as envoy for the Weatherlight.\n\nUrza Planeswalker\n\nUrza was a planeswalker who, after his death, was merged with a powerstone and transformed into an artificial planeswalker. He was the first person to travel to the plane of Phyrexia, and later forged a coalition of planeswalkers against the Phyrexians.\n\nSquee, Goblin Nabob\n\nSquee is a goblin who served as the goblin court advisor to the Supreme Arbiter of the Imperial Court of Otaria. He joins the Weatherlight crew after being abandoned in Krov on Dominaria, and joins the crew in order to find a way home.\n\nIcatian Lieutenant\n\nIcatian Lieutenant is a soldier from the nation of Icatia. She joined the crew of the Weatherlight in order to track down her fellow Icatian soldiers who were captured by Rathi forces.\n\nKarn, Silver Golem\n\nKarn is a silver golem who used to live on the plane of Argentum. He came aboard the Weatherlight after his homeworld was destroyed by a time riptide.\n\nBarren Glory\n\nBarren Glory is a captain who came from an apocalyptic future. He used to captain a ship called the Weatherlight, which is (unsurprisingly) a ship not unlike the Weatherlight.\n\nJhoira, Weatherlight Captain\n\nJhoira is a master artificer who was captain of the Weatherlight for a time.\n\nGryff, Knights of Benalia\n\nGryff was a member of the Knights of Benalia who died in a battle against an Onakke Ogre. He was later revived by Tiana, Ship\u2019s Caretaker, who repurposed his damaged body as a messenger for the ship.\n\nCaptain Lannery Storm\n\nCaptain Lannery Storm was a member of the crew of the Weatherlight who was killed during a mission to Rath. She was later revived by Tiana, Ship\u2019s Caretaker, and now serves on the Weatherlight as a crew member.\n\nNimbus Maze\n\nNimbus Maze was an artificer who served the Knights of Benalia. He was sent to accompany Squee on a diplomatic mission to Icatia, but was killed by a phyrexian vat lord during the visit.\n\nSquee, Goblin Nabob\n\nSquee is a goblin who served as the goblin court advisor to the Supreme Arbiter of the Imperial Court of Otaria. He joins the Weatherlight crew after being abandoned in Krov on Dominaria, and joins the crew in order to find a way home.\n\nAjani, Mentor of Heroes\n\nAjani is a leonin planeswalker who was once the leader of the Capashen clan on the plane of Alara. His pride led to a war between the clans of Capashen and Kumena. After the war, Ajani renounced his leadership and traveled to Dominaria.\n\nSquee, Goblin Nabob\n\nSquee is a goblin who served as the goblin court advisor to the Supreme Arbiter of the Imperial Court of Otaria. He joins the Weatherlight crew after being abandoned in Krov on Dominaria, and joins the crew in order to find a way home.\n\nBarren Glory\n\nBarren Glory is a captain who came from an apocalyptic future. He used to captain a ship called the Weatherlight, which is (unsurprisingly) a ship not unlike the Weatherlight.\n\nSquee, Goblin Nabob\n\nSquee is a goblin who served as the goblin court advisor to the Supreme Arbiter of the Imperial Court of Otaria. He joins the Weatherlight crew after being abandoned in Krov on Dominaria, and joins the crew in order to find a way home.\n\nKarn, Silver Golem\n\nKarn is a silver golem who used to live on the plane of Argentum. He came aboard the Weatherlight after his homeworld was destroyed by a time riptide.\n\nCaptain Lannery Storm\n\nCaptain Lan]" time="0.626"><properties><property name="score" value="0.5141985600000001" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.51419856 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.51419856
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[BestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disincastrare la Verifica Torx\xae Per Tutti i Modelli\n\nBestoBasket Cacciaviti Sfilabile Meccanico per Disinc]" time="0.811"><properties><property name="score" value="0.00021816011499999999" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[All the new games for the week\n\nOnce upon a time, the first week of the month meant a new Switch eShop release was imminent, but recently, Nintendo has shown an admirable level of restraint. The first week of this month is no different, as there's just a couple of new games on the way to the system's digital store.\n\nComing to North America this week is the sequel to the surprise hit of 2017, Wonder Boy: The Dragon's Trap. The platformer has a rich history on the PC and consoles, but this remake proved to be well worth the time spent by the fans. With a new look and modern gameplay, this is certainly worth your time if you haven't played it yet. The Dragon's Trap releases in North America on February 9.\n\nFor our European readers, this week brings us into the dangerous world of SteamWorld Dig 2. While the first game was critically acclaimed and earned quite a bit of love, this sequel looks to improve on the formula by adding a lot more variety and some online multiplayer options. Dig 2 is a bit more than a week away, and will be available on February 9.\n\nIf that's not enough for you, then you'll be happy to know that the Nintendo Switch's Virtual Console service has something new in store for you. For the week of February 13, the Nintendo 64 classic Donkey Kong 64 will be available on the system's store.\n\nAs always, we'll keep an eye on the eShop and update you on new releases if and when they become available. If you're holding out for some new physical releases, we should have some news later today.\n\nThis article may contain links to online retail stores. If you click on one and buy the product we may receive a small commission. For more information, go here.]" time="0.380"><properties><property name="score" value="0.33182573" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.33182573 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.33182573
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[View Full Version : How can I identify potential variables?\n\nMikeJackness Hi all,\n\nI'm trying to learn about and identify some potential (input) variables for a simple device.\n\n\n\nI've looked at the classic approach using the Analyser to get a range of DC voltages (input values) and their corresponding output values but that's not what I'm looking for.\n\n\n\nI want to find out what variables may affect the final values I am looking for and why they have an effect on the outputs.\n\n\n\nAn example would be, lets say I am looking for DC values of between 2V and 4V. The device I am testing has a button which, when pressed, will alter the value of something between 1% and 100%. How can I find out what that value is? I know that it's 1% - 100%, but I want to know the value of the device and how it affects the outcome.\n\n\n\nThanks\n\nMike\n\nIan Smith You need to identify what it is you are actually measuring.\n\n\n\nAre you measuring the current through a certain circuit? If so, you need to measure the voltage drop across it (and also the current through the circuit itself)\n\nAre you measuring the temperature of a thermocouple?\n\nAre you measuring the force produced by a tensile tester?\n\netc etc.\n\n\n\nThe only way to find out is to identify what is actually changing (when the button is pressed) and what is being measured.\n\n\n\nHope that helps.\n\nMikeJackness You need to identify what it is you are actually measuring.\n\n\n\nAre you measuring the current through a certain circuit? If so, you need to measure the voltage drop across it (and also the current through the circuit itself)\n\nAre you measuring the temperature of a thermocouple?\n\nAre you measuring the force produced by a tensile tester?\n\netc etc.\n\n\n\nThe only way to find out is to identify what is actually changing (when the button is pressed) and what is being measured.\n\n\n\nHope that helps.\n\n\n\nIt does help a lot, thank you. I'm looking at the values in the actual device rather than the sensor values.\n\n\n\nI'm trying to test a stepper motor, and I want to see if the resistance of the motor changes when it turns.\n\n\n\nI guess I'll have to figure out what the resistance is when the motor is not turning and what it is when it is, then identify the variables that affect it.\n\n\n\nAny more ideas would be great.\n\nIan Smith I'm trying to test a stepper motor, and I want to see if the resistance of the motor changes when it turns.\n\n\n\nAh! Well, you've gone and identified the system (stepper motor) and the variables (resistance). Now all you have to do is find out the actual resistance and how it changes when the motor is turned.\n\n\n\nAlso, have you determined whether the motor is powered from an AC mains supply or from a DC battery (or similar)? You need to know this because AC mains supplies may vary the current they provide, depending on the load (which may include the motor), and some DC supplies may have a current limit (which you may need to bypass if it's too low).\n\n\n\nHope this helps.\n\nMikeJackness Hi all,\n\nI've been doing some reading and thinking about how to approach this, and it looks like my answer is to use two multimeters.\n\n\n\nOne to measure the voltage of the stepper motor (when turned) and the other to measure the current flowing through it (when turned).\n\n\n\nThe questions are;\n\n\n\nWhat kind of multimeter should I use?\n\nShould I use a panel mount multimeter for ease of use, or a DMM?\n\nShould I try to build a sensor for the current measurement?\n\nIan Smith Hi all,\n\nI've been doing some reading and thinking about how to approach this, and it looks like my answer is to use two multimeters.\n\n\n\nOne to measure the voltage of the stepper motor (when turned) and the other to measure the current flowing through it (when turned).\n\n\n\nThe questions are;\n\n\n\nWhat kind of multimeter should I use?\n\nShould I use a panel mount multimeter for ease of use, or a DMM?\n\nShould I try to build a sensor for the current measurement?\n\n\n\n1. Both, to begin with. You may only need one, but you may need two, and it's better to have two of them.\n\n\n\n2. As above. If you can't build the current measurement, then either use one of the basic models that has a current setting, or use the voltage reading on the meter and then calculate the current from that. (e.g. multiply by 0.6 to get approximate amperes)\n\n\n\n3. Again, as above. If you can't build a current measurement, then you can get a panel meter to do the job for you, or you can try one of the fancier meters that have current measurement as one of their functions.\n\nMikeJackness Thanks for the replies. I am currently using two multimeters, a panel meter and a handheld meter.\n\n\n\nI've built an adjustable resistance using one of the 5W, 12V heater elements from a microwave. When I put it in series with the motor it showed a resistance of around 400 Ohms.\n\n\n\nI was then trying to identify how much current it drew when it was switched on, and I couldn't get a good result because the panel meter wasn't reading it properly.\n\n\n\nI think that's where I'm at with it at the moment. I may try using my handheld multimeter to see if it can read the current draw, but that may prove difficult because I'm not sure where the current is going through the stepper.\n\n\n\nThanks again for all the advice.\n\nIan Smith Thanks for the replies. I am currently using two multimeters, a panel meter and a handheld meter.\n\n\n\nI've built an adjustable resistance using one of the 5W, 12V heater elements from a microwave. When I put it in series with the motor it showed a resistance of around 400 Ohms.\n\n\n\nI was then trying to identify how much current it drew when it was switched on, and I couldn't get a good result because the panel meter wasn't reading it properly.\n\n\n\nI think that's where I'm at with it at the moment. I may try using my handheld multimeter to see if it can read the current draw, but that may prove difficult because I'm not sure where the current is going through the stepper.\n\n\n\nThanks again for all the advice.\n\n\n\nI can't help with the current measurement, I don't know much about motors.\n\n\n\nBut, if you]" time="0.923"><properties><property name="score" value="0.0030445531" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[LINGUIST List 12.2282\n\nThu Apr 26 2001\n\nReview: Discourse Studies\n\nEditor for this issue: Terence Langendoen <terry linguistlist.org>\n\nDirectory\n\nMessage 1: Genre Analysis and Discourse Analysis\n\nKen Hyland, Introducing Discourse Analysis (Blackwell Introductions to Applied Linguistics) , xii+267pp, paperback ISBN 0-631-22512-8, hardback ISBN 0-631-22511-X, $47.95 / ??35.00 The blurb on the back: This textbook introduces students to the main traditions of discourse analysis, from structuralism to modern approaches, and includes many examples of actual texts for study and analysis. Hyland has developed his own approach, based on a number of leading methods, to show the student how to apply them to language use. Divided into four parts, this book explores the key concepts, applications and findings of these methods, in the first section looking at language and discourse as a unit, in the second examining patterns of text structure, in the third explaining how discourse is used to construct particular kinds of meaning, and in the fourth looking at how we study discourse. The first three sections introduce three different approaches to discourse analysis - the macro-structural approaches of Saussure and Gee, the micro-structural approach of Halliday, and the interpersonal approaches of Brown and Hodge. The last section explores ways in which different kinds of discourse are studied, including conversation, literature, power, work and the media. What I liked: This is an excellent textbook. It provides a good survey of a range of discourses analysis approaches and provides clear descriptions of the methodological principles of these approaches. This is an approachable introduction to a complex and diverse field. The topics covered include the analysis of conversation, text and the various modes of literature. Hyland shows how the same principles can be applied to these different types of text. He draws on a wide range of literature to show how discourses can be studied and includes many examples of actual texts. The book is very clearly written, contains many well-chosen examples, and provides a good introduction to a subject which is likely to be of increasing interest to Linguists. What I didn't like: The chapter on the analysis of conversation and the chapter on the analysis of discourse in fictional texts would benefit from a more rigorous discussion of the key concepts used in this type of analysis. For example, the chapter on conversation provides an excellent introduction to this type of discourse, but it would be better if there was a clearer discussion of the concepts of turn-taking and overlap, and a more careful explanation of the use of 'look-back' studies and the main types of transcription. The chapter on discourse in fictional texts provides an introduction to a type of analysis which has not been covered elsewhere in the book, and this is an important addition to the text. However, this chapter does not include the discussion of the key concepts of discourse analysis which is provided in the other chapters. It would have been better if this chapter could have followed the same format as the other chapters, and discussed how a particular approach was developed, what its key concepts are, and how these concepts can be applied. I think that this is an important addition to the book. Another minor point is that there are several typos in the book, but I don't think that this detracts from the overall quality of the book. What is missing: A discussion of the key concepts of discourse analysis which can be applied to all types of text.]" time="0.478"><properties><property name="score" value="0.007755152" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[More than 600 students in the CSU system are waiting for their transcripts to be cleared.\n\nTranscripts at CSU campuses are frozen for over 600 students who attended the Pueblo campus last semester, and if they don't complete their credits and final exams, they could lose their scholarships and their seats.\n\nAccording to the CSU-Pueblo website, 615 students have not yet completed their spring semester. They will lose their financial aid eligibility if they don't finish.\n\n"It's like they're on a waiting list," said Dale Lange, who works at the registrar's office. "We're waiting for the teachers to grade their finals and the professor to submit the grades and then they can release the transcript."\n\nOn March 20, the Pueblo campus was told to cease instruction and close by the chancellor's office.\n\n"It's just horrible," said CSU-Pueblo student Julea Prentice. "I don't know if I'm graduating or not."\n\nPrentice said she's upset she's paying for classes that she can't use, but she feels she doesn't have a choice.\n\n"If I want to go to graduate school I have to get a certain GPA, so I can't afford to fail this semester," said Prentice.\n\nMeanwhile, her son is suffering because he needs a caretaker for his medical condition.\n\n"That's why I'm a mother, that's why I'm a mom, that's why I'm a father," said Prentice.\n\nPrentice said she feels alone and doesn't know what to do.\n\n"If I don't have an answer, I can't do anything," said Prentice. "I just have to wait."\n\nIt's a wait-and-see game for CSU students.\n\n"I just hope we all pass," said Prentice.\n\nSome students, like Adrienne Longoria, have called out for help.\n\n"Help us," she said. "Help us students."\n\n"We would have probably been able to catch up if they had let us finish our classes," said Longoria. "It's just frustrating that they can't let us finish our last few weeks."\n\nLongoria and Prentice said they want to go to graduate school, but if they don't pass this semester, they could lose their scholarships.\n\n"I'm trying to be hopeful," said Prentice.\n\n"It's frustrating, but I don't know what to do," said Longoria. "I'm hoping we get our money back and I'm hoping we can finish this semester."\n\nCSU-Pueblo officials said they don't know when transcripts will be released because each student's professor has to grade the final exams and send them to the registrar's office.]" time="0.366"><properties><property name="score" value="0.19423413" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.19423413 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.19423413
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Justin Fox\n\nIf you are the type of person who needs a car that can turn on a dime in the city but also tow your boat to the lake, the 2014 Lexus ES will probably fit the bill. When Lexus first introduced the current ES in 2006, the formula was right. But by 2012, it had become dated. The original ES was slow, thirsty and not very capable. The second generation added power and speed and was the first ES to tow. With the third generation, Lexus has taken that formula one step further and brought in all-wheel drive and a more refined driving experience. But it also kept the old formula.\n\nStyling\n\nThe 2014 Lexus ES shares its looks with the outgoing model and in a way with the new IS sedans as well. So it is a blend of a wedge shape and something more traditional. From some angles, it is vaguely reminiscent of the LFA. Its grille is pronounced, its side character lines are muscular and its curves on the hood and trunk are attractive and not overdone.\n\nIts front end is more Lexus-like than before and its tail is more sedan-like than before. It has a more modern look without being overly aggressive and its design is not overly bland like some of its competitors. It is a good looking sedan but it will be a little too plain for some people.\n\nTruck Trend's 2014 Best Interiors trophy went to the new Lexus ES. It has an attractive dash that has been borrowed from other Lexus models but it is still nice and functional.\n\nTechnology\n\nI was surprised at how good the 2014 ES was. It was comfortable and quick and the transmission was a work of art. It was easy]" time="0.339"><properties><property name="score" value="0.61719006" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Did you think there\u2019s no such thing as free lunch? Wrong!\n\nI was an old punk. I ate cheaply. I ate unhealthily. I went out for food once a week, never paid more than $8 for a plate of rice and 2 pieces of chicken. Other times I ate popcorn and French Fries with my friends while watching movies in the cinema. And as I became an adult, I ate badly and grew fat.\n\nLast year, I decided to change my life. I started to save money, and from that day, I stopped eating cheaply.\n\nHere are some tips I picked up.\n\n1. Choose the cheaper meal of the day\n\nMcDonalds have only 2 types of meals that are cheaper than the rest. These are the McD Snack Meal and McD Value Meals.\n\nThe McD Snack Meal cost RM5.69, which includes a Chicken McSpicy or Filet-O-Fish, 2 Nuggets and a 375ml soft drink. The McD Value Meal costs RM8.19, which includes a Big Mac, a McSpicy or a Filet-O-Fish, 2 Nuggets and a 375ml soft drink.\n\nBoth meals are cheaper than the other meals that you can buy.\n\nThe cheapest meal of the day in McDonalds is the Cheeseburger meal.\n\n2. Eat at \u2018The\u2019 Restaurant instead\n\nIn Singapore, McDonalds is known as \u2018The\u2019 Restaurant. And you don\u2019t need to ask \u2018Where is the nearest McDonalds?\u2019, because in Singapore, \u2018The\u2019 Restaurant and McDonalds is the same thing.\n\nIt\u2019s a myth that \u2018The\u2019 Restaurant is more expensive than McDonalds. In fact, most of the meals that are available in McDonalds can be found at \u2018The\u2019 Restaurant.\n\nThe most expensive meal in \u2018The\u2019 Restaurant is the Set Dinner (Veg/Chicken). The meal costs $7.20. The most expensive meal in McDonalds is the Cheeseburger meal, which costs $4.29.\n\nAll other meals in \u2018The\u2019 Restaurant are cheaper than the other meals in McDonalds.\n\nFor example, the cheapest meal in \u2018The\u2019 Restaurant is the Curry Puff. The Curry Puff costs $3.10. The cheapest meal in McDonalds is the Cheeseburger meal, which costs $4.29.\n\n3. Eat from 7-Eleven instead\n\nThere are two reasons why I suggest you eat at 7-Eleven instead of McDonalds or \u2018The\u2019 Restaurant.\n\nThe first reason is, the food at 7-Eleven is almost as good as the food in \u2018The\u2019 Restaurant.\n\nThe second reason is, 7-Eleven sell drinks and fast food cheaper than McDonalds and \u2018The\u2019 Restaurant.\n\nFor example, I ordered a portion of Mac and Cheese in 7-Eleven. I ordered the Mac and Cheese as a take away, because I do not have any microwave in my office.\n\nThe cost of the Mac and Cheese is $3.30. And I bought a Pineapple Juice, which costs $1.30.\n\nThe total cost of my meal is $4.60. The same meal costs $4.79 in McDonalds.\n\nIt\u2019s true that the Mac and Cheese in 7-Eleven tastes a bit different from the one that I bought in McDonalds.\n\nIt\u2019s also true that the taste is not as good as the one that I can buy in \u2018The\u2019 Restaurant.\n\nBut it\u2019s true that the cost is almost the same.\n\n4. Avoid eating at the food court\n\nFood courts are expensive. The price of food sold at the food courts are almost the same as the cost of the same meal in a fast food restaurant.\n\nSo I\u2019ll suggest you avoid eating at the food court.\n\n5. Make food at home\n\nI make sure I cook once a day. I try my best to cook healthy meals. And the cost of the food that I make at home is much cheaper than the cost of a fast food meal.\n\n6. Eat with other people\n\nThe total cost of my meal depends on how many people are eating the same meal.\n\nFor example, I shared a Big Mac meal with my friend. The total cost of the meal was $8.20. That\u2019s because the meal cost $4.29 each.\n\nThe cost of the meal depends on how many people are eating the same meal. The cheaper meal is when I eat alone.\n\n7. Share the meal\n\nSometimes I share the meal with my partner. I usually share a meal with my partner once a week. I share the meal because I feel bad that my partner is eating alone while I\u2019m eating with my friends.\n\nIf I share the meal with my partner, the total cost is $4.60.\n\nIf I eat alone, the total cost is $4.79.\n\n8. Always look for a promotion\n\nIn McDonalds, \u2018The\u2019 Restaurant and 7-Eleven, there are always promotions.\n\nFor example, 7-Eleven and \u2018The\u2019 Restaurant sometimes offer discount on their drinks and fast food.\n\nSo I suggest you always look for a promotion before buying a meal.]" time="0.369"><properties><property name="score" value="0.00196249925" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[HapWanderlust September 1, 2011, 8:10 pm it's a very interesting product...\n\nAnonymous September 3, 2011, 12:30 am Thanks for the review, very interesting product and its feature seems to be very promising. However, I wonder what the maximum resolution would be at the time when you take picture and share it instantly, like facebook etc? Would it be just at the same resolution as of the regular picture or even better?\n\nGordon394 September 5, 2011, 12:11 pm This is one of the most intriguing products I've seen for a while. Will the quality be comparable to the smartphone quality, or will it be significantly worse? Are you sure you'll be able to get the same picture quality from the handset as with the phone tethered to a DSLR? I have to say I'm excited.\n\nMatthew September 5, 2011, 8:22 pm Thanks for the review, very interesting product. Do you know how much it will be available to the market and how it will be distributed?\n\nHiFiChris September 7, 2011, 3:56 pm Not sure about this. Love the idea but dont think it's ready. Biggest concern is image quality and would be pretty disappointing to take photos that look awful. I'd be worried about the image quality from the Nikon and would expect that some of the 'features' are just Nikon marketing. Probably best to wait until there are some real world reviews before investing.\n\nR.I. September 11, 2011, 1:16 pm This sounds amazing but what about the battery life?\n\nI really like this feature because it would be handy for traveling.\n\nPaul 4 October 25, 2011, 7:33 am would like to buy one but looks too expensive for a one off piece of kit\n\nPaul 4 October 25, 2011, 7:34 am would like to buy one but looks too expensive for a one off piece of kit]" time="0.374"><properties><property name="score" value="0.051545482" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The leadership of the world is not giving a serious thought to the future of the world and they are not ready to save the world. If this condition continues then the future of the world will be very difficult to predict.\n\n\n\n\n\n\n\n\n\n\n\nThe world is facing some serious problems and a few of them are as follows:\n\n\n\n\n\nClimate change\n\nUnemployment\n\nIncome inequality\n\nHunger\n\nResource scarcity\n\nPublic health\n\nMass migration\n\nInternal conflicts\n\nAchievements of humankind\n\nThe most important achievements of humankind have been its ability to observe, to experiment, and to reason. These capabilities have given humans the power to conquer the world and to dominate everything. The presence of powerful armies of humans has protected humans from the evil of other humans.\n\nPeople are now able to live in many different places and these different places have different types of people.\n\n\n\n\n\nAre people ready to save the world?\n\nThe world is facing many problems, however, the leaders of the world are not ready to save the world. If this condition continues then the future of the world will be very difficult to predict. The world is facing many problems, however, the leaders of the world are not ready to save the world. If this condition continues then the future of the world will be very difficult to predict.\n\nThe countries which are rich in wealth and resources will enjoy a good future, but the countries which do not have wealth and resources will face very difficult situations. The climate change has become one of the biggest problems of the world and the government of the world is not taking serious actions to tackle this problem.\n\nIf the governments of the world are unable to deal with this problem then the world will suffer a lot from this problem. The fact is that the world is in very big trouble. If there is no action to save the world then the future of the world will be very difficult to predict.\n\nIn order to deal with the current problems of the world, the governments of the world will have to make some very tough decisions.]" time="0.328"><properties><property name="score" value="0.0037418474" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A major renovation project at York University in Toronto is expected to run at least $26 million over budget, due to unanticipated problems that are forcing school officials to tear out and rebuild much of the work already completed.\n\nConstruction started in January 2014 on the $136-million project, which is meant to replace the York Arena, which opened in 1971, with a new, modernized facility with more seating and amenities.\n\nWork on the exterior of the arena was completed, but the contractor, Armel Holdings, noticed a problem when it came to the steel supports for the roof in June 2015, York University president Rhonda Lenton said.\n\n"We realized there were some structural concerns around the roof, so we paused the project," Lenton told CBC Toronto.\n\nSteel reinforcements will be needed to strengthen the roof, which was built with "soft" steel. (York University)\n\nWorkers discovered the roof of the arena had been built with "soft" steel, which is not as strong as the "hard" steel that is typically used for these types of projects, said Lenton.\n\nIn order to make sure the project is safe, crews need to rip out and rebuild about 50 per cent of the roof, at an estimated cost of $16 million.\n\n"We\u2019ve got to take this roof down," said Lenton.\n\n"We will be replacing the steel \u2014 the beams \u2014 and re-engineering the entire roof structure, as well as all the supporting beams that support the roof."\n\nSchool officials say they will be applying for additional funding to cover the cost of the roof replacement.\n\n"We will be going to the province for the additional funding that we will need, for sure," Lenton said.\n\nThey are also hoping to get money from the York University Foundation, which is a non-profit fundraising organization that operates separately from the university, according to its website.\n\nShe said she does not believe taxpayers will have to foot the bill for the additional cost.\n\nUnforeseen problems\n\nYork University president Rhonda Lenton says she does not believe taxpayers will have to cover the $16-million cost of rebuilding the roof. (CBC)\n\nThe problems do not end with the roof.\n\n"We realized that there were some structural issues around the seating, and we\u2019re replacing the seating, the wood seating in the arena," Lenton said.\n\nIn total, there will be 12 new levels added to the arena, along with a new heating and cooling system.\n\n"I think, because of the complexity of this building, we have to anticipate what other unforeseen problems may come along," Lenton said.\n\nIn December 2015, school officials sent a memo to university faculty and staff outlining the potential for "additional costs and associated risks" that could arise in the future.\n\n"We will continue to keep all our stakeholders updated as the project progresses and when we know more details about timing and scope of work," the memo said.\n\n"I\u2019m just waiting for more details," said Brian Lee, a York University professor and co-chair of the university\u2019s Local 79 union.\n\nLee said he thinks the university should have been more specific about the challenges facing the project.\n\n"There is no need for it to be kept secret," Lee said.\n\n"There\u2019s nothing secretive about construction projects."\n\nScheduling setback\n\nThe timeline for the completion of the project has been extended by more than a year, said Lenton.\n\nThe university had initially planned to have the arena ready by the 2017-2018 school year, but that deadline has been pushed back to the 2018-2019 school year.\n\n"We did have an aggressive schedule. We have to replace a roof in a building that is up on a hill," Lenton said.\n\nLenton also said there will be more parking spaces at the arena once the project is complete. The university had to remove between 300 and 400 parking spaces in order to begin the work.\n\n"I think we will have more spaces than we had before," Lenton said.]" time="0.422"><properties><property name="score" value="0.053930618" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05393062 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05393062
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[October 19, 2015\n\nOnce again we find ourselves reflecting on our own good fortune as we consider the news from Paris. We are not only alive, but many of us have access to a wealth of luxury, both intellectual and material, that few of our ancestors would have dreamed of. And we also have access to media that have transformed the world. One of my sons recently discovered the fascinating series \u201cHow the Universe Works\u201d (available on Netflix). This is a television show, with a high-tech production budget, and it is fascinating. It has some of the best images of the stars and planets ever produced, with an engaging story to go with them. The soundtrack alone is amazing. I highly recommend it. But it only works because of our technology, which has the power to tell stories across the globe.\n\nYou don\u2019t have to leave the planet for science to reach you. It\u2019s right there in your living room.\n\nToday I read a story in the paper about a study that examined the safety of exercise and high protein diets. This study was designed to answer a question that most of us have faced at some point: should I cut back on protein? My story pointed out that the study was very small and inconclusive, but the real story is about how we learn about our world and why this study is inconclusive. It is a story that has been repeated again and again. When new information comes out, we all read it with the same kind of judgment that you would apply to a restaurant: is this place worth my time and money? The more of it you eat, the more of it you want to read. When I read the story in the paper, I didn\u2019t try to understand the process by which the authors made their conclusions. Instead, I simply had a gut reaction: was the story worth the cost of the information it contained?\n\nThat is the only real question that matters when we choose what to read. This question is especially important today because there is so much information out there. When the costs of information are low, it becomes much easier to consume, and with this abundance comes the difficulty of choosing what to read. So we focus on our gut. And this is because we have a brain designed to make these kinds of choices, one that is driven by emotional needs, not rational ones. We are not designed to rationally evaluate the content of each article, but instead we are designed to make emotional decisions about what to consume.\n\nThis point was well illustrated by some research done by scientists at the University of Michigan. They had two groups of subjects: one that was told to read a story that was fun and amusing, and one that was told to read a story that was sad. Then they had them make some choices about the food they would eat for the next week. The group that had been reading the sad story ate 25% fewer calories than the group that had been reading the amusing story. Why? Well, they thought that food was a reward, and since they had been unhappy in the experiment, they cut back on the number of rewards that they would give themselves. This is a very rational process, but the very fact that they were not looking at the process that led them to their choice means that it had to be some form of emotional response.\n\nIn this way, we respond to information much like we respond to food. Food provides us with energy and pleasure, so it is important to choose it well. So we think in terms of gut decisions, not because they are the best ones, but because they help us to cope with our lives. Information is also a source of energy and pleasure, and so we choose it as well.\n\nBut while we are creatures that make emotional choices about our food and information, we also have other needs. These are needs that were emphasized by the process of evolution: needs to know about the world and needs to know about ourselves. So when we read articles, or watch television, or go on social media, we need to know whether they provide this type of knowledge as well.\n\nMost of the time we are looking for a story that is interesting, and that will hold our attention. But we also want a story that tells us something about our world. The better the story is, the more likely we are to learn from it. A story about calories and exercise might not be particularly interesting, but it is important for us to know. A story about the stars and planets might be fascinating, but it doesn\u2019t matter if it is a good story or not.\n\nThis is because we need information about our world to survive and to thrive, and we know this to be true because it is encoded in our DNA. Our brains have evolved to help us process the information that we receive, and so it makes sense that we]" time="0.384"><properties><property name="score" value="0.12178427" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[By \u201cspecial\u201d, I mean, \u201ca man who plays a very particular role\u201d. This man is a type of \u201cperformer\u201d, a type that is often put forward in business culture and in the literature of business leadership, and many men admire it and want to be seen as this type of man. It is the man who is never at a loss for words, and always knows exactly what to say, and is a good listener too. He has an instinctive understanding of people\u2019s moods and emotions. He is the man with the plan. He knows what\u2019s going on. He has a direct influence on others. He is never without a list of bullet-points, even if he\u2019s just going into the shop. He\u2019s good at handling pressure and he\u2019s a team player. He is the man who is looked to for a reaction.\n\nYou can call this type of man many different things. I am going to call him a \u201cbusiness executive\u201d, as it is most widely-used, but it is also a term that is rather different from the role of \u201cbusiness leader\u201d, and which I will also address. I am a business executive, and I have been a business executive for as long as I can remember, and I\u2019m a fairly typical example of a business executive. I think that most people reading this will find that it accurately describes at least a few men that they know.\n\nMost men aspire to this particular role. Some men even feel a burning need to play it. They will not be happy or feel satisfied in life unless they are in this particular role. They often judge themselves by it. They have a high level of need and drive to be a business executive.\n\nBeing a business executive is one of the \u201cgood\u201d ways to be a man, it is one of the ways in which men \u201cmake a difference\u201d and \u201chave an impact\u201d. It is also one of the ways in which men achieve \u201crespect\u201d, \u201crespect\u201d being an essential element in most men\u2019s internal lives. Many men do feel that it is through this role that they will achieve respect, in the same way that they might feel that they achieve respect in the rest of their life. They might not be consciously aware of this, and they may have a lot of other reasons for doing what they do, but respect is there, and is an important part of their motivation.\n\nThis type of role is one of the ways in which men achieve success and status. It is also one of the ways in which they can \u201cgain influence\u201d and \u201cchange things\u201d. It is the way that they \u201chelp people\u201d and \u201cchange things\u201d and \u201cmake a difference\u201d. It is the way that men can \u201chave a great career\u201d, and achieve \u201csuccess\u201d, and \u201cbe respected\u201d, and \u201cmake money\u201d.\n\nIt is not necessary to believe that these are the only or even the most important reasons for having a job. In my experience, most people, male and female, care about these things to some degree or other. I am not attempting to persuade anyone that these are \u201cunimportant\u201d things, I am not setting out to denigrate them. But it is important to understand that these are reasons for working. People, both male and female, need these things, and it is to these needs that they often respond when asked why they work.\n\nBusiness executives often find it easy to get good work. Many people are happy to trust their judgement, because they are good at understanding the people around them, and they can provide answers to difficult questions. They often find it easy to get good work, and they may have a number of people to choose from when looking for a new job.\n\nThey often feel that they are \u201cjustified\u201d and \u201chave a right\u201d to be in the position that they are in. They have earned it.\n\nThis type of role is very similar to that of \u201cbusiness leader\u201d, but these are very different roles. Many people confuse them, and use them as synonyms, and they are often referred to as such in business literature and the popular media. They are not synonyms. They are two different roles, and their differences can be seen in the relationship of the people around them.\n\nThe business executive is a man who is often very popular and well-liked. He is a man who is often admired. He is often seen as the man to turn to for answers. People come to him to find out what is going on, and to find out what to do. He often knows what to say, and he has an instinctive understanding of people\u2019s moods and emotions, and a quick and accurate understanding of the situations that he is faced with. He is a man who is often used by other people as a sounding-board, as a person to talk things over with, as a man to provide feedback and reaction.\n\nBut this is often not the case with the business leader. He often gets into trouble with the people around him, and he often gets an awkward response to his advice. He is not often looked to for feedback or reactions. He often does not feel that he has the understanding that he wants, and that he needs, and that he feels he deserves. He often feels that he is not looked to as much as he would like, and that people would turn to someone else if he were not there.\n\nThis type of role is the most important in a business organisation. It is not a role that most men can aspire to. In fact, I would say that most men do not aspire to it. And for many, if not most, men it is not a role that they can play well.\n\nFor many men, playing this role will lead them into unhappiness. They will feel frustrated and unhappy, and it is often a role that causes men to turn against the organisation that they are working for.\n\nMany men who try to be business executives will often find themselves in a difficult situation. Many men will find that they are working for organisations that do not have a business executive position. They will find that they are attempting to play a role that does not exist in the organisation that they are working for.\n\nMany men are unhappy when they try to be business executives. Many of them will be unhappy if they do not play that role.\n\nThere are, of course, many other types of men, and many other types of roles that they play. But this particular type of man and role is a very special one.\n\nA case study of a \u201cbusiness executive\u201d\n\nThis is a man who is very good at his job, a very clever and able man, a man who has an instinctive understanding of people\u2019s moods and emotions, and who has a natural ability to speak effectively and confidently to other people. He has a good understanding of other people, and he has an ability to work with other people. He understands other people\u2019s motivations and he understands what is important to them. He has a good understanding of what people will do, what they will say, and what they will not say, and he understands what is going to happen and how things will turn out. He understands people\u2019s moods and emotions. He is quick to understand how things are going to turn out, and he is quick to make decisions.\n\nThis man is a good communicator. He is the type of man who people turn to for reactions. He is the man who knows what to say, and who knows how to say it. He is good at dealing with difficult people, and he can handle difficult situations. He is good at explaining things to other people. He is good at handling pressure, he is good at dealing with crises, and he is good at giving people confidence.\n\nThis man has a good understanding of his organisation, and he has a good understanding of his work. He is often the man that people go to when they need information. He is the man who has a good overview of the situation.\n\nThis man has a good understanding of his organisation\u2019s finances. He has a good understanding of his organisation\u2019s future, and he can see things that other people cannot see. He is the man who knows what is going to happen. He is a man who has the answers, and a man who knows what to do. He has the information that other people need. He has an instinctive understanding of his organisation\u2019s situation. He has a good overview of the situation. He is good at taking decisions.\n\nThis man can be effective at many things. He is good at working with other people. He is good at providing feedback. He is good at explaining things to people. He is good at providing support and comfort to people. He is good at listening to people and taking them seriously. He is good at convincing people. He is good at getting people to agree to things. He is good at persuading people. He is good at making plans. He is good at using his initiative. He is good at seeing what is going on. He is good at moving things forward.\n\nThis man is used to being respected, and he is used to people listening to him. He is used to being popular. He is used to having an influence on people. He is used to]" time="0.664"><properties><property name="score" value="0.005715872099999999" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[ABC News Good Morning America ABC Feb 10, 2013 7:00am PST\n\n. he is married to the former martha lee hawkins. he has two children, bill and samantha. >>> it is an amazing story about someone you may have never heard of. he wrote a best-seller and he just turned 13. abc's ginger zee is here with more. good morning, ginger. >> reporter: good morning, robin. allen barra who is not quite yet a teenager, he is a writer and he has a deal with harpercollins. >> i have been interested in writing for a very long time. i was always trying to write different kinds of books. >> when he was 10, he started a diary. he had it bound and published. >> it was for a school project but the book was an instant hit. "i wrote the diary of a wimpy kid" was one of the top selling books of 2010. the second book, "the third wheel" was a number one best seller. he and his sister had started the website, kidwrite.com to promote their stories. now at 13, he has a deal for a third book. he plans to use the money to pay for college. >> i'm hoping to go to brown and to study international relations and history. >> his publisher is thrilled with his success. >> he has a rare combination of]" time="0.339"><properties><property name="score" value="0.65807813" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This article is about the combat ability. For the status effect, see Poison\n\nFor the Hunter creature, see King black dragon\n\nVenom is a poisonous status effect inflicted by many creatures, and is inflicted by the dragon dagger special move. It deals low damage over time, reducing the player's defence level, and decreasing the effectiveness of protection prayers and similar effects. There is no venom available as a spell in RuneScape.\n\nWhen venom is applied, a timer of 16 seconds begins and the afflicted player receives the message "You are beginning to feel venomous!" This timer can be frozen using either an antipoison, or an antifire potion if the dragon dagger special attack is used against the player.\n\nContents show]\n\nSigns and symptoms Edit\n\nIf you get hit by poison, you may notice the following symptoms:\n\nInability to eat while venom is active (unless the player is using food that heals life points only)\n\nInability to cure poison with antipoison or heal poison using poison cures whilst the venom is active (unless the player is using antipoisons or super antipoisons)\n\nA decrease in defence level\n\nVenom damage Edit\n\nPoison has a poison damage value of 10 + 4 * n {\\displaystyle 10+4*n} , where n {\\displaystyle n} is the number of hits received. This means that the average damage of a venom hit is 22.5% higher than the hit's base damage. The maximum poison damage is 120 + 10 * n {\\displaystyle 120+10*n} , which occurs when the player is hit 16 times by venom.\n\nAs with other damage over time effects, poison damage is not affected by damage modifiers or protection prayers.\n\nResistance Edit\n\nThe player's resistance to venom is related to the player's Defence level, and reduces the damage done by venom accordingly. A player with level 90 Defence or higher will be almost immune to the venom of most dragons, while those with a lower Defence level will take considerable damage from even low-level dragons. The dragon dagger's special attack provides temporary immunity to poison from venom, however this immunity is lost when the dagger's special attack is used up, or if the player unequips the dagger.\n\nTrivia Edit\n\nEven though the Venom poison effect was not in RuneScape Classic, a poisoned player would say the same thing: "I feel a little woozy..."]" time="0.277"><properties><property name="score" value="1.3813539" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Description\n\nOn 2 June 1945 in the Tiergarten of Berlin, hours after Hitler had committed suicide, Major-General Hans Krebs (with his right hand raised) signed the German instrument of surrender. The capitulation of all German forces to the Allies was unconditional.The Reich Chancellery in Berlin was chosen for the signing. Soviet leader Joseph Stalin had insisted on a place in Berlin, his army had reached the city ahead of the others, and he had expressed a wish to receive the capitulation in his capital. The same location had been used for the signing of the surrender of Germany by the Russian army in November 1918. The others present were the Soviet military commander Marshal Georgi Zhukov, U.S. General of the Army Dwight D. Eisenhower, and British Field Marshal Sir Bernard Law Montgomery, whose signatures appear at the bottom. This moment is often said to be the end of World War II, but is not the date used for official purposes. The terms of the surrender were finally worked out in Esen, on the river Mulde, between 24 and 27 April 1945, and approved by Eisenhower and Zhukov on 4 May. The official document (the text of which is in the final picture) was signed in Berlin in the evening of 8 May. It was ratified by the Soviet government on 1 September 1945 and by the other allies later.]" time="0.271"><properties><property name="score" value="0.07386004" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07386004 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07386004
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nSenator KROGER (Minister for Population and Immigration) (10:46 AM) \u2014I seek leave to make a short statement.\n\n\n\nThe PRESIDENT \u2014Leave is granted for one minute.\n\n\n\nSenator KROGER \u2014The Leader of the Opposition indicated yesterday that he would be referring to the legal framework in relation to the privatisation of Telstra. This is not surprising given that the issue of Telstra was discussed at the last election and he has been a long-time supporter of privatisation.\n\nIt is interesting to note, though, that it is the opposition who have failed to produce their privatisation plan\u2014not that they have one. And they have failed to produce it for one simple reason: it will have to meet with the ACCC guidelines in relation to Telstra. I was very happy to provide those guidelines to the opposition. I can provide them again this morning if they want.\n\n\n\nSenator Campbell \u2014We know you are the legal supremo.\n\n\n\nThe PRESIDENT \u2014Senator Krueger, on your own account, to get a bit of latitude\u2014I think you have five minutes now.\n\n\n\nSenator KROGER \u2014Thank you, Mr President. What I can do is provide them again this morning, but if the opposition has the same rhetoric it has used at the last election\u2014and I know it is used at every election by the leader of the opposition\u2014then it will fail to have its proposal examined in any great detail by the ACCC. It is not because we have an axe to grind, it is because the opposition have an axe to grind. But it does not pass the ACCC test, and it is interesting that they do not want to have that detailed examination of their proposal.\n\nLet us have a look at what Telstra said yesterday. The headline, of course, in the Australian Financial Review is \u2018Telstra asks regulator to speed up broadband overhaul\u2019. You would be very happy about that, Senator, wouldn\u2019t you?\n\n\n\nSenator Campbell \u2014We are.\n\n\n\nSenator KROGER \u2014The point is that you have not said what the rates are. But if you had done your job in the last election and had produced your plan, then the ACCC would have had the option to have you examine your plan and to determine what the rates should be and whether they could be extended. What we have done is ensure that the interest of consumers and business in this country are protected. We have done it by putting in a position where the ACCC will have the opportunity to examine any privatisation proposal that the opposition has.\n\nAnd, Mr President, there are a number of aspects of Telstra that have been raised by the opposition. They are in the policy documents that the opposition are putting around. There is no doubt that those aspects of Telstra will be examined by the ACCC, as will be anything else they may have up their sleeve.]" time="0.297"><properties><property name="score" value="0.9389286" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The government has set up a panel to study the RBI's recommendation on high-denomination currency notes, Economic Affairs Secretary Shaktikanta Das said on Monday.\n\n\n\nThe high-powered committee will take a decision after it gives its recommendations, he said.\n\n\n\nThe Reserve Bank had last week recommended withdrawal of Rs 500 and Rs 1,000 currency notes to curb funding of terrorism and tackle the problem of counterfeit notes.\n\n\n\nThe decision to set up the committee was taken at a high-level meeting chaired by Finance Minister Arun Jaitley and attended by top officials from the Finance Ministry and the Reserve Bank.\n\n\n\nDas said the government would take a decision on the recommendations of the RBI only after the panel submits its report.\n\n\n\n"The committee has been set up, which will look into the matter and come up with its recommendations. The government will take a call only after the recommendations are submitted," Das said.\n\n\n\nAsked if the panel would be headed by a member of the Prime Minister's Office (PMO), he said: "No, it is headed by a senior Finance Ministry official and members of the RBI."\n\n\n\nThe panel is likely to comprise senior officers from the Finance Ministry and RBI.\n\n\n\nThe panel is likely to meet on Tuesday, sources said.\n\n\n\nOn a query on the option to withdraw the new series of Rs 500 and Rs 2,000 notes, Das said: "It is a hypothetical question.\n\n\n\n"The government will take a call on the RBI's recommendations only after the panel submits its recommendations."\n\n\n\nIn a bid to curb funding of terror, the RBI had recommended withdrawal of the bank notes of Rs 500 and Rs 1,000 denominations.]" time="0.315"><properties><property name="score" value="0.118575096" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Social media company Twitter Inc said it suspended about 70 million accounts in the past quarter to curb abusive behaviour, but its active user base grew about one per cent in the same period, disappointing investors.\n\n[SAN FRANCISCO] Social media company Twitter Inc said it suspended about 70 million accounts in the past quarter to curb abusive behaviour, but its active user base grew about one per cent in the same period, disappointing investors.\n\nThe company said it has seen continued "abuse, harassment, and other kinds of behaviours that distort and distract from the public conversation."\n\n"The best defence against these challenges is a combination of technology and people," Twitter chief executive Jack Dorsey said in a statement.\n\nThe company said it also saw some growth in its advertising base, adding that it expected to generate US$650 million in revenue in the fourth quarter, topping market expectations.\n\nsentifi.com Market voices on:\n\nTwitter also announced it would begin notifying users of covert political influence efforts, after having blocked such suspicious activity in the past.\n\nThe changes came as the company reported a profit of US$91 million for the third quarter, which was in line with market expectations.\n\nTwitter shares dipped slightly in after-hours trade, but gained 2.6 per cent over the last 12 months.\n\nTwitter said it saw a 1 per cent user growth in the third quarter, adding three million monthly active users.\n\nThe company's daily active users grew 12 per cent year-on-year, a modest increase as it continues to grapple with efforts to combat abusive behavior and harassment.\n\nThe company also said it would start to notify users of "malicious automated accounts" in a move that comes after Facebook and Google have taken similar steps.\n\nIn June, Twitter updated its terms of service and privacy policy to clarify its rules on the use of bots, which are a favourite of fraudsters and malicious actors, such as Russian propagandists.\n\nTwitter said it "dramatically reduced" the number of suspicious log-ins that could have led to accounts being compromised.\n\nWhile the company continues to suspend millions of accounts, critics have complained that the company has not done enough to police activity on the platform.\n\nOn Thursday, Mr Dorsey said Twitter would "double-down on the most important factor of our success: You."\n\nWhile he said the company did not expect to be free of abuse or misuse, it wanted to ensure the conversation on Twitter remained healthy.\n\nTwitter said the problem was particularly severe in private, one-to-one conversations, where the rate of harassment was five times higher than the regular feed.\n\n"We want to increase the collective health, openness, and civility of public conversation, and to hold ourselves accountable towards progress," said Twitter's chief executive.\n\n"We are making progress as we go."\n\nAFP]" time="0.752"><properties><property name="score" value="0.016161919" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01616192 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01616192
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Culture of Empathy: Bats and Bells\n\nCulture of Empathy: Bats and Bells\n\nYou are likely familiar with the cultural myths surrounding the bat, often involving vampires and bloodsuckers, evil demons or even winged creatures that steal one\u2019s soul. In the Western world, the bat has for centuries, and for many people even today, been associated with negativity and danger.\n\nThe bat, on the other hand, is a highly empathetic creature. Bats have amazing social connections and perform complex rituals that ensure the welfare of their group members. They are amazing hunters of both insects and fruit, thanks to their very good eyesight and a large brain for processing data. Because of their social abilities and prey-catching skills, the bat has been hunted and killed.\n\nAccording to the Bats of Trinidad and Tobago website, \u201cSince bats are prey for many animals, the loss of bat populations due to predation is widespread. Predatory birds and snakes, for example, may take a large number of bats from a colony.\u201d\n\nI often wish for such care, consideration and connection when I\u2019m interacting with other people. I often wonder what it would be like to have relationships built on respect, reciprocity and trust. My hope is that someday all the people in the world will connect with their hearts and brains, and practice empathetic responses to others.\n\nThough a long time ago, I have even heard the birds and bats say\u2026\n\nCome on baby, light my fire.\n\nI wanna be burned, and baby, then you\u2019ll desire.\n\nTo my readers, I\u2019d like to introduce a new piece of music that I recorded on a ukulele. I\u2019m not sure if I\u2019ve mentioned this before, but my instrument of choice is the ukulele. I\u2019ve been studying classical guitar for a few years and I\u2019m not so sure I\u2019ll ever play anything other than the uke.\n\nThe song I am introducing is a tune that came to me as I was studying bats for my Culture of Empathy book. I was curious to learn more about the bat\u2019s in Trinidad and Tobago. Their indigenous names include:\n\nBakabak (Carib)\n\nAlik-Bakabak (Bhojpuri)\n\nBakabak-a (Bhojpuri)\n\nBakabak-fefa (Creole)\n\nBakabak-fura (Creole)\n\nBakabak-ki-bot (Creole)\n\nBakabak-ra (Creole)\n\nBakabak-rah (Creole)\n\nBakabak-rah-alik-bakabak (Creole)\n\nBakabak-rah-mich (Creole)\n\nBakabak-rah-te (Creole)\n\nBakabak-ra-te (Creole)\n\nBakabak-ra-te-bakabak-ra (Creole)\n\nBakabak-ra-te-pumpu-bakabak-ra (Creole)\n\nBakabak-ra-te-pumpu-alik-bakabak-ra (Creole)\n\nBakabak-ra-te-pumpu-bakabak-ra-alik-bakabak-ra (Creole)\n\nBakabak-ra-te-pumpu-mich-alik-bakabak-ra (Creole)\n\nBakabak-rah-te-pumpu-mich-alik-bakabak-ra (Creole)\n\nBakabak-rah-te-te-mich-alik-bakabak-ra (Creole)\n\nBakabak-tite (Creole)\n\nKaiyot (Indian)\n\nMalik-kabaak (Indian)\n\nMakai-kuar (Indian)\n\nMas (Indian)\n\nPumpu (Indian)\n\nUkuar (Indian)\n\nXalk-ra-te (Creole)\n\nXalk-rah-te (Creole)\n\nZokak-ra-te (Creole)\n\nZokak-rah-te (Creole)\n\nZokak-rah-te-pumpu-alik-bakabak-ra (Creole)\n\nZokak-rah-te-pumpu-bakabak-ra-alik-bakabak-ra (Creole)\n\nZokak-rah-te-pumpu-bakabak-ra-te-pumpu-alik-bakabak-ra (Creole)\n\nZokak-rah-te-pumpu-bakabak-ra-te-pump]" time="1.100"><properties><property name="score" value="0.002111175" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Shopper They came so fast, the colour is more bright than I expected but the quality is nice, my size is M and it was very good\n\nD***a I ordered the size M, took the XXL. Perfectly fit the body and did not stretch. Came to the moscow region for a month. I like the color. On the parameters og 84-61-86-88-chest 107.\n\nE***a Delivery is fast. The size is chosen by the table.\n\nG***o I haven't received the product yet, but the customer service of the seller is really good.\n\nA***n It's for the first time that I ordered something from this seller. The order was done at 11:40, and I already received it at 18:08, the parcel came from China to Romania in 4 days! The products are high quality, and the sizes are pretty well chosen. I recommend the store and will buy from it again!\n\nE***a Very cool dress, ordered as a gift, but not what i expected. Ordered and delivered quickly, but i liked more with a tie on the neck.\n\nM***s Perfect. I am a little large and ordered a size bigger so it will be nice and loose\n\nO***o I ordered two sizes bigger. Came up perfectly. I recommend to order more size for a comfortable fit.\n\nM***i Very good quality, it's a little big on the shoulders but it's ok :)\n\nA***a Quality is excellent. Everything is neatly stitched, i advise you to buy!\n\nG***g I am satisfied, beautiful fabric, high quality, very comfortable, thanks for the gift.\n\nO***e Same as the picture. Very cute and perfect fit! Recommend\n\nT***o So beautiful and cool i love it\n\nA***z I recommend the product. Come nicely wrapped and the material is good. Very nice\n\nD***s Perfect same as the picture, it arrived very fast to spain\n\nS***e The dress is perfect, the colour is exactly as the picture. It's also nice and soft. It was a gift for my mom and she is delighted!\n\nC***o The product is perfect. I am super happy with it!\n\nT***t My daughter is happy with the product, arrived in spain in 30 days, thanks!\n\nD***a Looks like the picture. Very good product, very comfortable\n\nG***e super, ty\u0142ek takiej wyjdzie dobrze umiem zaryzykowa\u0107 ;)\n\nM***a Perfect. This is the second time i bought this product, and i am still very happy. Thank you\n\nT***t This dress was the same as the photo. It was a gift for my mother and she was super happy.\n\nG***n I liked the product and it arrived in perfect condition.\n\nL***i Beautiful. This is the second time i buy it, very beautiful.\n\nC***t Love it!!!\n\nS***n The order was received very fast. The product is exactly the same as the description. It's very beautiful, quality, nice, soft and comfortable. Thank you very much!\n\nA***n Ordering more colors\n\nB***t Very good fabric\n\nD***o I got the dress on time, fits good, the colour is accurate. Thanks\n\nB***r Great quality and looks exactly like the picture.\n\nA***h I am very satisfied with the product, the only thing is that the photo in the arm is white. I do not think it is white in reality. Everything else is very good.\n\nM***y Very cool dress! Looks very good on. Good fabric! Very fast delivery!\n\nD***a Fast shipping and a good product! I'm satisfied. Thank you very much.\n\nShopper Very good quality. Thank you seller, the product is the same as the photo.\n\nN***n The order arrived on time. The dress is good. The material is pleasant. I liked it. I recommend the product. Thank you.\n\nShopper The product arrived very fast, the product is exactly like the photo, i recommend the product, it came with a good packaging.\n\nL***y Very good quality, the fabric is pleasant, thank you!\n\nShopper Product matches the description, quality at altitude\n\nG***a Fast shipping. Very good quality. Very comfortable.]" time="0.298"><properties><property name="score" value="0.016118063" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Washington (CNN) On his way to a diplomatic crisis with Qatar, President Donald Trump spent part of the day Tuesday praising a trio of Middle East leaders who are strong allies in the fight against ISIS and terrorism, as well as helping to crack down on Iran.\n\nIn the course of a 50-minute speech in Saudi Arabia to a group of leaders of more than 50 Muslim countries, Trump mentioned the names of three leaders: King Salman of Saudi Arabia, King Faisal of Iraq and President Abdel Fattah el-Sisi of Egypt. He described them as "friends" who had "brought calm" to the region.\n\n"This is a battle between barbaric criminals who seek to obliterate human life, and decent people of all religions who seek to protect it. This is a battle between good and evil," Trump said, according to a White House pool report. "If we do not stand in uniform condemnation of this killing, then not only will we be judged by our people, not only will we be judged by history, but we will be judged by God. This is not a battle between different faiths, different sects or different civilizations. This is a battle between barbaric criminals who seek to obliterate human life, and decent people of all religions who seek to protect it. This is a battle between good and evil."\n\nIt's an evolution for Trump, who had attacked the trio of Middle East leaders during the campaign and, after he won, avoided being too complimentary about them.\n\nAnd in the days before his speech, Trump had been on the attack again against Qatar. He had bashed the Gulf country in a series of tweets for alleged "funding of terrorism," which triggered the diplomatic rift. Trump went to Saudi Arabia on his first trip abroad as President.\n\nTrump has backed the Saudi-led boycott of Qatar and threatened "severe punishment" against Doha for its alleged "sponsorship of terrorism," according to a Qatari official who spoke with CNN.\n\nTrump's comments about Salman and Faisal came just after he spoke about the Iran nuclear deal. Trump said it was an "embarrassment to the United States" and called it "one of the worst and most one-sided transactions the United States has ever entered into."\n\nIt is also not the first time Trump has praised King Salman. After his inauguration, Trump made a phone call to the king. He called him a "very wise person who wants to see things get much better rapidly" and called their relationship "extremely good."\n\nKing Salman was the first world leader to speak to Trump after he was inaugurated, and Salman joined Trump in a visit to a home in Riyadh that was built for families of the victims of the 9/11 terrorist attacks in the US.\n\nSaudi Arabia's King Faisal was assassinated in 1975.\n\nBut despite that history, Trump has only been complimentary about the Saudis, but not in the way some have accused him of being too cozy with Russian President Vladimir Putin. The Saudis helped him create the first page in his Middle East policy.\n\nHe praised the Saudis after he won the election, saying, "Saudi Arabia and I get along great." He had spoken about it as a campaign issue, saying in March 2016 that he "would like to protect Saudi Arabia" but that the country is "going to have to help us economically" in the fight against ISIS.\n\nTrump had also said in December 2015 that he was against the "concept of bombing" and was for a strong intelligence-gathering effort instead. He said then, "It is a mistake to bomb the oil fields. You bomb the oil fields, you kill civilians, you destroy the oil fields. They are going to get into something else. They are going to produce and sell it someplace else. It will not be a pretty picture."\n\nAt the time, Trump was being accused of being naive about the region and for giving a nod to terrorists when he questioned whether the US should be spending money and lives to intervene in Syria.\n\nTrump has been criticized for appearing to blame Qatar for the current state of affairs in the region. Some, like the U.S. ambassador to Qatar, have said Trump is trying to improve ties with Qatar in order to fight terrorism.\n\nTrump also spoke during his visit to Saudi Arabia about his support for the monarchy.\n\n"We are not here to lecture. We are not here to tell other people how to live, what to do, who to be or how to worship. Instead, we are here to offer partnership, based on shared interests and values," Trump said. "We are not here to tell other people how to live, what to do, who to be or how to worship. Instead, we are here to offer partnership, based on shared interests and values."]" time="0.338"><properties><property name="score" value="0.07551066" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07551066 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07551066
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Dei aperti oggi dalla Regione Piemonte gli uffici per il trasferimento delle attivit\xe0 dalla Sic - Societ\xe0 Industria Costruzioni - al costituendo cda di Sistri - Sistema Territoriale della ricostruzione e riqualificazione idrogeologica, in sintesi una sorta di Anas dei Comuni. Le sezioni di Pinerolo, Chieri, Torino e Moncalieri sono state create per i cittadini in transito, anche se in questo momento non ci sono pendenze che li richiedono. La sede di Pinerolo \xe8 presso la sede di Regione Piemonte in via Monsignor Forno, 2, ma l'appuntamento \xe8 dalle ore 10 alle ore 13, dal luned\xec al venerd\xec. Le altre saranno gestite da Bologna, dove in via Crispi al n.8 e via Mascagni n.6. Lo staff incaricato per la giornata di oggi prender\xe0 i certificati in essere in Sic e, qualora non si tratti di ricostruzione, provveder\xe0 a stamperli in copia fotostatica, inserire nella pratica un modulo che costituir\xe0 richiesta di trasferimento e conservare la copia nei propri archivi. I cittadini in possesso del certificato in essere, o del sostitutivo del titolo abilitativo, dovranno recarsi nell'ufficio e presentare la pratica con copia dei documenti. Si potr\xe0 quindi ritirare l'atto compilato ed essere abilitati all'uso della nuova regolazione. Se la richiesta non \xe8 espressa per opere di ricostruzione, gli uffici provvederanno al trasferimento alla nuova amministrazione. Le varie competenze dei Comuni (ad esempio, le pavimentazioni, che hanno ottenuto una nuova regolazione della Regione) dovranno essere portate in una seconda fase, per i successivi trasferimenti. Si tratta, in tutti i casi, di interventi di adeguamento alla Legge Madia (230/2010), che non ha ancora recepito la normativa regionale del 2014, sulla riordino degli uffici comunali. Con le nuove modalit\xe0, non ci saranno pi\xf9 sezioni di competenza territoriale, ma saranno dei centralini di ambito regionale. In Regione ci saranno anche uffici "complementari", dove sar\xe0 possibile fare le pratiche per il reddito di cittadinanza, che dovranno poi essere trasferite all'ufficio dell'Inps.]" time="0.372"><properties><property name="score" value="0.36309582" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Efren Castillo on Boxing\n\nWith the recent announcement of Canelo Alvarez vs. Gennady \u201cGGG\u201d Golovkin and Vasyl Lomachenko vs. Nicholas Walters for May 2, the sport of boxing is picking up some good steam. On Saturday, Danny Garcia and Robert Guerrero will be fighting in the co-main event of the Alvarez-Kovalev undercard, and they are both in the top five of my pound-for-pound list. The winner of this fight will be the mandatory challenger to Keith Thurman for the WBC welterweight title.\n\nThis fight is just one example of how competitive boxing has been in recent years. There are so many great fighters that we could have one of the best years in boxing in recent memory. But before we go any further, let\u2019s take a look at the four fights that were announced this past week.\n\nFor Alvarez-Kovalev, it was the best fight that could have been made at this time in boxing. In the beginning of 2015, the year started off great with Miguel Cotto vs. Canelo Alvarez, which was supposed to be one of the best fights of the year. But instead, it was a non-event and was a flop. Both fighters looked bad, and the fans were disappointed. That being said, the promoters realized that Cotto vs. Alvarez II would not do great numbers, so a rematch was out of the question.\n\nWith Cotto leaving Top Rank, there was a gaping hole in the middleweight division. Alvarez wanted to stay at 154 pounds, but the only option for him was to go up to 160 to fight the middleweight champion Gennady Golovkin. But with Golovkin only having one fight in 2016, and the third bout against Martin Murray in March, the timing could not have been any better for this fight.\n\nWhile the fight is taking place in Las Vegas, it should not hurt the Mexican fighter. The best fights involving Mexican fighters in Las Vegas have always been ones where the opponent is big in name and popularity. Alvarez has already faced Floyd Mayweather, Erislandy Lara, Alfredo Angulo, James Kirkland and Miguel Cotto. He has had two pay-per-view fights in Las Vegas, and he has never been hurt by the size of the city or venue.\n\nAlvarez is favored to win this fight, but that could all change if he loses to Golovkin. For those that don\u2019t know, boxing fans can be ruthless, and one loss can change everything. But in the end, the fans and the boxing industry will be the biggest winners in this fight.\n\nThen we move on to Lomachenko vs. Walters. These two fighters have two of the most awkward and beautiful styles in boxing. With Lomachenko being at 122, and Walters being at 130, this is a fight that could not be missed. Walters will be giving up eight pounds to the Ukrainian, but that is not a huge factor in this fight. Lomachenko is only about 1.5 inches shorter than Walters, and he is naturally taller.\n\nThe big difference between these two fighters is the lack of power by Walters. He has knocked out 34 out of his 35 opponents, but his most recent fight was against IBF super featherweight champion Miguel Berchelt. Walters could not KO Berchelt, and he lost a 12-round decision. Walters does not have a huge knockout percentage, and Lomachenko does not get knocked out. So it will be interesting to see how this fight plays out.\n\nThe fight that I am looking forward to the most is Garcia vs. Guerrero. These two fighters are very competitive in their division, and they are both in their prime. Garcia has already had two losses this year, but they were to Shawn Porter and Keith Thurman. Those two fights were competitive and competitive in style. But Garcia showed heart and talent in both of those fights.\n\nGuerrero is coming off of a very exciting win over Andre Berto in November. He was hurt several times in the fight, but he pulled out a split decision. Garcia is coming off of a draw with Porter in March, and he is currently ranked No. 3 by the WBC. While Guerrero is ranked No. 4, he has the ability to beat Garcia. Both fighters are fairly similar in style, and if Garcia is smart, he will win this fight.\n\nThe last fight is a big one: Nicholas Walters vs. Vasyl Lomachenko. I am hoping that this fight does not happen until 2018. The reason is because Lomachenko has a fight with Guillermo Rigondeaux on Dec. 9, and Walters is fighting in March. I want to see both fighters in top condition in this fight. With a possible date of April 28, 2018, it will give the fighters plenty of time to prepare.\n\nI believe that this fight could possibly happen before the end of the year. With Walters fighting on March 4 against Jason Sosa, and Lomachenko fighting on Dec. 9, it could set up this fight for the end of the year. Both fighters are on HBO, and the boxing industry will be happy if this fight takes place. Walters has already fought Lomachenko once in 2013, and Lomachenko is undefeated since that fight.\n\nThe only fight that I am looking forward to more than this one is GGG vs. Alvarez. But this is the second most anticipated fight of the year for me. Walters has proven that he can fight great fighters, but he has not faced anyone that could compare to Lomachenko. Walters was supposed to fight Miguel Marriaga on Nov. 26, but it was cancelled due to his weight.\n\nFor Lomachenko, he has had two tough fights against Guillermo Rigondeaux and Jason Sosa, and they have both been challenging fights for him. Lomachenko has fought great fighters such as Nicholas Walters, Gary Russell Jr., and Orlando Salido]" time="0.728"><properties><property name="score" value="0.018975941000000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Self Portrait was a virtual representation of one of Ratonhnhak\xe9:ton's genetic memories, relived by Desmond Miles in 2012 through the Animus.\n\nContents show]\n\nDescription Edit\n\nRatonhnhak\xe9:ton was getting dressed when he heard the sound of barking. Worried that the guards were alerted to his presence, he exited the room, only to find a domesticated wolfdog.\n\nDialogue Edit\n\nRatonhnhak\xe9:ton: (frightened) Who's there?\n\nThe wolfdog growled.\n\nRatonhnhak\xe9:ton: Shush!\n\nRatonhnhak\xe9:ton: (calming) Hush!\n\nRatonhnhak\xe9:ton: Good boy.\n\nRatonhnhak\xe9:ton: Now, where'd you come from?\n\nRatonhnhak\xe9:ton: What a curious creature.\n\nRatonhnhak\xe9:ton: You are one of the villagers' pets, no?\n\nRatonhnhak\xe9:ton: The closest village is east of here.\n\nRatonhnhak\xe9:ton: And they keep you locked up, like an object?\n\nRatonhnhak\xe9:ton: That is not right.\n\nRatonhnhak\xe9:ton: I will take you where you can run free.\n\nThe wolfdog barked and followed Ratonhnhak\xe9:ton.\n\nRatonhnhak\xe9:ton: There, now.\n\nRatonhnhak\xe9:ton: Out of here, boy.\n\nRatonhnhak\xe9:ton: We need to be quick.\n\nRatonhnhak\xe9:ton: Come on!\n\nRatonhnhak\xe9:ton: I have a plan, but I cannot do this alone.\n\nRatonhnhak\xe9:ton: You will help me, won't you?\n\nRatonhnhak\xe9:ton: I have a job for you.\n\nRatonhnhak\xe9:ton: Good boy.\n\nRatonhnhak\xe9:ton: I am going to distract the guards.\n\nRatonhnhak\xe9:ton: You must go out the back door, and fetch help.\n\nRatonhnhak\xe9:ton: There are warriors who are eager to prove themselves.\n\nRatonhnhak\xe9:ton: They are in the forest to the south.\n\nRatonhnhak\xe9:ton: Go now!\n\nRatonhnhak\xe9:ton: I'll distract them!\n\nRatonhnhak\xe9:ton: There's a way out this way!\n\nRatonhnhak\xe9:ton: What?\n\nThe wolfdog growled and rushed past Ratonhnhak\xe9:ton.\n\nRatonhnhak\xe9:ton: Oh, well.\n\nRatonhnhak\xe9:ton: Guess I'm not alone after all.\n\nRatonhnhak\xe9:ton: But we are two, and they are many!\n\nRatonhnhak\xe9:ton: If you'll give us some cover, we can...\n\nRatonhnhak\xe9:ton: (sighing) It was worth a try.\n\nRatonhnhak\xe9:ton: I'll hold them off, but you need to fetch help.\n\nRatonhnhak\xe9:ton: You remember the warriors in the forest, yes?\n\nRatonhnhak\xe9:ton: Go!\n\nRatonhnhak\xe9:ton: No, you're not leaving me here!\n\nRatonhnhak\xe9:ton: You can come with me, or fetch help, but you are not leaving me here.\n\nRatonhnhak\xe9:ton: I have an escape route.\n\nRatonhnhak\xe9:ton: Follow me!\n\nRatonhnhak\xe9:ton: Good dog!\n\nRatonhnhak\xe9:ton: The steps are there, come!\n\nRatonhnhak\xe9:ton: Come on!\n\nRatonhnhak\xe9:ton: What are you waiting for?\n\nRatonhnhak\xe9:ton: Good dog.\n\nRatonhnhak\xe9:ton: A woman!\n\nRatonhnhak\xe9:ton: How did she get in here?\n\nRatonhnhak\xe9:ton: Who is she?\n\nRatonhnhak\xe9:ton: Can she help us escape?\n\nRatonhnhak\xe9:ton: (startled) Is that you?\n\nRatonhnhak\xe9:ton: Are you a wolf?\n\nRatonhnhak\xe9:ton: What are you doing here?\n\nRatonhnhak\xe9:ton: If you want to leave with me, we need to move!\n\nRatonhnhak\xe9:ton: We need to be quick!\n\nRatonhnhak\xe9:ton: (giggling) You'll protect me, yes?\n\nRatonhnhak\xe9:ton: Yes, yes.\n\nRatonhnhak\xe9:ton: Oh, it's so dark!\n\nRatonhnhak\xe9:ton: There must be a way out!\n\nRatonhnhak\xe9:ton: There are, but I cannot see where they lead!\n\nRatonhnhak\xe9:ton: You could sniff them out.\n\nRatonhnhak\xe9:ton: Good boy!\n\nRatonhnhak\xe9:ton: Oh, no!\n\nRatonhnhak\xe9:ton: He's blocking our escape!\n\nRatonhnhak\xe9:ton: There has to be a way around!\n\nRatonhnhak\xe9:ton: Perhaps if we avoid him, we can escape!\n\nRatonhnhak\xe9:ton: No!\n\nRatonhnhak\xe9:ton: Wait!\n\nRatonhnhak\xe9:ton: (sighing) They are everywhere!\n\nRatonhnhak\xe9:ton: I don't know if we can get out of here.\n\nRatonhnhak\xe9:ton: (startled) There are more of them!\n\nRatonhnhak\xe9:ton: (sighing) I do not think I can defeat them alone.\n\nRatonhnhak\xe9:ton: You have the smell of the forest on you.\n\nRatonhnhak\xe9:ton: You must lead the others to us!\n\nRatonhnhak\xe9:ton: Find the warriors and bring them to us!\n\nRatonhnhak\xe9:ton: I will do everything in my power to keep them distracted.\n\nRatonhnhak\xe9:ton: You know the way.\n\nRatonhnhak\xe9:ton: Good dog!\n\nRatonhnhak\xe9:ton: (yelling) Come on, we're waiting!\n\nRatonhnhak\xe9:ton: Where are the warriors?\n\nRatonhnhak\xe9:ton: (growling) What is that sound?\n\nRatonhnhak\xe9:ton: It is coming from above!\n\nRatonhnhak\xe9:ton: Is this the help you've brought?\n\nRatonhnhak\xe9:ton: (growling) No, it cannot be!\n\nRatonhnhak\xe9:ton: Good dog!\n\nRatonhnhak\xe9:ton: (yelling) That way!\n\nRatonhnhak\xe9:ton: I think the warriors have arrived!\n\nRatonhnhak\xe9:ton: (yelling) We need your help!\n\nRatonhnhak\xe9:ton: Come on!\n\nRatonhnhak\xe9:ton: No, I said that way!\n\nRatonhnhak\xe9:ton: (yelling) Where are you going?\n\nRatonhnhak\xe9:ton: Come back!\n\nRatonhnhak\xe9:ton: There is no need to be so rude!\n\nRatonhnhak\xe9:ton: Who are you?\n\nRatonhnhak\xe9:ton: (startled) A bear?\n\nRatonhnhak\xe9:ton: I had a wolf for a companion.\n\nRatonhnhak\xe9:ton: You can see him outside.\n\nRatonhnhak\xe9:ton: (surprised) Another dog?\n\nRatonhnhak\xe9:ton: That one is not as friendly as yours.\n\nRatonhnhak\xe9:ton: What are you doing here?\n\nRatonhnhak\xe9:ton: How can you be here?\n\nRatonhnhak\xe9:ton: They are ready to attack, you must distract them!\n\nRatonhnhak\xe9:ton: Good dog!\n\nRatonhnhak\xe9:ton: He can help me, I just need to get him outside!\n\nRatonhnhak\xe9:ton: I cannot leave without the other!\n\nRatonhnhak\xe9:ton: Do not be a fool!\n\nRatonhnhak\xe9:ton: He's too heavy!\n\nRatonhnhak\xe9:ton: You have to help me.\n\nRatonhnhak\xe9:ton: (yelling) Leave him and go!\n\nRatonhnhak\xe9:ton: It is too late!\n\nRatonhnhak\xe9:ton: We are doomed!\n\nRatonhnhak\xe9:ton: They're moving too fast!\n\nRatonhnhak\xe9:ton: How can you be so calm?\n\nRatonhnhak\xe9:ton: They will kill us!]" time="0.692"><properties><property name="score" value="0.0025065885000000003" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I remember the first time I saw Dazed and Confused. I didn't know what to expect, but it blew me away. As I was preparing to sit down with Richard Linklater to discuss his new film, I had that same feeling. How do you get an audience to empathize with characters they would normally write off as deplorable, if not outright despicable? We talked about this and more, along with the film's complex themes, which Linklater and his actors spent years developing. This interview has been edited and condensed.\n\nHugh: So what I'm really curious about, it's a little bit about tone. The last scene is going to be one of the most talked about, but there are lots of moments in the film where I don't think it's going to be easy to laugh. We're going to laugh, but it's going to be a complicated laugh. I want to know how you feel about that scene, and the importance of it being there, and what else is going to be the most talked about scene for people?\n\nRichard: You know what, I don't have a clue. I had a couple of moments. You know, I don't think it's anything like the rape scene. You know, that was one that everybody seemed to feel like the first time they saw it, at least in the audience screenings, there was a palpable kind of, "Oh my god." But the bowling alley thing, we went through a couple of different iterations of it, and I thought the kids were just going to keep on throwing stuff at him, and he'd get up and leave, but no, that was the one that made people in the audience just go, "I can't." I mean, I remember, I just think of, I have to confess that I haven't seen the movie in a while, but I remember some of the testing, because the movie tested a lot. And they always give you these cards, like "what scene did you love, what scene did you hate," or whatever, and I was shocked by some of the things that people found totally inconsequential. You know, the whole detention room scene was almost universally praised. They loved that, they thought that was great, and the end of it, not so much.\n\nHugh: Yeah. The thing that's different about this film, obviously, is it's not only looking at people and their humanness. It's also looking at their flaws. I mean, you could write these guys off as total scumbags, but it's also very clear that they're young, and they're just trying to find their way. And that's what makes this so powerful.\n\nRichard: That was very intentional, and the fact that I had kids in the film, that was a choice that I made very consciously, because I wanted to get the perspective of the younger people who are looking at the world for the first time. And, you know, they don't have the same values that we do. They're different, and they don't realize it, but they are. They haven't been tested yet. And they're also kind of looking at, you know, maybe the judgmental generation that they have to become. So it was very conscious.\n\nHugh: So you're interested in their stories. What about the parents? I mean, you're going to be a parent soon, how has that changed the way you look at this film and the stories?\n\nRichard: I think it's made me even more interested in getting the stories right of the younger people, and being as honest as I can with them. I mean, I've thought about, I want to do a prequel, you know, like set in the '70s. I've thought about doing one that goes into the '90s, and then just getting closer and closer and closer to what it's like today, but really starting in the '70s and the '80s.\n\nHugh: It's a very complicated thing, and I know you've talked about this a lot, I mean, this idea of nostalgia. But I feel like there's a particular version of nostalgia that goes with this film. You know, you look at the sort of deep Americana in the film. I mean, how do you feel about that?\n\nRichard: Well, I guess I don't really know what you mean by that.\n\nHugh: It's this kind of very rich Americana that really looks at what life was like before people moved to the suburbs.\n\nRichard: Well, that was intentional, that was sort of the style of the film, but there were a lot of choices in the film, you know, that were very deliberate, and one was to make it as realistic as possible. You know, there was no comedy, there was no satire. I mean, it was really the intention, and one of the ideas that we were talking about was, how can you really make people identify with these people, if they're like, I mean, just people would say, "Oh, they're just total scumbags," and that's not the intention. You know, it's like, how can you make people feel like this is a reality, and it's not a joke? And I guess that was one of the choices, you know, like that was just something that was a choice that we were very intentional about.\n\nHugh: What about you? How much do you want this film to be like the experience you remember, and how much do you want to add your own personal story into it?\n\nRichard: You know, I guess, I can remember the moment, it's hard to put into words, but it was, it was a really, it was a weird thing, I was in high school, and we were supposed to be staying at this place, and I was going to walk there. And I was, it was very late, it was like, after 10:00 at night, and I started walking, and I started walking, and I started walking, and I started walking, and I was like, you know, what the hell, you know? And I started walking, and I started walking, and I ended up in my bed, but I just had this sense of loneliness and alienation that I can't describe, but it was a very, it's kind of hard to put into words.\n\nHugh: Yeah.\n\nRichard: So I think that's one of the things that was in the film, that's in all my films, but I think that was something that maybe people don't talk about. But it's, you know, the great teenage angst, that's like a rite of passage, you know, and I guess that was one of the ideas. I think that's what you mean by kind of a different nostalgia.\n\nHugh: Yeah, but I also wonder if it's almost more... It's like an explanation of the parents, of why they are who they are. You know, because I feel like, I mean, you're an independent filmmaker. You're not making a studio movie, but a lot of these people are making that decision because it's a career, but it's also that they're really starting to question their parents.\n\nRichard: That's a good point. Yeah, I mean, I guess that's probably true. But I'm not sure that the same characters would make the same choices. You know, it's a little bit different.\n\nHugh: That's true.\n\nRichard: So I mean, I guess there's probably a different way of looking at it, but I'm not sure.\n\nHugh: Yeah.\n\nRichard: But that's probably true.\n\nHugh: One of the other things that I think is so powerful about the movie, is you can't really tell that they're all the same age.\n\nRichard: Right.\n\nHugh: You know, I think a lot of the time, especially in independent movies, you really can't, especially with characters who are supposed to be that age. But you really do a great job of putting that in there.\n\nRichard: You know, that was a real choice. The only choice that we did was when the girls are taking their bikini tops off, we did make them a little bit older than the guys, because the guys, they were mostly 18, and the girls, you know, they were 21, and they wanted to look that way, you know.\n\nHugh: Yeah.\n\nRichard: I didn't want to deal with, you know, the issue of kids playing these kinds of roles, you know.\n\nHugh: Yeah.\n\nRichard: So, you know, that was one of the choices that we made, but other than that, you know, that was a choice that we made.\n\nHugh: You know, I can't help but think of the movies that inspired this. You know, I'm wondering if there are any that you feel like really influenced you, or you thought about as you were working on this.\n\nRichard: There were lots of movies, but I can't think of any specifically. But, you know, it was really one of the, like I said, it was really one of the influences was, you know, when I was a kid, and I watched all those movies, and I thought, "Wow, I want to make movies that have this feel." And that's what I wanted to do, and when I say, "this feel," I mean like, you know, I guess it's sort of the feel of early '70s films, but the cool thing about those films, they have their own feel, you know. I mean, they were different, and I]" time="0.706"><properties><property name="score" value="0.0014272276666666666" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Dead Space is a popular sci-fi horror game franchise from Visceral Games and Electronic Arts. In addition to two sequels and several handheld spin-offs, the series also has an animated movie called Dead Space: Aftermath which was released in 2011. The movie is set between the events of Dead Space and Dead Space 2.\n\nThis week, we're looking at the movie's trailer and comparing it to its source material. I've played through the game and watched the movie and will be judging the trailer based on what was included in the movie. I'll only be judging the first 30 seconds of the trailer to get an idea of what to expect from the whole movie.\n\nThe trailer starts with a shot of the U.S.G Ishimura, the ship from Dead Space. In the game, the ship is overrun by the necromorphs and infested with scary creatures. The Ishimura's distress beacon is flashing, indicating it's under attack. However, the ship looks too clean to be infested. It's not enough to see the ship itself, you would have to see the dead bodies and monsters crawling around to get the idea.\n\nNext, we see a number of humans fleeing from something off-screen. In the game, they would be running from the necromorphs that have overrun the Ishimura. Unfortunately, they're all human beings in a space suit. You'd have to be pretty stupid to mistake that for the necromorphs. Plus, there's no one attacking the humans. In the game, there would be an endless amount of monsters chasing after the players. There wouldn't be a calm look to everything.\n\nThe next shot shows an exterior shot of the Ishimura while the camera rotates around it. Again, it's too clean to be infested.\n\nNext, we see a shot of some characters, all looking shocked. Again, there's no reason for this if it's not an infestation. It's a bit like seeing a normal-looking family in a horror movie. No one is scared. In fact, there's no real reason for them to be on the Ishimura, which is supposed to be an extremely dangerous place.\n\nThe next shot shows the captain of the Ishimura, Gibb, running up a long ramp. In the game, the Ishimura is more like a battle station than a ship, so the captain would be in the control room. We then see someone telling Gibb to "get everyone out of here." This person has to be an important character from the game or a secondary character. But I'm guessing the person is Gibb's secretary. Again, there's no one yelling or crying. In fact, it seems like the only reason for them to be running around is because it's time to leave.\n\nThe last shot shows the Ishimura firing on something. It looks like they're firing at something, but it's a small target in the distance. The characters aren't running around like it's an emergency. It doesn't look like they're fighting a desperate battle. In fact, the trailer is too clean. All of the shots look like they were taken in a clean studio, not the remains of a space station.]" time="0.304"><properties><property name="score" value="0.08201605" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[It is possible that you may not want your users to have the ability to make certain changes to the data that is being tracked. For example, you may want to track a list of servers, but you don't want your users to be able to add servers, remove servers, or make any other changes to the server list.\n\nThe answer to this problem is to use triggers. You can create triggers that run when a particular type of change is made to the data, and it is possible to make these triggers prevent the data from being changed.\n\nTo create a trigger, you can use the command-line function sqlt. For example, you could write a trigger that prevents a user from removing a particular field from the database.\n\nHere is an example of how you might create a trigger that prevents a user from removing the server_name field from the list of servers:\n\n[mars@luna src]$ sql --user=alena --password=huh --default-access=READ --tables=ListOfServers,ListOfIPAddresses --echo CREATE TABLE ListOfServers(name TEXT); CREATE TABLE ListOfIPAddresses(ip_address TEXT); CREATE TRIGGER server_name_deletion_not_allowed ON ListOfServers FOR DELETE AS BEGIN RAISE INFO 'You may not delete the field server_name'; END; SELECT * FROM ListOfServers; name ---------- nameserver1 nameserver2 name ---------- nameserver1 name ---------- nameserver2\n\nThe SQL statement you would use to drop the trigger would look like this:\n\n[mars@luna src]$ sql --user=alena --password=huh --default-access=READ --tables=ListOfServers,ListOfIPAddresses --echo DROP TRIGGER server_name_deletion_not_allowed ON ListOfServers; DROP TRIGGER server_name_deletion_not_allowed ON ListOfServers;\n\nNotice that we used the same SQL statement to create and drop the trigger. This is a powerful feature of SQL, which allows you to control exactly when a particular change will occur.\n\nFor example, if you want to remove the server_name field from the database, but you want to retain the data that has already been entered, you could write the trigger as follows:\n\nCREATE TRIGGER server_name_deletion_not_allowed ON ListOfServers FOR DELETE AS BEGIN RAISE INFO 'You may not delete the field server_name'; IF (@old.server_name <> @new.server_name) BEGIN INSERT INTO ListOfIPAddresses VALUES (@old.server_name, NULL); UPDATE ListOfServers SET server_name = NULL WHERE server_name = @old.server_name; END; END;\n\nYou would then delete the field, as follows:\n\n[mars@luna src]$ sql --user=alena --password=huh --default-access=READ --tables=ListOfServers,ListOfIPAddresses --echo DELETE server_name FROM ListOfServers; DELETE server_name FROM ListOfServers;\n\nThis example uses the triggers to prevent data from being deleted, but you can use triggers to make other changes as well. You can use the following table to help you determine which commands should be used to insert and delete information:\n\nSQL Command Insert Insert into table Insert into table columns Update Update table Update table columns Delete Delete table Delete table columns]" time="0.310"><properties><property name="score" value="0.02195413" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Perfect! Thank you very much for thess beautiful items!! fast and great quality Top seller, nice one, very fast delivery only took 2 days too come from Germany too the UK, The record was in mint condition!,,,, I Would Recommend Highly quick delivery, record in perfect condition - couldn't be better. thank you very good. Thanks.Great deal. Thanks a lot ! All good, recommended seller !!! Great item, great seller! Superb all round. Professional packing, conservative grading, fast. Thoroughly recommended! Great. thanks! top Very fast shipment, highly recommended, AAAAA+++++++++++++++ top seller, thanks alles super!!! immer wieder gern!!! Perfect !!! very fast Shipping !! Friendly Contact !! A+++++++++ , Perfekt !! Super schneller Versand !! Freundlicher Kontakt !!! 1++++++++++ perfect! Excellent service, very professional. Very fast, good quality top Thanks! Thank you for your quick resoponse!! Quick delivery.No problems.beste Ware=bestenDank No problems! Perfect - thank you so much! Great service. Thank you. Very nice. Thank you! Brilliant seller, arrived very fast for an international delivery and the condition was perfect. I highly recommend this seller and would happily purchase from them again. Vielen Dank! Great seller. Items as described. Deal with confidence. A+ Alles bestens! Gerne wieder! Great service Thank you arrived Mon 23/3/2015 great record, fast shipping, thanks! excellent record, quick shipment, recommended seller! Absolutely perfect in every way: Mint (M) Excellent! Thanks a lot! Good international seller. Great packaging! THANKS!! Very Good, thanks!!!! perfect thanks Awesome disc!!! Perfect transaction!!! PERFECT!!! record arrived teh other day, much better condition as stated, TOP!!! Perfect!!! Thank You!!! Everything perfect! Thank you Awesome!! Great packaging. Very happy!! Thank you for your quick resoponse!!]" time="0.329"><properties><property name="score" value="0.162392" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.162392 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.162392
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Gonzalo \u2018ZeRo\u2019 Barrios, the best Super Smash Bros. for Wii U player in the world, had been competing in Apex for years, and for the most part his reputation remained untarnished by upsets. But this year, things were different. In Apex 2017, he was defeated for the first time since 2015, eliminated in pools by a man that he once conquered: Samuel \u2018Dabuz\u2019 Buzby.\n\nThe question on the minds of many Smash fans was: Why did Dabuz defeat ZeRo, the player who has never been beaten in this game in tournament?\n\nWell, according to Dabuz himself, it was a relatively simple answer.\n\n\u201cI can speak for myself, but one thing that I have definitely noticed is I\u2019ve been playing with a controller for longer,\u201d Dabuz said. \u201cI was playing a lot with the Gamecube controller in 2012 and 2013, and he was mainly playing with the Wii U controller. That\u2019s a big thing, and I think that in general I know how to read his tendencies a little bit better.\u201d\n\nThe controller is a big factor because of the way that Smash for Wii U is played. Because the game was released on the Wii U, it is not played with a controller that has buttons like the PS4 controller, but rather a gamepad with a touchscreen.\n\nZeRo plays with a Gamecube controller with his right hand on the directional pad, and his left hand on the A and B buttons. Because of this, he has to learn the way he plays on that controller and how to switch to it from a standard Wii U gamepad. Dabuz, on the other hand, is more used to the standard controller, which requires more precision and speed to accomplish the same things.\n\nDabuz and ZeRo also play in different regions, which are played on different stages. For example, Dabuz plays on the East Coast, which has the Dream Land stage. This stage is the most neutral stage, and a player who has grown up on that stage would have an edge on a player who was more familiar with the other stages in the game.\n\nZeRo, on the other hand, plays on the West Coast, where the counterpick stages are often Dream Land 64 and Smashville. These stages can change the way a player plays, especially the super defensive style that ZeRo often employs.\n\nThere are also a few other things that can throw a player off their game, including the noises of the crowd and the pressure of being at the top. In a tournament where every person is trying to eliminate you, it can cause even the best to have a momentary lapse in focus and lose a match they should have won.\n\nThese are all things that have affected ZeRo, but they are things that he can get past. Because he is the best, the biggest target and a huge crowd favorite, it is unlikely that the crowd will stop cheering for him any time soon. And when he has a momentary lapse in focus, his playstyle is based around having more than one good option, and his tech skill is such that he can often do something even when he isn\u2019t at his best.\n\nZeRo will be at CEO next week, and this is his chance to reclaim his title as best in the world.\n\nCover photo by Robert Paul via Twitter]" time="0.269"><properties><property name="score" value="0.012546507" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01254651 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01254651
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[by Vincent\n\nOnePlus has officially released the Open Beta version of Android 9.0 Pie for the OnePlus 6. OnePlus, being the company they are, have managed to get the Android 9.0 Pie out to their devices at a very fast pace and they are the only company, at the time of writing, who have managed to do so on a flagship device. The Open Beta 3 update is based on Android 9.0 Pie and will get your OnePlus 6 up to date with the rest of the Android devices. OnePlus have also released their Beta application for Android, the app is currently available for Android devices and will help users test out the new Beta updates before they are released.\n\nThis update brings a number of new features to the OnePlus 6, some of which include the new gestures, including a navigation bar gesture, swiping gestures and double-tapping the display. You can now double-tap to wake your device or tap the power button to go to the lock screen. Also in the Open Beta 3 is a new feature known as Gaming Mode 3.0. The new gaming mode has been redesigned and users will be able to choose which apps they want to use the mode with, so for example, if you do not play any games, you can still use the mode with other apps.\n\nOther new features in the Android 9.0 Pie update include adaptive brightness, adaptive battery and Adaptive Brightness in which the brightness will automatically adjust based on the environment. There is also a new design and layout for the entire Android 9.0 Pie update. Some of the features also include the Smart Display feature which is only found on Android Pie devices. The Smart Display feature includes the redesigned Do Not Disturb, new time-to-leave feature, new quick settings and new power management settings.\n\nNow onto the update, the update is currently available to download via the Open Beta website, for more information on how to install the Open Beta updates, check out this guide. Once the update is downloaded, you can follow our guide to install the update via the recovery. The full changelog for the update can be seen below:\n\nSystem Updated system to Android 9.0 Pie\n\nBrand new UI for Android Pie\n\nNew navigation gestures (Available for devices with pop-up camera, Full Screen display)\n\nUpdated Android security patch to 2018.12 General New features for setting app background and text colors\n\nOptimization for Do Not Disturb\n\nOptimization for haptic feedback\n\nOptimization for Volume panel\n\nOptimization for accidental touch\n\nNow able to switch to last app via 3 dots button in the navbar Phone New UI for speed dial and call history screen\n\nWhite UI for dial pad\n\nTransfer support for dual front camera\n\nOptimization for receiver\u2019s screen\n\nNew quick settings design (text color and background color of each tile can be adjusted)\n\nNew features for notification dots (Notification dots are enabled by default. Tap and hold a notification to turn it off)\n\nOnePlus Community app icon is changed Navigation Updated UI for home screen\n\nUpdated Android security patch to 2018.12 Gaming Mode 3.0 Added new feature to adjust display temperature\n\nAdded frame rate benchmark for better game experience. The benchmark runs after exiting a game.\n\nAdded battery level option for battery saver\n\nNew design for power saving mode\n\nOnePlus Launcher Updated icon for Launcher app\n\nUpdated Android security patch to 2018.12\n\nThere are some known issues in the update which OnePlus have said they are working on fixing. The following issues will be fixed in the next update:\n\nCertain third party apps may fail to connect to the internet\n\nWhen using Bluetooth audio devices, the audio may occasionally cut out after a few minutes\n\nAlert slider settings may disappear after the device reboots\n\nAs you can see, OnePlus are still very busy fixing up the Android 9.0 Pie update for the OnePlus 6. You can also follow the Open Beta program, which allows you to see when a new update is available to download and helps you to try out beta updates before they are released.]" time="0.311"><properties><property name="score" value="0.0012066026" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0012066 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0012066
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[[In many cases, this book is available for "slightly used" prices at Amazon and the rest of the internet. I also offer this advice: if you find yourself using this book often, buy the paperback, not the hardback.]\n\n\n\nFor a one volume handbook of natural remedies and herbal medicine, I think this book offers quite a bit. The different herbal sections are separated out by area of the body with the body part followed by the particular ailment, i.e., heart disease is followed by the subhead heart disease and some of the suggestions are alfalfa, astragalus, and hawthorne. It also gives you the Latin name of the herb (or tree, or flower, etc) which is followed by a very detailed description of how the particular herb can be used in a variety of ways. You can also find the name in parentheses to the right. In this way, you can find an herb quickly in this volume that you may have heard of, but don't know exactly what it is used for or how to use it.\n\n\n\nI feel like the author offers some very useful information here, but unfortunately the descriptions are so brief that they can be confusing. It's hard to glean all of the information in the little boxes. I've come to rely on it as a resource when I don't have anything else to go on, but I also realize that it is a one-volume reference book and cannot be expected to cover everything. I like to have other books around for that purpose. This book does give a good foundation in herbal medicine, but I don't like using it as a primary resource in itself.]" time="0.345"><properties><property name="score" value="0.007116528" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[L\u2019Aquedotto\n\nL\u2019Aquedotto del vescovo Sisto di Heidenheim\n\nIl primo lavoro che merita di essere considerato \xe8 l\u2019Aquedotto di Heidenheim. Anche se in questo caso l\u2019opera non \xe8 frutto di uno sforzo volontario e non aveva lo scopo di fornire acqua, ma ha come scopo principale la delimitazione del terreno (leggi il resto della notizia).\n\nL\u2019Aquedotto del vescovo Sisto di Heidenheim (XI secolo) \xe8 una delle pi\xf9 importanti e affascinanti opere dell\u2019architettura dell\u2019epoca carolingia.\n\nLa costruzione dell\u2019Aquedotto del vescovo Sisto di Heidenheim, cio\xe8 l\u2019opera a cui si \xe8 qui riferito, avvenne durante il dominio dei vescovi e di cui il famoso Sisto di Heidenheim fu vescovo. Egli viene da una nobile famiglia e si laurea in teologia presso l\u2019universit\xe0 di Parigi, dove acquisisce una grande dottrina.\n\nIn seguito egli torna alla sua citt\xe0 natale per occuparsi dei suoi affari, ma anche per prendersi cura dei suoi parrocchiani. Viene chiamato a prendere le redini del suo vescovado, allorch\xe9 il precedente vescovo, eletto da Carlo Magno, viene accusato di simonia.\n\nIl vescovo Sisto diviene il successore del suo predecessore dopo esser stato eletto nel 1074. Sotto la sua guida il vescovado cresce e prospera notevolmente.\n\nLa dimostrazione pi\xf9 evidente di questo successo \xe8 la costruzione dell\u2019Aquedotto del vescovo Sisto di Heidenheim, la cui costruzione ha inizio nel 1079, quando Sisto \xe8 vescovo, e termina nel 1092, quando cessa le sue funzioni come vescovo.\n\nAncora oggi si pu\xf2 ammirare questo famoso edificio lungo la strada che va da Heidenheim a N\xf6rdlingen. La sua lunghezza \xe8 di una trentina di chilometri, e il suo diametro di cinque metri.\n\nGli spunti di tale opera li ebbe il vescovo Sisto da tre guerre che furono combattute durante i suoi anni di vescovado, e che hanno luogo, la prima, nell\u2019anno 1077 contro i Tedeschi, la seconda, contro i Bavari nel 1085, e la terza, ancora contro i Bavari, ma questa volta per la conquista della citt\xe0 di Bisanz nel 1092.\n\nIn conseguenza di questi attacchi, il vescovo Sisto fu costretto a rispettare un\u2019astuta tattica militare e ad impiegarla nel campo della politica. Egli fu sempre sul chi vive per quanto riguarda la difesa dei confini del suo territorio.\n\nPer ottenere questo scopo, egli, appoggiato dal vescovo di Bamberga, costru\xec il pi\xf9 grande Aquedotto del suo tempo.\n\nSotto la guida del suo vescovo, il vescovo di Heidenheim, il vescovo di Bamberga ed il vescovo di W\xfcrzburg, si \xe8 provveduto ad avanzare verso i confini nordoccidentali, e i confini dei territori confinanti al nord e ad ovest.\n\nI lavori furono attuati nel campo militare, cos\xec come pure nell\u2019ambito delle arti e delle scienze, perch\xe9 il vescovo Sisto cre\xf2 nel 1078 un\u2019Accademia, a Heidenheim, in cui si studiavano le matematiche e l\u2019astronomia.\n\nIl vescovo Sisto riusc\xec cos\xec a mettere fine alla sua missione e a trasformare Heidenheim in un centro per la conservazione della cultura.\n\nLa costruzione dell\u2019Aquedotto del vescovo Sisto, avvenne attraverso un processo molto interessante. Anche se il vescovo Sisto non costru\xec l\u2019Aquedotto, ma invece lo compr\xf2 e lo espropri\xf2, egli, comunque, ne diresse la costruzione e con questo oper\xec una grande opera.\n\nI lavori dell\u2019Aquedotto del vescovo Sisto avvennero in due diverse fasi. La prima delle quali si ebbe tra l\u2019anno 1079 e l\u2019anno 1084, la seconda, tra l\u2019anno 1085 e il 1092.\n\nI primi lavori iniziarono quando Sisto compr\xf2 e prese in esproprio una quantit\xe0 considerevole di terreno, tra il suo vescovado, e il territorio che allora apparteneva a W\xfcrzburg. In conseguenza di questo acquisto, l\u2019Aquedotto pass\xf2 inoltre da W\xfcrzburg a Heidenheim.\n\nLe trattative che precedettero l\u2019acquisto dell\u2019Aquedotto non furono particolarmente facili, e Sisto si trov\xf2 nelle condizioni di dover impegnare molto denaro e cercare di ottenere il necessario appoggio anche nel campo militare.\n\nSisto, comunque, ebbe la capacit\xe0 di perseguire il suo scopo, e di ottenere il suo Aquedotto, pur non potendo completare l\u2019intero progetto, di cui egli, tuttavia, lavor\xf2 ad un livello rilevante.\n\nL\u2019Aquedotto di Heidenheim \xe8 un monumento per la cultura, e una vera e propria meraviglia, cos\xec come lo fu, quindi, per il suo tempo. Oggi l\u2019Aquedotto \xe8 ancora l\u2019opera principale di un moderno vescovo, che di continuo, invece, esalta la sua coscienza della cultura di tale Aquedotto.]" time="0.356"><properties><property name="score" value="0.012459725" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Chrysanthemum is a non-flowering perennial plant belonging to the Asteraceae family. The asteraceae family is composed of around 24,000 species. The genus Chrysanthemum is a composite group and consists of approximately 200 species. In Hindi, the plant is known as Karanji, Kuntimuk, Kwatamal. It is a good source of vitamin C and is used as a food and a medicinal plant. The leaves are considered to be of some value as a pot-herb. The entire plant is highly toxic. This plant is often confused with one belonging to the Rosaceae family, known as Golden Shower (Cassia fistula).\n\nChrysanthemum is widely used in Ayurveda, Siddha, Unani, Homoeopathy and allopathy. The plant is used as an appetizer, digestive, vermifuge, for treating jaundice, anthelmintic, skin infections, piles, and disorders of uterus and vagina. The plant is reported to have antiviral activity.\n\nThe extract of Chrysanthemum spp. is used in form of drops, ointments, nasal sprays, aerosols, gargles, and nasal drops in Western medicine. It is a non-opiate analgesic. It is an antipyretic, vasodilator, hypotensive, and anti-inflammatory agent. It is used for treating dental infections, painful cold sores, and sinusitis.\n\nIt is a powerful disinfectant used in hospitals and clinics as a wound antiseptic. It is an effective treatment for infections of the skin, boils, and other skin lesions. The preparation is a thick solution of manganese salts in a 2% solution of hydrogen peroxide and contains 4% to 10% of this chemical, which acts as an antiseptic. It is also used to treat malaria.\n\nChrysanthemum oil is considered as a good antimicrobial agent. It is used in the form of inhalation for the treatment of sinusitis. It is effective against fungi, yeast, bacteria, and viruses. This oil is also used as an antiviral agent for flu, chickenpox, herpes, and herpes zoster.\n\nThe extract is used in the treatment of infectious diarrhoea, hepatitis, and amoebic dysentery. It is also used to reduce irritation and promote healing of the urethra. The extract is used in the treatment of oral thrush and vaginal candidiasis.\n\nThe plant is used for treating leucorrhoea and vaginitis in traditional medicine. It is used for treating burning and pain in the urethra. The plant is used as an antiseptic for the treatment of mouth sores. It is used for treating boils, blisters, insect bites, burns, and wounds. It is also used for treating skin conditions like eczema, ringworm, and hives.\n\nSome of the names that this plant is known by include Chrysanthemum morifolium, Cassia fistula, Chrysanthemum indicum, Chrysanthemum chamissonis, Homonoia chrysanthemi, and Xiong-hua.\n\nChrysanthemum is considered to be of great value for medicinal purposes. The plant is not only used as an appetizer and digestive, but also for treating the disorders of uterus and vagina. The herb is considered as a good antiseptic and as a healing agent. It is useful for healing wounds, ringworm, and jaundice. It is also considered to be good for treating tuberculosis and reducing phlegm.]" time="0.306"><properties><property name="score" value="0.013588636" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A Jersey City firefighter, one of the department\u2019s most seasoned, has been stripped of his rank and placed on administrative leave as a result of alleged sexual harassment and stalking.\n\nThe city took the action against James Fitzpatrick, a 13-year veteran, last month, according to police and fire officials.\n\nFitzpatrick, who has worked at Engine 6, told The Jersey Journal he is appealing his demotion and administrative leave and does not admit to the accusations.\n\n\u201cThey\u2019re saying this is harassment and stalking, but I don\u2019t know what else to do,\u201d he said. \u201cI just want to talk to her.\u201d\n\nCity spokeswoman Jennifer Morrill said Jersey City law prohibits her from discussing the matter because it is a personnel issue.\n\nThe Journal reported in October that city police had been investigating Fitzpatrick on a complaint that he sent hundreds of harassing and harassing and stalking text messages to a firefighter who works at a different firehouse.\n\nCity officials said at the time that they knew of at least 200 messages. The city launched an investigation and suspended Fitzpatrick with pay in November, and he was demoted on Jan. 8.\n\nThe suspended firefighter and police said they were not aware of any criminal charges against Fitzpatrick.\n\n\u201cWe are investigating it and reviewing it internally,\u201d Morrill said last month. \u201cThere is no further information at this time.\u201d\n\nFitzpatrick, a Marine Corps veteran who has been with the Jersey City Fire Department for 13 years, said he is appealing his demotion and administrative leave.\n\nHe said he received a letter from the city in December saying his leave was the result of a \u201cpersonnel matter,\u201d but he said he has not been able to see the letter\u2019s contents because it is sealed by the city\u2019s law department.\n\n\u201cThey\u2019re saying this is harassment and stalking, but I don\u2019t know what else to do,\u201d he said. \u201cI just want to talk to her.\u201d\n\nFitzpatrick said he met the firefighter while they were both in college, and the two became good friends. Fitzpatrick said he started sending her text messages in September because she had not returned his calls. He said he sent her messages out of concern that she was missing work because she was depressed.\n\nThe messages were more than once a day, he said, and he said he never threatened the woman.\n\nThe woman\u2019s lawyer, Susan Ross, said last month that Fitzpatrick sent \u201cmore than 200 harassing and stalking text messages.\u201d\n\n\u201cThe harassment has included threats to my client's life,\u201d she said.\n\nRoss did not respond to a request for comment this week.\n\nFitzpatrick\u2019s wife, Cheryl Fitzpatrick, said the situation has been difficult for their two young daughters, who know nothing about the accusations.\n\n\u201cMy husband is an outstanding fireman,\u201d she said. \u201cIt has been very difficult on my children.\u201d\n\nTerrence T. McDonald may be reached at tmcdonald@jjournal.com. Follow him on Twitter @terrencemcd. Find The Jersey Journal on Facebook.]" time="0.292"><properties><property name="score" value="0.0019905847" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00199058 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00199058
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Sen. Joe Donnelly Joseph (Joe) Simon DonnellyDems pressure GOP to take legal action supporting pre-existing conditions Senate Dems build huge cash edge in battlegrounds Fed chief lays out risks of trade war MORE (D-Ind.) is touting his support for President Trump Donald John TrumpCorker: US must determine responsibility in Saudi journalist's death Five takeaways from testy Heller-Rosen debate in Nevada Dem senator calls for US action after 'preposterous' Saudi explanation MORE\u2019s first Supreme Court nominee, Judge Neil Gorsuch, to make the case to skeptical progressives in Indiana that he can still win their votes in a tough reelection race.\n\nDonnelly has made his vote for Gorsuch, who was confirmed in April, a central part of his reelection pitch.\n\n\u201cMy decision to support Judge Neil Gorsuch was based on an overwhelming need to fill the Supreme Court vacancy,\u201d Donnelly wrote in an op-ed in The Indy Star this week.\n\nADVERTISEMENT\n\n\u201cI strongly believe Judge Gorsuch is a qualified, mainstream jurist who will base his decisions on his understanding of the law and is well-respected among his peers. Judge Gorsuch\u2019s extensive experience and respect in the legal community is important to the integrity of the Supreme Court,\u201d he added.\n\nDonnelly, who is facing a reelection battle against Republican businessman Mike Braun in November, is trying to win over progressives and not alienate them in a state that went for Trump in 2016.\n\nA poll from last month showed that 49 percent of Hoosiers say that they would prefer to vote for someone other than Donnelly, compared to 42 percent who say they will vote for the incumbent senator.\n\nDonnelly told The Hill last month that he is focusing on making his case to voters and he doesn\u2019t pay attention to polls.\n\nBut while Donnelly touts his vote for Gorsuch, he\u2019s been careful to show he won\u2019t be someone who will blindly vote for the president\u2019s agenda.\n\n\u201cI won\u2019t support a nominee who doesn\u2019t respect the rights of Ho]" time="0.273"><properties><property name="score" value="0.0042468687" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00424687 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00424687
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Highland League Founded: 1975 Country: Scotland Level: 5 Number of teams: 17 most based in: Scotland (4) Region(s): Scotland Sponsor(s): TBD Website: TBD\n\nThe Highland Football League is a senior non-league association football competition in the north of Scotland.\n\nContents show]\n\nPremier League Edit\n\nThe league consists of 17 clubs, playing each other home and away.\n\nSeason Premier Division Relegated from 1. 2016\u201317 (A) (A) Oban Camanachd\n\n(B) Kyles Athletic 2. 2015\u201316 (A) (A) (A) Lochaber\n\n(B) Skye Camanachd 3. 2014\u201315 (A) (A) Lochaber\n\n(B) Kyles Athletic 4. 2013\u201314 (A) (A) Lochaber\n\n(B) Strathspey Camanachd 5. 2012\u201313 (A) (A) (A) Skye Camanachd\n\n(B) Lochaber 6. 2011\u201312 (A) (A) (A) Skye Camanachd\n\n(B) Kyles Athletic 7. 2010\u201311 (A) (A) (A) Lochaber\n\n(B) Kyles Athletic 8. 2009\u201310 (A) (A) (A) Skye Camanachd\n\n(B) Strathspey Camanachd 9. 2008\u201309 (A) (A) (A) Skye Camanachd\n\n(B) Strathspey Camanachd 10. 2007\u201308 (A) (A) (A) Skye Camanachd\n\n(B) Lochaber 11. 2006\u201307 (A) (A) (A) Kyles Athletic\n\n(B) Strathspey Camanachd 12. 2005\u201306 (A) (A) (A) Lochaber\n\n(B) Skye Camanachd 13. 2004\u201305 (A) (A) (A) Skye Camanachd\n\n(B) Kyles Athletic 14. 2003\u201304 (A) (A) (A) Skye Camanachd\n\n(B) Lochaber 15. 2002\u201303 (A) (A) (A) Strathspey Camanachd\n\n(B) Lochaber 16. 2001\u201302 (A) (A) (A) Skye Camanachd\n\n(B) Kyles Athletic 17. 2000\u201301 (A) (A) (A) Lochaber\n\n(B) Kyles Athletic 18. 1999\u201300 (A) (A) (A) Lochaber\n\n(B) Kyles Athletic\n\n1. In the initial year of the league, reserve teams of the Highland Football League clubs were eligible to take part, although the games were not counted as official League matches.\n\n2. Only one team can be promoted to the league, although in the first year only two teams took part, and in the second year four teams took part.\n\n3. Both the first and second placed teams in the reserve league took part.\n\n4. The winners of the league and the runners-up compete in a playoff for the right to play in the Scottish Cup, and if the runners-up win they enter the competition in the first round, the winners in the fourth.\n\nLeague History Edit\n\nLeague History Season Champions Relegated 1. 2008\u201309 Strathspey Camanachd Kyles Athletic 2. 2007\u201308 Lochaber Skye Camanachd 3. 2006\u201307 Lochaber Kyles Athletic 4. 2005\u201306 Skye Camanachd Lochaber 5. 2004\u201305 Lochaber Kyles Athletic 6. 2003\u201304 Skye Camanachd Lochaber 7. 2002\u201303 Strathspey Camanachd Lochaber 8. 2001\u201302 Skye Camanachd Kyles Athletic 9. 2000\u201301 Lochaber Kyles Athletic 10. 1999\u201300 Skye Camanachd Kyles Athletic\n\nTitles by club Edit\n\nAberdour - 1\n\n2000\u201301\n\n\n\nSkye Camanachd - 8\n\n2000\u201301, 2003\u201304, 2005\u201306, 2008\u201309, 2011\u201312, 2013\u201314, 2014\u201315, 2015\u201316, 2017\u201318\n\n\n\nLochaber - 5\n\n1999\u201300, 2003\u201304, 2008\u201309, 2010\u201311, 2011\u201312\n\n\n\nKyles Athletic - 4\n\n1996\u201397, 1997\u201398, 2008\u201309, 2011\u201312\n\n\n\nLochside Rovers - 3\n\n1989\u201390, 1992\u201393, 1998\u201399\n\n\n\nStrathspey Camanachd - 3\n\n1997\u201398, 1998\u201399, 2009\u201310\n\n\n\nBoleskine Rovers - 1\n\n1993\u201394\n\n\n\nInvergordon - 1\n\n1991\u201392\n\n\n\nKinlochshiel - 1\n\n1991\u201392\n\n\n\nFort William - 1\n\n1991\u201392\n\n\n\nArisaig - 1\n\n1990\u201391\n\n\n\nCaberfeidh - 1\n\n1987\u201388\n\n\n\nAberdeen University - 1\n\n1985\u201386\n\n\n\nFormartine United - 1\n\n1982\u201383\n\n\n\nStrathspey Thistle - 1\n\n1979\u201380\n\n\n\nFort William Rovers - 1\n\n1947\u201348\n\n\n\nRoss County - 1\n\n1946\u201347\n\n\n\nFortrose - 1\n\n1945\u201346\n\n\n\nNairn Thistle - 1\n\n1942\u201343\n\n\n\nInverness Thistle - 1\n\n1941\u201342\n\n\n\nStrathspey Thistle - 1\n\n1940\u201341\n\n\n\nFort William Thistle - 1\n\n1939\u201340\n\n\n\nCambridge University - 1\n\n1935\u201336\n\n\n\nDeveronvale - 1\n\n1935\u201336\n\n\n\nCaberfeidh - 1\n\n1934\u201335\n\n\n\nInverness High School FP - 1\n\n1933\u201334\n\n\n\nMurdo Macleod - 1\n\n1933\u201334\n\n\n\nIona - 1\n\n1932\u201333\n\n\n\nFasnakyle - 1\n\n1931\u201332\n\n\n\nCaberfeidh - 1\n\n1930\u201331\n\n\n\nRoyal HSFP - 1\n\n1929\u201330\n\n\n\nRovers - 1\n\n1928\u201329\n\n\n\nAberdour - 1\n\n1927\u201328\n\n\n\nDeveronvale - 1\n\n1926\u201327\n\n\n\nInverness Thistle - 1\n\n1925\u201326\n\n\n\nForres Thistle - 1\n\n1924\u201325\n\n\n\nDeveronvale - 1\n\n1923\u201324\n\n\n\nFortrose - 1\n\n1922\u201323\n\n\n\nInverness Thistle - 1\n\n1921\u201322\n\n\n\nForres Thistle - 1\n\n1918\u201319\n\n\n\nInverness Thistle - 1\n\n1917\u201318\n\n\n\nFortrose - 1\n\n1916\u201317\n\n\n\nInverness Caledonian - 1\n\n1915\u201316\n\n\n\nDeveronvale - 1\n\n1914\u201315\n\n\n\nFortrose - 1\n\n1913\u201314\n\n\n\nDeveronvale - 1\n\n1912\u201313\n\n\n\nRoyal HSFP - 1\n\n1911\u201312\n\n\n\nFortrose - 1\n\n1910\u201311\n\n\n\nInverness Thistle - 1\n\n1909\u201310\n\n\n\nDeveronvale - 1\n\n1908\u201309\n\n\n\nDeveronvale - 1\n\n1907\u201308\n\n\n\nInverness Thistle - 1\n\n1906\u201307\n\n\n\nHighland Regt. - 1\n\n1905\u201306\n\n\n\nRoyal HSFP - 1\n\n1904\u201305\n\n\n\nFortrose - 1\n\n1903\u201304\n\n\n\nHighland Regt. - 1\n\n1902\u201303\n\n\n\nRoyal HSFP - 1\n\n1901\u201302\n\n\n\nDeveronvale - 1\n\n1900\u201301\n\n\n\nDeveronvale - 1\n\n1899\u201300\n\n\n\nHighland Regt. - 1\n\n1898\u201399\n\n\n\nInverness Caledonian - 1\n\n1897\u201398\n\n\n\nDeveronvale - 1\n\n1896\u201397\n\n\n\nDeveronvale - 1\n\n1895\u201396\n\n\n\nFortrose - 1\n\n1894\u201395\n\n\n\nDeveronvale - 1\n\n1893\u201394\n\n\n\nHighland Regt. - 1\n\n1892\u201393\n\n\n\nHighland Regt. - 1\n\n1891\u201392\n\n\n\nFortrose - 1\n\n1890\u201391\n\n\n\nDeveronvale - 1\n\n1889\u201390\n\n\n\nDeveronvale - 1\n\n1888\u201389\n\n\n\nInverness Thistle - 1\n\n1887\u201388\n\n\n\nDeveronvale - 1\n\n1886\u201387\n\n\n\nFortrose - 1\n\n1885\u201386\n\n\n\nFortrose - 1\n\n1884\u201385\n\n\n\n]" time="0.341"><properties><property name="score" value="0.003603079" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A man died Sunday in China\u2019s western Xinjiang region after setting himself on fire outside a police station, a regional government spokesman said.\n\nThe man set himself ablaze after fighting with local police over a traffic fine, Nur Bekri, head of the regional government, told a press conference.\n\nPolice in the northwestern region were carrying out \u201cstability maintenance work\u201d at the time of the incident, he said.\n\n\u201cHe self-immolated after a quarrel over a traffic violation and the police station,\u201d Bekri said, adding that the police handled the case correctly.\n\n\u201cThe government urges people to resolve their disputes through legal means,\u201d he said.\n\nIn recent months, dozens of people have set themselves on fire in Xinjiang to protest what they say are human rights abuses, while scores more have resorted to violence or armed assaults against government officials or police stations.\n\nWhile official figures show that most of those who have set themselves on fire are Uyghur, a Turkic-speaking, largely Muslim ethnic group, a majority of those who carried out attacks were Han Chinese, according to reports.\n\nAn estimated 200 people died as a result of the self-immolations or violence last year.\n\n(AFP)\n\n\u7f51\u53cb\u8bc4\u8bba\uff1a\n\n\u7f51\u6613\u8fbd\u5b81\u7701\u961c\u65b0\u5e02\u624b\u673a\u7f51\u53cb\uff1a\n\nThis is nothing. In the most difficult time of the Cultural Revolution, more than a thousand people self-immolated themselves to death, over five million were violently killed, and an entire country was sacrificed for one man. The self-immolators are committing suicide for what? All of this is being sacrificed for a man.\n\n\u7f51\u6613\u6cb3\u5317\u7701\u5eca\u574a\u5e02\u624b\u673a\u7f51\u53cb\uff1a\n\nSending military troops into Urumqi, letting people starve, shoot, slaughter, etc., the government has long since abandoned any kind of \u201cmaintenance of stability.\u201d But can they face the fact that a few hundred Uyghurs have gone to extremes? This is the embarrassment of the government, a proof that the lives of the Uyghur are worth even less than the government thinks. I\u2019m just hoping that the Uyghur people will gain their own freedom one day.\n\n\u7f51\u6613\u5e7f\u4e1c\u7701\u4f5b\u5c71\u5e02\u624b\u673a\u7f51\u53cb\uff1a\n\nTerrorism and arson.\n\nOnly a thief is afraid of fire.\n\nThe history of the burning of books in the East is the same as that of the burning of witches in the West.\n\nThe responsibility of the Uyghurs is in the hands of the government and the people of China.\n\nIf the people of China can be unified, if the government can be clear, it will not be as it is now, nor will it have the effects of spreading instability throughout the world.\n\n\u7f51\u6613\u7f8e\u56fd\u624b\u673a\u7f51\u53cb\uff1a\n\nThe most important thing in the Uyghurs\u2019 lives is the love for their children and themselves, as the life of one\u2019s family is the foundation of all things. This is how the Uyghurs are, and this is the reason why they fight back, and this is why they do what they do.\n\nFor example, the government forcibly inserts women into the Uyghur\u2019s households and forces them to wear head scarves, it forcibly strips the children from their families and rears them in \u201corphanages,\u201d forcibly rips young girls from their parents\u2019 arms to be sent to Tibet, forcibly controls the number of children Uyghurs are allowed to have, forcibly forces Uyghurs to go to Han villages, forcibly encourages them to go to work in the cities, forcibly puts Han businesses into Uyghur homes, forcibly buys out their livestock and agricultural fields to build industrial parks, forcibly forces Uyghur young people to go to school to study and the rest are to go to do factory work, forcibly builds supermarkets, shops, hotels, etc., which gives them no chance to get employment, forcibly makes it so that Uyghur young people can\u2019t find a spouse to get married and have children, forcibly demolishes their houses and forces them to move to another area, forcibly blocks them from having religious activities, etc., etc., the Uyghurs are continuously being forced to endure.\n\nIf you look at the Uyghur protests from a perspective of someone observing them, you can understand how it all began and why it has continued to this day.\n\nThe government has no choice but to take all this, because the Uyghurs are a minority group with nothing to back them up and their lot is really not the greatest.\n\nOn the other hand, if the government wants to go easy on the Uyghurs, this might also lead to the Uyghurs feeling discontent with the government, so it has to be a careful balancing act.\n\nYou know, because of this constant bickering, the government can no longer help the Uyghurs, because it\u2019s already using all its energy to help the Han, which is what it cares about most.\n\n\u7f51\u6613\u6e56\u5317\u7701\u6b66\u6c49\u5e02\u624b\u673a\u7f51\u53cb\uff1a\n\nIf the man really did self-immolate because of the fines, isn\u2019t that a little too extreme? If he had used this method before, it could be understood. But he\u2019s done this only now, this means that he\u2019s only using this method for his own ends. What does this mean? How can people kill themselves and turn themselves into such an extreme protest against injustice? Who are the ones to blame?\n\n\u7f51\u6613\u5317\u4eac\u5e02\u624b\u673a\u7f51\u53cb\uff1a\n\nI am just trying to understand, he set himself on fire to fight over a traffic violation?\n\n\u7f51\u6613\u7f8e\u56fd\u624b\u673a\u7f51\u53cb\uff1a\n\nWhen the time comes, there will only be Uyghur resistance and nothing else.\n\n\u7f51\u6613\u6e56\u5357\u7701\u624b\u673a\u7f51\u53cb\uff1a\n\nJust look at this, everyone. The Uyghurs have their own methods of protest and methods of expressing their wishes and opinions, which have nothing to do with us.\n\nSo can we stop always picking on them and accusing them of terrorist actions? What they are doing is simply that they are using extreme methods to express their unhappiness and discontent, but I hope that they will consider the extreme actions of their people and act in accordance with the situation in China.\n\nI would like to ask everyone, what do you think?\n\nI believe the true thinking of the masses should be understood.\n\n\u7f51\u6613\u9655\u897f\u7701\u624b\u673a\u7f51\u53cb\uff1a\n\nWhat a shame, they have this kind of personality and they\u2019re so different from us. But since they are living under our government, and their lives are being constantly destroyed, I understand the psychology of people like this.]" time="0.563"><properties><property name="score" value="0.0349434313" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03494343 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03494343
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[We the people of India are collectively called as Hindus.\n\nThe Quran says that we are better than other nations.\n\nIn the Quran it is written as\n\n\u201cThe most honorable of you in the sight of God is the most pious of you.\u201d (49:13)\n\nIt also says that Allah is closer to the believers than their jugular vein. (Quran 50:15)\n\nHindus consider the cow to be sacred. The Quran teaches us that it is not what enters the stomach that is impure but what comes out of the mouth.\n\nIn the Quran it is written as\n\n\u201cGod does not hold you responsible for your unintentional oaths. And He forgives you for any oaths you take to intentionally falsify something. (Quran-66:2)\n\nIt says that we should have absolute faith in God.\n\nIt says that the scholars are our friends and neighbors, that is why they must be obeyed and respected. (Quran- 4:71)\n\nOur God is one.\n\nIt is written in the Quran as\n\n\u201cThose who believe, and those who are Jewish, and the Christians, and the Sabians \u2013 whoever believes in God and the Last Day and does righteous deeds \u2013 will have their reward with their Lord. (Quran 2:62)\n\nIt is also written in the Quran as\n\n\u201cIndeed, the religion in the sight of God is Islam. (Quran 3:19)\n\nA Hindu must strive to become a better person and have patience, and trust in God.\n\nThe QURAN says as\n\n\u201cAnd it is He who sent down to you the Book. In it are verses that are entirely clear, they are the foundation of the Book; and others not entirely clear. As for those in whose hearts there is a deviation (from the truth) they follow that which is not entirely clear thereof, seeking discord and seeking an interpretation (suitable to them). And no one knows its [true] interpretation except God. But those firm in knowledge say, \u201cWe believe in it. All [of it] is from our Lord.\u201d And no one will be reminded except those of understanding. (Quran 3:7)\n\nWe must follow what is in the Quran and what was said by the Prophet (PBUH).\n\nWe can learn from all great men.\n\nIt is written in the Quran as\n\n\u201cTo you we sent the scripture in truth, confirming the scripture that came before it, and guarding it in safety: so judge between them by what God has revealed, and do not follow their low desires [to turn away] from the truth that has come to you. For each of you We have appointed a law and a way. If God had so willed, He would have made you a single community, but [He intended] to test you in what He has given you; so strive as in a race in all virtues. The goal of you all is to God; it is He that will show you the truth of the matters in which you dispute.\u201d (Quran 5:48)\n\nThe Quran says as\n\n\u201cThis day, I have perfected your religion for you, completed My favor upon you, and have chosen for you Islam as your religion.\u201d (Quran 5:3)\n\nHindus must believe in God and His Prophets.\n\nThe Quran says as\n\n\u201cThe similitude of Jesus before God is as that of Adam; He created him from dust, then said to him: \u201cBe\u201d. And he was. The truth is from your Lord, so be not of those who doubt.\u201d (Quran 3:59)\n\nHindus must believe in the Quran and what it says.\n\nThe Quran says as\n\n\u201cAnd We have sent down to you the book explaining all things, a guide, mercy, and glad tidings for those who have submitted.\u201d (Quran 16:89)\n\nThe Quran says as\n\n\u201cIf only they had stood fast by the Law, the Gospel, and all the revelation that was sent to them from their Lord, they would have enjoyed happiness from every side. There is from among them a party on the right course; but many of them follow a course that is evil.\u201d (Quran 5:66)\n\nHindus should follow their great men like Krishna and Mahavir.\n\nThe Quran says as\n\n\u201cHe has ordained for you of religion what He enjoined upon Noah and that which We have revealed to you, [O Muhammad], and what We enjoined upon Abraham and Moses and Jesus \u2013 to establish the religion and not be divided therein. Difficult for those who associate others with God is that to which you invite them. God chooses for Himself whom He wills and guides to Himself whoever turns back [to Him].\u201d (Quran 42:13)\n\nThe Quran says as\n\n\u201cYou [true believers in Islamic Monotheism, and real followers of Prophet Muhammad and his Sunnah (legal ways, etc.)] are the best nation produced [as an example] for mankind. You enjoin what is right and forbid what is wrong and believe in God.\u201d (Quran 3:110)\n\nMuslims are to call people to follow the path of the right.\n\nThe Quran says as\n\n\u201cWe have sent you forth as a witness, as a bringer of good tidings and a warner, as well as to give mercy.\u201d (Quran 34:28)\n\nMuslims must follow the truth.\n\nIt is written in the Quran as\n\n\u201cYou shall be on the right course, as long as you are firm and mindful of God.\u201d (Quran 2:110)\n\nThe Quran says as\n\n\u201cYou [true believers in Islamic Monotheism, and real followers of Prophet Muhammad and his Sunnah (legal ways, etc.)] are the best of peoples ever raised up for mankind; you enjoin what is right and forbid what is wrong and believe in God.\u201d (Quran 3:110)\n\nThe Hindus must follow the truth and must not take the path of falsehood.\n\nThe Quran says as\n\n\u201cYou will certainly be tested in your possessions and in yourselves. And you will certainly hear from those who were given the Scripture before you and from those who associate others with God much abuse. But if you are patient and fear God \u2013 indeed, that is of the matters [worthy] of determination.\u201d (Quran 3:186)\n\nThe Hindu should seek the guidance of God.\n\nThe Quran says as\n\n\u201cIs it not to God that sincere devotion is due? But those who take for protectors other than God (say): \u201cWe only worship them that they may bring us nearer to God.\u201d Truly God will judge between them in that wherein they differ. But God guides not such as are false and ungrateful.\u201d (Quran 16:72)\n\nThe Hindu should follow the teachings of the Quran.\n\nIt is written in the Quran as\n\n\u201cLet there be no compulsion in religion: Truth stands out clear from Error: whoever rejects evil and believes in God hath grasped the most trustworthy hand-hold, that never breaks. And God heareth and knoweth all things.\u201d (Quran 2:256)\n\nHindus should also keep away from alcohol and gambling.\n\nIt is written in the Quran as\n\n\u201cO you who believe! Intoxicants (all kinds of alcoholic drinks), and gambling, and Al-Ansab, and Al-Azlam (arrows for seeking luck or decision) are an abomination of Shaitan\u2019s (Satan) handiwork. So avoid (strictly all) that (abomination) in order that you may be successful.\u201d (Quran 5:90)\n\nHindus must avoid sex outside marriage.\n\nThe Quran says as\n\n\u201cAnd do not go]" time="0.582"><properties><property name="score" value="0.03711195" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03711195 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03711195
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Format: Mass Market Paperback\n\nI am a big fan of Julie Garwood. I have read and enjoyed all of her books. Most of her works have been historical romances. She is the queen of the historical romance. In her "Garwoodesque" style, she takes on a contemporary setting, but her attention to detail and superb research remains. If you've read her works in the past, you will find this new one to be in keeping with her other works.\n\n\n\nThe story takes place in modern day Scotland. Lucinda Ashton's family has had it rough for the past two years. Her father has been suffering from an incurable illness, her mother's nerves are beginning to show, and her twin brothers are both leaving for college and working part time jobs to help with the family expenses. But, it is her brother Duncan who she is most worried about. Duncan has always been her hero. The oldest and most handsome of the Ashton boys, she has watched him for years make the right choices and resist temptation. Lucinda wants to be a lawyer. But her parents are barely able to feed and cloth their five children, so Lucinda has had to abandon her dreams of higher education. Lucinda is determined to help her parents and her siblings. She will sell her beautiful pearl necklace so she can pay for her brothers' educations and alleviate some of her parents' financial burden.\n\n\n\nDuncan is thrilled to be going to university in Edinburgh. He is determined to study hard and make something of himself. When he discovers that his sister has sold her necklace, he is furious. But, Lucinda has already made the deal and there is nothing Duncan can do to stop it. Lucinda is devastated by Duncan's reaction to her choice. She is so hurt by his harshness that she stops speaking to him. Duncan is ashamed of his anger, and he is sorry for the pain he has caused his sister. His mother, a loving and kind woman, tells him to go to Lucinda and make things right.]" time="0.397"><properties><property name="score" value="0.7485483" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[di Mara Polli\n\n\xc8 sceso sottotraccia, il Professore, perch\xe9 ne aveva piene le scatole. E perch\xe9 sostenere che la lezione di merda di quel giorno era solo la punta di un iceberg, un ritaglio di una realt\xe0 molto pi\xf9 vasta. In quel preciso momento, aveva preso coraggio, lo stesso coraggio che aveva avuto vent\u2019anni prima, quando s\u2019era inventato lo sciopero a sorpresa. Al posto del tran tran, era passato agli scioperi. Il primo, nel \u201977, aveva avuto un riscontro difficile: un solo docente aveva appoggiato la sua iniziativa, ma la classe era nel complesso solidale con l\u2019insegnante (sbagliato). Il secondo, invece, aveva attirato l\u2019attenzione delle maestre. Quelle della prima e della seconda. E s\xec che aveva ragione: quello, per esempio, era il momento pi\xf9 duro, non solo per lui, ma anche per tutte le donne: l\u20198 marzo, avevano dovuto copiare i fogli per fare i mazzi di fiori (d\u2019autunno, nel caso dei professori). Copiare i fogli, e lasciare l\u2019edificio in ginocchio, a sguazzare nella scienza delle macchine. Ma il professore non sapeva come fosse l\u20198 marzo per le maestre. La maestra che la giornata l\u2019aveva passata con la matita in bocca, che faceva finta di avere i minatori tra i denti. I minatori di turno. Quelli della prima e della seconda.\n\nLui, il professore, era sempre in bilico, ma in un modo o nell\u2019altro ce l\u2019aveva fatta, e questo gli bastava. Non avrebbe mai detto che tutte le donne svolgono un lavoro, alcune stanno al cesso, altre a cucire, altre stanno in sala operatoria, altre ancora passano a ritirare il pane o a farsi servire a tavola. Di tutte queste attivit\xe0, lui avrebbe fatto a meno. Di tutte, e del lavoro in generale. Ma a volte \xe8 dura essere supereroi. Anche se solo per un giorno.\n\nAnnunci]" time="0.276"><properties><property name="score" value="0.23751588" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The murder of the investigative journalist and two-time Academy Award winning filmmaker who was critical of Russian president Vladimir Putin, points to the fact that there is no independent journalism in Russia, Prof. Mark Galeotti, Senior Researcher at the Institute of International Relations Prague (Czech Republic) and an expert on Russian security services, has told Sputnik.\n\n\xa9 AP Photo / Evgeny Feldman Oligarchs Pushed Away From the Media, Facing Pressure From the Russian Authorities\n\nThe state-run Russian Investigative Committee has opened a criminal investigation into the murder of Boris Nemtsov , a Russian opposition politician, on charges of illegal arms trade.\n\nOn Sunday, February 28, Nemtsov was shot dead while walking across a bridge near the Kremlin in Moscow, on his way home.\n\n\u201cPutin has silenced the few remaining independent newspapers and there is no independent television. If it weren\u2019t for the internet, people would not have any information about what is going on,\u201d Mark Galeotti, Senior Researcher at the Institute of International Relations Prague (Czech Republic) and an expert on Russian security services, told Sputnik.\n\nGaleotti pointed out that as Russia\u2019s opposition leaders are being arrested or killed, the country\u2019s media are totally \u201cunder the control of the Russian authorities.\u201d\n\n\u201cIf you are critical of Putin, you are likely to disappear or be killed. There is no independent journalism,\u201d he stressed.\n\nAt the same time, the academic stressed that \u201cmurder\u201d should not be used in this case, as it is actually \u201ca pre-meditated killing.\u201d\n\n\u201cIt is a message to anybody else who might want to be critical, that there is no point in being outspoken,\u201d Galeotti noted.\n\nSpeaking about the possible motives for Nemtsov\u2019s murder, the academic suggested that there might have been a \u201cspat\u201d between the victim and the Russian authorities over the situation in Ukraine.\n\n\u201cI can imagine that there was some sort of disagreement,\u201d Galeotti said. \u201cNemtsov was an avowed liberal, who was pro-Western. He said that Putin\u2019s policies in Ukraine were wrong.\u201d\n\nThe Russian academic noted that Nemtsov could have been \u201cbrought into the public eye by some of the authorities who are opposed to Putin\u2019s policies.\u201d\n\n\u201cI am not saying that Putin ordered the killing, but if you look at who is opposed to him, there are different people. Nemtsov was a figure of importance in the 1990s and in the early 2000s. So if you are trying to build up a coalition, you would bring Nemtsov back,\u201d Galeotti noted.\n\nThe killing of Boris Nemtsov is \u201chighly significant,\u201d Galeotti said, adding that \u201cnot everybody is killed.\u201d\n\n\u201cThe message is that there is no point in being outspoken. It is an effective silencer of anyone else who might want to be critical of the regime,\u201d the academic concluded.]" time="1.036"><properties><property name="score" value="0.0021931296" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00219313 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00219313
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The legacy of past security problems with GM vehicles has forced GM to recall more than 6 million vehicles over the past decade, according to the National Highway Traffic Safety Administration.\n\nGM made most of the recent recalls, including those for ignition switch and power steering problems.\n\nThe automaker will appear before Congress this week to answer questions about its handling of the ignition switch problem. It faces lawsuits from owners of vehicles that were part of the recall, and also faces a criminal investigation.\n\nRep. Diana DeGette (D-Colo.) released a list of recalls from the NHTSA. DeGette has proposed legislation that would require the NHTSA to assess how automakers handled vehicle defects and how their actions impacted safety.\n\nThe data below is taken directly from the NHTSA. The list does not include recalls from the agency's other administrative offices, including the Offices of Defects Investigation.\n\nAlso, the NHTSA does not keep data for recalls issued in the 1950s.\n\n2013: 2.3 million\n\n2012: 1.3 million\n\n2011: 1.3 million\n\n2010: 1.1 million\n\n2009: 710,000\n\n2008: 780,000\n\n2007: 650,000\n\n2006: 480,000\n\n2005: 360,000\n\n2004: 290,000\n\n2003: 290,000\n\n2002: 270,000\n\n2001: 300,000\n\n2000: 310,000\n\n1999: 260,000\n\n1998: 230,000\n\n1997: 260,000\n\n1996: 250,000\n\n1995: 230,000\n\n1994: 240,000\n\n1993: 200,000\n\n1992: 210,000\n\n1991: 220,000\n\n1990: 190,000\n\n1989: 190,000\n\n1988: 200,000\n\n1987: 180,000\n\n1986: 150,000\n\n1985: 140,000\n\n1984: 160,000\n\n1983: 140,000\n\n1982: 120,000\n\n1981: 100,000\n\n1980: 90,000\n\n1979: 90,000\n\n1978: 80,000\n\n1977: 70,000\n\n1976: 60,000\n\n1975: 60,000\n\n1974: 50,000\n\n1973: 50,000\n\n1972: 40,000\n\n1971: 40,000\n\n1970: 30,000\n\n1969: 20,000\n\n1968: 20,000\n\n1967: 10,000\n\n1966: 0\n\n1965: 0\n\n1964: 0\n\n1963: 0\n\n1962: 0\n\n1961: 0\n\n1960: 0\n\n1959: 0\n\n1958: 0\n\n1957: 0\n\n1956: 0\n\n1955: 0\n\n1954: 0\n\n1953: 0\n\n1952: 0\n\n1951: 0\n\n1950: 0\n\n1949: 0\n\n1948: 0\n\n1947: 0\n\n1946: 0\n\n1945: 0\n\n1944: 0\n\n1943: 0\n\n1942: 0\n\n1941: 0\n\n1940: 0\n\n1939: 0\n\n1938: 0\n\n1937: 0\n\n1936: 0\n\n1935: 0\n\n1934: 0\n\n1933: 0\n\n1932: 0\n\n1931: 0\n\n1930: 0\n\n1929: 0\n\n1928: 0\n\n1927: 0\n\n1926: 0\n\n1925: 0\n\n1924: 0\n\n1923: 0\n\n1922: 0\n\n1921: 0\n\n1920: 0\n\n1919: 0\n\n1918: 0\n\n1917: 0\n\n1916: 0\n\n1915: 0\n\n1914: 0\n\n1913: 0\n\n1912: 0\n\n1911: 0\n\n1910: 0\n\n1909: 0\n\n1908: 0\n\n1907: 0\n\n1906: 0\n\n1905: 0\n\n1904: 0\n\n1903: 0\n\n1902: 0\n\n1901: 0\n\n1900: 0\n\n1899: 0\n\n1898: 0\n\n1897: 0\n\n1896: 0\n\n1895: 0\n\n1894: 0\n\n1893: 0\n\n1892: 0\n\n1891: 0\n\n1890: 0\n\n1889: 0\n\n1888: 0\n\n1887: 0\n\n1886: 0\n\n1885: 0\n\n1884: 0\n\n1883: 0\n\n1882: 0\n\n1881: 0\n\n1880: 0\n\n1879: 0\n\n1878: 0\n\n1877: 0\n\n1876: 0\n\n1875: 0\n\n1874: 0\n\n1873: 0\n\n1872: 0\n\n1871: 0\n\n1870: 0\n\n1869: 0\n\n1868: 0\n\n1867: 0\n\n1866: 0\n\n1865: 0\n\n1864: 0\n\n1863: 0\n\n1862: 0\n\n1861: 0\n\n1860: 0\n\n1859: 0\n\n1858: 0\n\n1857: 0\n\n1856: 0\n\n1855: 0\n\n1854: 0\n\n1853: 0\n\n1852: 0\n\n1851: 0\n\n1850: 0\n\n1849: 0\n\n1848: 0\n\n1847: 0\n\n1846: 0\n\n1845: 0\n\n1844: 0\n\n1843: 0\n\n1842: 0\n\n1841: 0\n\n1840: 0\n\n1839: 0\n\n1838: 0\n\n1837: 0\n\n1836: 0\n\n1835: 0\n\n1834: 0\n\n1833: 0\n\n1832: 0\n\n1831: 0\n\n1830: 0\n\n1829: 0\n\n1828: 0\n\n1827: 0\n\n1826: 0\n\n1825: 0\n\n1824: 0\n\n1823: 0\n\n1822: 0\n\n1821: 0\n\n1820: 0\n\n1819: 0\n\n1818: 0\n\n1817: 0\n\n1816: 0\n\n1815: 0\n\n1814: 0\n\n1813: 0\n\n1812: 0\n\n1811: 0\n\n1810: 0\n\n1809: 0\n\n1808: 0\n\n1807: 0\n\n1806: 0\n\n1805: 0\n\n1804: 0\n\n1803: 0\n\n1802: 0\n\n1801: 0\n\n1800: 0\n\n1799: 0\n\n1798: 0\n\n1797: 0\n\n1796: 0\n\n1795: 0\n\n1794: 0\n\n1793: 0\n\n1792: 0\n\n1791: 0\n\n1790: 0\n\n1789: 0\n\n1788: 0\n\n1787: 0\n\n1786: 0\n\n1785: 0\n\n1784: 0\n\n1783: 0\n\n1782: 0\n\n1781: 0\n\n1780: 0\n\n1779: 0\n\n1778: 0\n\n1777: 0\n\n1776: 0\n\n1775: 0\n\n1774: 0\n\n1773: 0\n\n1772: 0\n\n1771: 0\n\n1770: 0\n\n1769: 0\n\n1768: 0\n\n1767: 0\n\n1766: 0\n\n1765: 0\n\n1764: 0\n\n1763: 0\n\n1762: 0\n\n1761: 0\n\n1760: 0\n\n1759: 0\n\n1758: 0\n\n1757: 0\n\n1756: 0\n\n1755: 0\n\n1754: 0\n\n1753: 0\n\n1752: 0\n\n1751: 0\n\n1750: 0\n\n1749: 0\n\n1748: 0\n\n1747: 0\n\n1746: 0\n\n1745: 0\n\n1744: 0\n\n1743: 0\n\n1742: 0\n\n1741: 0\n\n1740: 0\n\n1739: 0\n\n1738: 0\n\n1737: 0\n\n1736: 0\n\n1735: 0\n\n1734: 0\n\n1733: 0\n\n1732: 0\n\n1731: 0\n\n1730: 0\n\n1729: 0\n\n1728: 0\n\n1727: 0\n\n1726: 0\n\n1725: 0\n\n1724: 0\n\n1723: 0\n\n1722: 0\n\n1721: 0\n\n1720: 0\n\n1719: 0\n\n1718: 0\n\n1717: 0\n\n1716: 0\n\n1715: 0\n\n1714: 0]" time="0.352"><properties><property name="score" value="0.0014716014" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rabi Kaul\n\nRabi Kaul (born 1951) is a social activist, writer, human rights activist, former Director of Amnesty International India, and former Chairperson of Alternative Law Forum, Bangalore, India. He is a graduate of the University of Delhi.\n\nHis human rights work has been a major part of his life since 1981 when he began his work in civil liberties defence and the protection of human rights in general, and of Dalit rights in particular. In the 1980s, he was active in the movement against the Emergency. He was in prison for a few months during that time. He is widely respected as a human rights activist, and one of the most important advocates for social justice in India.\n\nKaul served as the Executive Director of the International Humanist and Ethical Union, and as the International Secretary of the International Humanist and Ethical Union, and is a past Chair of the IHEU Coordinating Committee.\n\nHe has worked with Amnesty International since 1989. During his tenure with Amnesty International, Kaul was Director of the organization's Indian chapter, which he helped to build into one of the largest branches in the world. He served as the Regional Director of Amnesty International for South Asia. In December 2012 he was replaced by Raviya Ismail.\n\nKaul also serves as an adviser to the South Asia Human Rights Documentation Centre. He is a recipient of the UN Human Rights Award, the Yash Bharti Award and the \nPeople's Union for Civil Liberties (PUCL) Award, amongst other recognitions. He is also a recipient of the Gandhi Peace Prize (2011).\n\nKaul has written extensively on human rights issues, social justice, and democracy. He has published a number of books, including "Democracy, Minority Rights and Violence" (2008), "Religion, Violence and Non-Violence" (2005) and "Whither Secularism" (1999).\n\nHis publications include:\n\n]" time="0.384"><properties><property name="score" value="0.31636515" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Erskine Hamilton Childers\n\nErskine Hamilton Childers (; 17 June 1870 \u2013 20 November 1922) was an Irish politician who served as the fourth President of Ireland, from 25 June 1921 to his death on 20 November 1922. He was a member of the Irish Republican Brotherhood and Sinn F\xe9in.\n\nErskine Hamilton Childers was born in England in 1870, the eldest son of Robert Erskine Childers, a British Army officer and later a writer and political theorist.\n\nIn the course of his lifetime he spelled his surname in a number of different ways, including Childers and Childs.\n\nChilders attended school at Stubbington House, Fareham. At the age of 16 he became a clerk in a Southampton shipping office. He joined the Liberal Party and became a political speaker on its behalf. In 1899 he was elected as a councillor to Southampton County Borough Council.\n\nHe married Molly Zichy-Woinarski (sister of Francis "Frank" Zichy-Woinarski) in 1908, but had no children.\n\nChilders was a keen yachtsman, and in 1906, with Sir Thomas Lipton, he set up the Shamrock IV syndicate to challenge for the Americas Cup.\n\nHe participated in the unsuccessful Irish Convention of 1917\u20131918, a body established by British Prime Minister David Lloyd George which negotiated an agreement with Irish representatives in an attempt to end the period of Irish nationalist insurrection. The Convention, which met at Dublin Castle, made a number of suggestions regarding the governance of Ireland, which were partially incorporated into the Government of Ireland Act 1920. It was Childers, who, in September 1917, raised the need for a "conversation" between Irish and British leaders.\n\nAfter the Easter Rising of 1916, and his arrest for involvement, Childers helped reorganise the Irish Republican Brotherhood (IRB) in an effort to steer it towards constitutional activity and away from militancy.\n\nIn the 1918 general election, Childers stood as a Sinn F\xe9in candidate in Wicklow. Although he did not win the seat, he polled well and the Sinn F\xe9in party decided to nominate him as one of its members of the Irish delegation to the Paris Peace Conference. It was at the Paris Peace Conference that he met Arthur Griffith and became a convinced Irish republican.\n\nHe became a committed supporter of Arthur Griffith's Sinn F\xe9in party. In 1919, he was arrested and charged with sedition, because of his support of the Irish Republican Army (IRA).\n\nHe was elected unopposed as a Sinn F\xe9in Teachta D\xe1la (TD) to the 2nd D\xe1il at the 1921 elections for the Dublin Mid constituency. He supported the Anglo-Irish Treaty of 1921, and became a member of the Irish Free State Seanad in 1922.\n\nHe became the fourth President of the Executive Council of the Irish Free State (i.e. prime minister) in June 1921, and on 26 June 1921 he was appointed to the office of President of the Republic, (which was to become that of President of the Executive Council on the enactment of the 1922 Constitution in August 1922).\n\nIn 1921, the Government of Ireland Act 1920 split the island into two autonomous territories within the United Kingdom: the six north-eastern counties became Northern Ireland and the rest of Ireland became Southern Ireland, governed by the Irish Free State government in Dublin. However, the Parliament of Northern Ireland chose to opt out of the Free State in 1922. Under the terms of the Anglo-Irish Treaty, this meant that Northern Ireland would become part of the Irish Free State, but the British refused to accept this, saying it would lead to the "break-up of the United Kingdom". The Irish Taoiseach and President of the Executive Council (prime minister), W. T. Cosgrave, insisted that the British had breached the Treaty and that the Free State had the right to "withdraw from the British Commonwealth of Nations", but he chose not to use this option. Instead, he demanded that the Northern Ireland government do so, and thus abolish itself.\n\nChilders was shot dead in his home on Inishmore, Aran Islands, County Galway, in November 1922, two months after becoming President. The following January, the "Irish Independent" reported that Michael Noyk, the Russian Consul in Galway, and Joseph Murray, a member of the Irish Republican Brotherhood, were both implicated in his murder. The paper stated that Murray was sent by James O'Connor to warn Childers to stop political work in the Four Courts or else he would be killed, while Noyk knew of the plot and failed to notify the police. A police officer told the paper that he believed it was an ordinary robbery that "went wrong" as "Childers was too tough a man to be robbed".\n\n]" time="0.369"><properties><property name="score" value="0.372921465" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Sarah Williams (social worker)\n\nSarah "Sally" Williams (1880 \u2013 April 23, 1951) was an American social worker. Williams established herself as an activist, fighting for women's suffrage, juvenile delinquency, and public health. Williams was well known for her innovative and groundbreaking approaches to improving the quality of life for children, the public, and the underprivileged. Williams began working for the New York City Health Department in 1918, and in 1925 she became the director of the Bureau of Child Guidance. Williams was the only woman in the country with such a position at the time, and held the position until her death in 1951.\n\nSarah Williams was born in 1880 in Philadelphia, Pennsylvania, the second child of James Williams, a grocer and later a dentist, and Ella Burt Williams. At age 10, she attended the Powelton Avenue School in Philadelphia, and by age 12 she had already decided that she wanted to be a teacher. At age 13, Williams attended the Girls' High School and excelled academically. She took part in school plays and oratorical contests, and upon graduation, Williams attended Swarthmore College in 1896. Williams majored in Greek and Latin and continued to study oratorical contests and plays. After graduating in 1900, Williams continued her education at Cornell University, where she studied American History and Economics. While studying at Cornell, Williams became a member of the college women's debating team, which would later become a hobby for her. Upon graduation, Williams pursued graduate studies at Columbia University, where she received her M.A. degree in Social Science in 1907. At Columbia, Williams received one of her most important honors, the Demorest Fellowship. After graduation, Williams decided to enter the field of social work.\n\nAfter receiving her Master's Degree, Williams began to work as a social worker in Philadelphia. While working in Philadelphia, Williams became interested in the idea of juvenile courts, and worked to improve them. Williams began traveling to study different models of juvenile courts and while in London, she visited the Infant Welfare and the Juvenile Probation Departments. While visiting a British Probation Home, Williams became interested in the training of child welfare workers. She returned to the United States and started a training program for juvenile probation officers in Philadelphia.\n\nIn 1911, Williams accepted a job as the chief social worker of the Infant Welfare Association of Philadelphia. In 1915, Williams moved to New York City and accepted a position as the executive secretary of the Child Labor Committee. Williams continued her work with juvenile delinqu]" time="0.293"><properties><property name="score" value="0.27671748" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.27671748 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.27671748
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Tips for Buying Brooklyn End Tables By Bradington-Young\n\nHow to purchase a Brooklyn End Tables By Bradington-Young\n\nTop Tips To Help You Buy And Care For Your Furnishings It doesn't require much time to study this informative article, nonetheless the rewards are fantastic. You is going to be shocked whenever you realize how these guidelines alter your shopping behaviors. When it comes to furniture, there is little if any difference between affordable and top quality. You will get everything you buy and don't be concerned about inferior quality. If you adored this information and you would certainly such as to receive even more facts concerning best camping tents reviews i implore you to check out our own page. Solid wood furniture is perhaps the most suitable purchase. It lasts lengthier and requires less maintenance than different\n\nWhat you should know before buying end side tables .\n\nSmart Tips For Purchasing Quality Affordable Furniture It 's what holds your meal since you eat. What keeps one's body aloft when you sleep. What contains your best valuables to guard them. It holds your lamp, television and books. Furniture is available to us, within our office, at home and elsewhere. Learn how to be a smarter end side tables shopper by reading the below information. If you've got youngsters, you must avoid purchasing end side tables with sharp edges. Little ones have a tendency to trip and fall often which can create a visit to the emergency room if the end side tables has sharp edges. When buying end side tables for the family room, seek out simple styles. You may well be totally into that black leather couch, but a couch adorned with a bunch of floral designs is not something that you are going to be thankful for. You and your children can be happy with contemporary end side tables. Go shopping for end side tables with your hues as your guide. You might love a certain piece, but when you go it with the room, it may not hold the existing decor. Avoid this from happening. It's easy to by\n\nThis bed was as described, very easy to assemble, and had good instructions. Very nice and firm bed. Assembly went well. This bed was as described, very easy to assemble, and had good instructions. Very nice and firm bed. Assembly went well.\n\nBrooklyn End Tables By Bradington-Young...\n\n\n\nSee Products Descriptions & Reviews!!]" time="0.301"><properties><property name="score" value="0.5008499" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.5008499 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.5008499
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["This is the work of idiots who do not know what they are doing. They have no idea about cars, engines or aerodynamics, and in the end they will pay for it," team principal Peter Sauber said in a statement.\n\nF1 racing, one of the world's most lucrative sports, has for years been plagued by small teams on tight budgets. The sport's commercial supremo Bernie Ecclestone is trying to improve the situation and has created a fund, estimated to be worth up to $40 million, to support teams in dire straits.\n\n"The idea of taking money from one and giving it to the other is not very positive," Sauber said. "It creates the possibility of a new form of slavery. I do not think that anyone who worked in the factories during the war thought about whether a tank would end up being driven by a German or an Englishman. He was just happy to be making money. But people are not stupid, and there are some consequences that need to be considered. This is just crazy. It will never work."\n\nFerrari, BMW-Sauber, McLaren and Renault, four of the sport's top teams, have signed up to the initiative but Ferrari president Luca di Montezemolo said Sauber was missing the point.\n\n"If the results of the championship are being hampered by an imbalanced distribution of resources, then there is a reason for the redistribution," he said.\n\nSauber's team have won 10 world championships but are among a number of outfits on the verge of going under as the sport's top teams spend millions of dollars in search of an elusive tenth title.]" time="0.347"><properties><property name="score" value="0.13594165" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.13594165 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.13594165
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Paladin\n\nA paladin is the sworn defender of a group of creatures, a good-aligned organization, or a person. Most are deeply religious, but the few who aren't still serve their groups or causes with fanatical zeal. The paladin is essentially a warrior of the gods, and most spend their lives wandering the world of Oerth, aiding those they deem good or just. Although a paladin will fight to slay a horde of monsters or a mad king, he will not do so out of a lust for battle or destruction, but out of a need to keep the forces of darkness at bay.\n\nPaladins are renowned for their bravery, their unyielding dedication to the principles of good, and their mastery of martial arms. It is rare to find an evil paladin.\n\nAbilities: Strength and Charisma are both prime requisites for a paladin. Strength is his prime requisite, followed by Charisma. Strength governs how hard a paladin can hit, how effectively he can wear armor, and his carrying capacity. Charisma governs the strength of his spells and the DC's of his class skills. A paladin must be lawful good.\n\nHit Die: d10\n\nStarting Age: Complex.\n\nStarting Gold: Complex.\n\nClass Skills\n\nThe paladin's class skills are Concentration (Con), Craft (Int), Diplomacy (Cha), Handle Animal (Cha), Heal (Wis), Intimidate (Cha), Knowledge (nobility and royalty) (Int), Knowledge (religion) (Int), Profession (Wis), Ride (Dex), and Sense Motive (Wis).\n\nSkill Points at First Level: (2 + Int modifier) x 4.\n\nSkill Points at Each Additional Level: 2 + Int modifier.\n\nClass Features\n\nAll of the following are class features of the paladin.\n\nWeapon and Armor Proficiency: Paladins are proficient with all simple and martial weapons, with all types of armor (heavy, medium, and light), and with shields (except tower shields).\n\nAura of Good (Ex): The power of a paladin's aura of good (see the detect good spell) is equal to her paladin level.\n\nDetect Evil (Sp): At will, a paladin can use detect evil, as the spell.\n\nSmite Evil (Su): Once per day, a paladin can call out to the powers of good to aid her in her struggle against evil. As a swift action, the paladin chooses one target within sight to smite. If this target is evil, the paladin adds her Charisma bonus (if any) to her attack rolls and adds her paladin level to all damage rolls made against the target of her smite. If the target of smite evil is an outsider with the evil subtype, an evil-aligned dragon, or an undead creature, the bonus to damage on the first successful attack increases to 2 points of damage per level the paladin possesses. Regardless of the target, smite evil attacks automatically bypass any DR the creature might possess.\n\nIn addition, while smite evil is in effect, the paladin gains a deflection bonus equal to her Charisma modifier (if any) to her AC against attacks made by the target of the smite. If the paladin targets a creature that is not evil, the smite is wasted with no effect.\n\nThe smite evil effect remains until the target of the smite is dead or the next time the paladin rests and regains her uses of this ability. At 4th level, and at every three levels thereafter, the paladin may smite evil one additional time per day, as indicated on Table: Paladin, to a maximum of seven times per day at 19th level.\n\nDivine Grace (Su): At 2nd level, a paladin gains a bonus equal to her Charisma bonus (if any) on all saving throws.\n\nLay on Hands (Su): Beginning at 2nd level, a paladin can heal wounds (her own or those of others) by touch. Each day she can use this ability a number of times equal to 1/2 her paladin level plus her Charisma modifier. With one use of this ability, a paladin can heal 1d6 hit points of damage for every two paladin levels she possesses. Using this ability is a standard action, unless the paladin targets herself, in which case it is a swift action. Despite the name of this ability, a paladin only needs one free hand to use this ability.\n\nAlternatively, a paladin can use this healing power to deal damage to undead creatures, dealing 1d6 points of damage for every two levels the paladin possesses. Using lay on hands in this way requires a successful melee touch attack and doesn't provoke an attack of opportunity. Undead do not receive a saving throw against this damage.\n\nAura of Courage (Su): Beginning at 3rd level, a paladin is immune to fear (magical or otherwise). Each ally within 10 feet of her gains a +4 morale bonus on saving throws against fear effects. This ability functions while the paladin is conscious, but not if she is unconscious or dead.\n\nDivine Health (Ex): At 3rd level, a paladin gains immunity to all diseases, including supernatural and magical diseases.\n\nDivine Bond (Sp): Upon reaching 5th level, a paladin forms a bond with her god. This bond can take one of two forms. Once the form is chosen, it cannot be changed.\n\nThe first type of bond allows the paladin to enhance her weapon as a standard action by calling upon the aid of a celestial spirit for 1 minute per paladin level. When called, the spirit causes the weapon to shed light as a torch. At 5th level]" time="0.378"><properties><property name="score" value="0.023127267" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02312727 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02312727
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Suspension (mechanical)\n\nIn mechanical engineering, suspension refers to a system of shock absorbers and springs designed to improve the ride quality of a vehicle or other types of machinery. It is an essential component in wheeled vehicles, providing a convenient way to deal with irregularities in the road surface.\n\nMost modern vehicles are fitted with some sort of suspension. It is the primary means of isolating the passengers from the road, as well as absorbing the bumps and vibrations from the road.\n\nThe suspension system on a vehicle provides the following functions:\n\nThere are many systems available that provide all or most of these functions, but most can be categorized by their design and motion characteristics.\n\nThe simplest suspension systems are rigid, and often called "hard suspensions", because they don't use any fluid damping. Instead, they rely entirely on the elasticity of the metal or the springiness of the suspension elements to soak up the bumps. Some early vehicles used torsion springs as suspension, but modern systems almost all use either coil or leaf springs, or shock absorbers.\n\nThe first and simplest suspension system was used by the French inventor of the wheel, Leonardo da Vinci. It consisted of four flexible limbs connected to the carriage. These limbs served as both the suspension and steering system.\n\nIn addition, Leonardo designed a system that included advanced features such as brake linings, bearings and a double-action brake system. A suspension system for cars was introduced by M. Thon in France in 1898. It consisted of a network of rubber bands that took the place of conventional springs. The rubber bands were enclosed in a conventional coil-spring housing. An advantage of this system was its light weight. Thon's design was introduced to the United States by John M. Curtis in 1904.\n\nBy the 1920s, many independent suspension manufacturers were using the pneumatic springing system as the basis of their systems, as well as using rubber or steel cords for springing. The principal disadvantage of the pneumatic system is that the spring-pressure increases with the compression of the suspension. In addition, a system that is not correctly adjusted will not ride well.\n\nThe third kind of suspension system was developed by the Morgan Motor Company, based in the UK. In this system, the spring is attached to the frame, and the shock absorbers are attached to a special hub, which attaches to the front and rear axles. This system is still sometimes seen in modern cars, since it is less expensive than the other systems and in most cases provides an adequate ride. This system has not been popular in Europe and North America since the 1930s.\n\nThe most common suspension system in modern cars, used in everything from Ford Model Ts to the Chevrolet Corvette, is the "independent front suspension", or "live axle". In this system, the suspension is a more or less conventional system of springs and shock absorbers, with the additional feature of a locating link (the king pin in an axle-based suspension). This allows the axle to move up and down relative to the chassis. The locating link ends are attached to the car body, which provides the rolling element to the system.\n\nThe other feature of this system is the axle, which provides the pivoting element of the suspension system. The wheel hub is attached to the ends of the axle, and the wheel itself is attached to the hub. The spring system, located in the body of the vehicle, is attached to the axle via the locating link. The body of the car, therefore, provides the "pivot" of the suspension.\n\nA number of variations on this design have been used, most notably independent rear suspension, in which the rear wheels are located by a trailing arm (a form of wishbone) instead of the traditional transverse leaf spring. Another design commonly found on trucks is the "live rear axle". In this system, the axle is located by an arm from the leaf spring. The rear wheels can move up and down relative to the chassis without any location from the body.\n\nA design commonly used on many racing cars and on some passenger cars is the DeDion or De Dion suspension, named after its inventors, the De Dion brothers. In this system, the two wheels are located by a triangular or "semi-trapezoidal" bar. The pivot is provided by a bearing block mounted to the car body, while the pivoting point for the wheels is a ball joint on the axle.\n\nThe DeDion design is an expensive design, due to the cost of the wheels, brakes and other parts. However, it does provide excellent wheel location, as the wheels can be moved by several inches in any direction without affecting the steering.\n\nRacing cars generally use the DeDion system, as the location of the wheels is the primary function of the suspension system. However, it is also used on a number of sports cars, including the Jaguar XK120, the Maserati 3500 GT and the Lamborghini Gallardo.\n\nOne of the main disadvantages of the DeDion suspension is that the front wheels are not located directly above the chassis, and there is significant scrub radius. For example, a wheelbase of 86\xa0inches (218\xa0cm) on a vehicle with a wheel diameter of 18\xa0inches (46\xa0cm) would produce a scrub radius of around 8\xa0inches (20\xa0cm). This can cause the car to steer and corner differently depending on the tire wear, since the scrub radius is at its largest when the tires are new.\n\nWhile an advantage of the DeDion system is that it is lighter than a comparable design, this is not a major consideration for racing cars. However, since racing cars are generally not driven at high speeds for long distances, the "chassis bounce" caused by the scrub radius is not an issue.\n\nOne of the first types of suspension system was introduced by Earle Crooker and was called "Independent Coil Spring Suspension". It was a brand name that existed only in the late 1920s. The name was used by C. G. Ames Co.\n\nIn this system, the springs are attached directly to the frame. In this system, the wheel is attached to the axle, which is supported by a bearing attached to the frame, not the car body.\n\nThe primary advantage of this system is the ease with which the wheelbase can be changed. In most cars, the wheels are located by a link that is attached to the axle and the frame, and the wheels can move relative to the car body. In this system, there is a much smaller length change, as the wheels move up and down relative to the axle.\n\nThe disadvantage of this system is that the body is no longer a "pivot point" for the suspension. The body is now part of the suspension system. This makes it very difficult to change the camber of the wheels (i.e., the angle of the wheel relative to the car body). In addition, the wheel can only move in one plane, as the upper control arm and the lower control arm limit the movement of the wheel. The car may need to be aligned more often, as the geometry of the suspension can change more than a suspension system where the wheels move relative to the body.\n\nThis system is commonly found on American cars built in the 1940s and 1950s, such as the Nash Ambassador, Hudson, and other brands. It is less commonly found on European cars, although it was used on some Mercedes-Benz models]" time="0.626"><properties><property name="score" value="0.0149004365" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[L\u2019avvento di Zuckerberg ha definitivamente maturato il passaggio dalla televisione tradizionale a quella digitale. Il successo del prodotto Facebook per Smartphone ha determinato la consacrazione di un nuovo media che non si muove pi\xf9 solo tra i PC ma che, a partire da un apparecchio mobile, si espande a livello planetario. In un solo anno la piattaforma del social network di Menlo Park ha infatti scalato le vette dell\u2019ecosistema tecnologico con un balzo da 5,8 milioni di utenti nel 2010 a quasi 60 milioni di abbonati nel 2011.\n\nSe da un lato le prestazioni del prodotto Facebook per Smartphone hanno assicurato un rapido avanzamento delle quotazioni del titolo in borsa, dall\u2019altro l\u2019entrata in azione del colosso californiano \xe8 stata uno dei fattori principali per l\u2019incremento dei dati di traffico degli oltre 90 milioni di italiani che utilizzano ogni giorno Internet dal proprio smartphone.\n\nMentre negli Stati Uniti la situazione non \xe8 ancora perfetta ma le promesse sono grandi, in Italia il Facebook per Smartphone ha assicurato a Facebook il consolidamento di una base di utenti in crescita. Con le recenti performance che sta raggiungendo il social network, sempre pi\xf9 persone decidono di interagire dal loro smartphone con i contatti personali e gli amici di Facebook, grazie alle nuove funzionalit\xe0 dell\u2019applicazione che ha recepito le nuove esigenze degli utenti. Il fenomeno sta infatti dilagando in tutto il mondo, come dimostra il caso della Spagna che in poco tempo ha passato da 4 milioni di utenti a 15 milioni.\n\nTra le novit\xe0 dell\u2019applicazione troviamo un nuovo caricamento della home, in cui sono stati aggiunti i nuovi pulsanti \u201cGiochi\u201d e \u201cScrivi al tuo amico\u201d, inoltre sono stati eliminati i due pulsanti \u201cFoto e Storie\u201d che avevano originariamente l\u2019incarico di condividere le immagini su Facebook e Instagram.\n\nIl suo funzionamento si basa su un semplice scambio di messaggi in cui l\u2019utente, dall\u2019apposita interfaccia di Facebook per Smartphone, pu\xf2 utilizzare una tastiera per comporre il testo e inviarlo ai suoi contatti. L\u2019opzione gi\xe0 si integra con il servizio di messaggistica istantanea di Facebook, WhatsApp, e con Messenger. Per effettuare una ricerca \xe8 necessario digitare il nome di un contatto nell\u2019apposita barra delle ricerche.\n\nInoltre per chi non dispone di una connessione Internet a banda larga, \xe8 stata introdotta la possibilit\xe0 di caricare un\u2019immagine senza l\u2019obbligo di avere una connessione internet. L\u2019immagine viene caratterizzata da una piccola animazione che si sviluppa gradualmente sul display del telefono, permettendo di vedere il progressivo aggiornamento dell\u2019immagine.]" time="0.325"><properties><property name="score" value="0.8136215" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8136215 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8136215
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Minister for Justice and Equality, Charlie Flanagan TD, and Minister for Social Protection, Leo Varadkar TD, today launched a joint campaign in support of the Crosscare Pathways Project, a nationwide outreach service for rough sleepers.\n\nLaunched this morning in Dublin, the \u2018Living On The Streets\u2019 campaign aims to draw attention to the fact that there are approximately 1,000 rough sleepers in Ireland. The aim of the project is to help these rough sleepers access the appropriate support services, whether it be residential or non-residential. The campaign highlights the issue of rough sleeping in Dublin city, which is rising at an alarming rate, with an increase of over 40% in the number of people living on the streets since 2013. The campaign\u2019s focus is on raising awareness of this issue.\n\nThe campaign involves advertisements on the city\u2019s LUAS and Dublin Bus, as well as featuring on O\u2019Connell Street, Portobello and Talbot Streets. It also involves the installation of posters across the city, specifically in locations where the homeless are more likely to reside.\n\nSpeaking at the campaign launch, Minister Flanagan said: \u201cRough sleeping has reached record levels and has become a visible problem in our capital city. The launch of this campaign will increase awareness of the services provided by the Crosscare Pathways Project to rough sleepers, so that they are aware of the options available to them. Rough sleepers should be referred to the services that will best suit their needs. As Minister for Justice and Equality, I am particularly concerned to ensure that rough sleepers are not penalised for begging and sleeping on the streets.\n\n\u201cThe Government is determined to prevent and reduce homelessness, to support rough sleepers to exit homelessness, and to prevent homelessness for others at risk. Over \u20ac70 million has been provided to support homeless services and prevent homelessness, which includes funding to frontline services such as the Crosscare Pathways Project, who work to prevent rough sleeping by providing outreach support to rough sleepers.\u201d\n\nMinister for Social Protection Leo Varadkar said: \u201cThe \u2018Living On The Streets\u2019 campaign brings home the reality that the street is a harsh and unforgiving place to be, particularly during the winter months. The response from the public will be crucial if we are to address this problem effectively.\n\n\u201cThere are over 1,000 rough sleepers in Dublin city and unfortunately this is a significant increase on previous years. That is why it is so important that we engage the public, using this campaign as an opportunity to highlight the services available to rough sleepers, including the Crosscare Pathways Project. It is a complex problem that requires a complex response, involving a number of different organisations, as well as a societal change in attitude.\n\n\u201cWith the help of my colleague, Minister Flanagan, we have increased funding for the homeless to \u20ac70 million this year, which will provide more than 3,000 more beds in a wide variety of services. We have also agreed to provide an additional \u20ac5 million over the next two years.\u201d\n\nCrosscare Pathways Project is a national organisation with local services based in Ballymun, Jobstown, Dublin city centre, Trim, Waterford and Wexford. It provides a range of services to homeless people and others at risk of homelessness, as well as people sleeping rough, particularly those sleeping on the streets of Dublin. The Crosscare Pathways Project also provides services for homeless people in Carlow, Cork, Donegal, Dublin North, Dublin South and Dublin West.\n\nThe project\u2019s services include outreach services, sleeping bags, socks, warm clothes, food, clothing, showers, laundry and toiletries.\n\nThe campaign is the work of the cross-agency Dublin Central Area Partnership (DCAP), which is comprised of An Garda S\xedoch\xe1na, Dublin City Council, Dublin Regional Homeless Executive (DRHE), Dublin Fire Brigade, Dublin Regional Housing Executive (DRHE), Dublin Street Pastors, Homeless Hotline, Irish Red Cross, Samaritans, Simon Community and Street Reach.\n\nThe campaign is supported by a number of major partners including Dublin City Council, Bus \xc9ireann, Dublin Bus, Dublin Airport Authority, Transdev and Luas Cross City.\n\nENDS]" time="0.353"><properties><property name="score" value="0.0048067295" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00480673 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00480673
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[See the live USD price. Control the current rate. Convert amounts to or from BABB and other currencies with this simple calculator.\n\nHow did the currency on yesterday? The average value Babble price for convert (or exchange rate) during the day was $0.009986. Min. Babble value was $0.009322. Max. BABB price was $0.011702. BABB price dropped by 7.5% between min. and max. value. Let's see what's next.\n\nOlder news about Babble\n\nThe Babble increased by 15.27% on Thursday 17th of September 2019 Let's take a look at interesting data from yesterday. BABB price increased by 15.27% between min. and max. value. Max. BABB price was $0.010422. Min. Babble value was $0.008959. The average value Babble price for convert (or exchange rate) during the day was $0.010405. Keep it up.\n\nThe Babble dropped by 17.49% on Wednesday 16th of September 2019 How did the currency on yesterday? The average value Babble price for convert (or exchange rate) during the day was $0.010164. Min. Babble value was $0.009265. Max. BABB price was $0.011671. BABB price dropped by 17.49% between min. and max. value. Let's see what's next.\n\nThe Babble dropped by 23.23% on Tuesday 15th of September 2019 How was the currency exchange rate changed on yesterday? BABB price dropped by 23.23% between min. and max. value. Max. BABB price was $0.012727. Min. Babble value was $0.009289. The average value Babble price for convert (or exchange rate) during the day was $0.012042. Watch the next day.\n\nThe Babble increased by 16.08% on Monday 14th of September 2019 And we have data for yesterday. Min. Babble value was $0.009069. Max. BABB price was $0.011378. The average value Babble price for convert (or exchange rate) during the day was $0.010781. BABB price increased by 16.08% between min. and max. value. Certainly it is good news for all.\n\nThe Babble dropped by 7.02% on Sunday 13th of September 2019 Let's see on yesterday. BABB price dropped by 7.02% between min. and max. value. Min. Babble value was $0.010600. Max. BABB price was $0.011775. The average value Babble price for convert (or exchange rate) during the day was $0.011251. Let's see what's next.\n\nThe Babble increased by 5.37% on Saturday 12th of September 2019 Let's take a look at interesting data from yesterday. Min. Babble value was $0.010724. Max. BABB price was $0.011425. The average value Babble price for convert (or exchange rate) during the day was $0.010947. BABB price increased by 5.37% between min. and max. value. Certainly it is good news for all.\n\nThe Babble increased by 7.5% on Friday 11th of September 2019 How was the currency exchange rate changed on yesterday? BABB price increased by 7.5% between min. and max. value. Min. Babble value was $0.010348. Max. BABB price was $0.011268. The average value Babble price for convert (or exchange rate) during the day was $0.010825. Keep it up.\n\nAnother conversions\n\nUsc to Babble, Uro to Babble, Uralscoin to Babble, Uscoin to Babble, USD-e to Babble, Usdq to Babble, US Dollar to Bangladeshi Taka, US Dollar to Banca, US Dollar to Bancor, US Dollar to Bankcoin, US Dollar to Bancorplus, US Dollar to Bankera, US Dollar to Banca,]" time="0.362"><properties><property name="score" value="0.9596059" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.9596059 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.9596059
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Mick Campbell: Some Hilarious (but Informed) Jokes About Health Reform\n\nHealth-care reform is under way in the US and health-care reform is under way in Britain. Some people may not have noticed the second fact. Over here, the NHS is now the NHS 2.0, or 3.0, or whatever they are on to. We\u2019re getting used to the idea that it will always be changing, and changing in ways we\u2019re not in total control of.\n\nWith my dry British sense of humor, I\u2019ve always enjoyed the NHS. In fact, I like it so much that I even thought of emigrating to a country with an NHS \u2013 like, say, the USA. So what a treat to discover in my in-box this morning a compilation of jokes, half of them at the expense of the USA and half at the expense of the UK, about health-care reform.\n\nFrom London, Chris Salisbury compiled them, and here are a couple of samples. The first is about healthcare reform in the USA:\n\n\u201cHave you heard about the new Congressional Health Care plan?\u201d\n\n\u201cYeah, the government\u2019s going to give you half of what it takes away.\u201d\n\nAnd the second, about the NHS:\n\nA man is at the doctor\u2019s office, and the doctor tells him, \u201cI\u2019ve got some good news and some bad news for you.\u201d\n\nThe man says, \u201cWell, I can\u2019t take the bad news right now, so give me the good news first.\u201d\n\nThe doctor says, \u201cWell, the good news is that you have an 18-inch penis.\u201d\n\nThe man looks stunned for a moment, and then asks, \u201cWhat\u2019s the bad news?\u201d\n\nThe doctor says, \u201cYour brain\u2019s in your dick.\u201d\n\nThese jokes may be inaccurate, of course. For example, the doctors\u2019 pay packets are pretty great, and some of them can do much better work in the US than in Britain. But one thing I know is for sure: it\u2019s great to see the NHS getting some serious attention in the American media. I bet it makes the doctors happy.]" time="0.312"><properties><property name="score" value="2.252617" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nBuchbesprechung\n\nHeinz Wernicke: Das zerrissene Land.\n\n\n\n1\n\nEin erstaunlich gutes Buch, das sich auf das politische und wirtschaftliche Geschehen Deutschlands in der Epoche von 1870 bis 1950 bezieht. Es zeigt die Interessen, aus denen sich die in der ersten H\xe4lfte der Epoche g\xfcltigen Allianzen zwischen Reichswehr und Arbeiterschaft, den Kirchen, den Nazis und den Kapitalisten in der zweiten H\xe4lfte zu so erstaunlich verschiedenen Gebilden wandelten.\n\n\n\n2\n\nDas Buch kommt zu dem Ergebnis, dass der R\xfcstungsstaat, der heute aus der Weltkriegsgeneration stammt, sich schon in den letzten Jahren des Kaiserreichs vorbereitete und dass er nicht von der Weimarer Republik, sondern von dem inzwischen gescheiterten Gegner der Weimarer Republik konzipiert wurde.\n\n\n\n3\n\nEs schildert die Haltung des Kaisers und seines Adlatus Ebert zu der als Gro\xdfmacht \xfcberlebenswichtigen Schwerindustrie und zu dem Staat, der seit 1871 f\xfcr die industrielle Entwicklung garantiert hat.\n\n\n\n4\n\nEs stellt dar, wie und warum Hitler nicht auf einen Einmarsch in die Tschechoslowakei gefolgt ist und zeigt die Beweggr\xfcnde f\xfcr diese Entscheidung. Diese sind bis heute in der Diskussion \xfcber den Charakter des Nationalsozialismus vernachl\xe4ssigt worden.\n\n\n\n5\n\nEs berichtet \xfcber die Zusammenarbeit von milit\xe4rischer und ziviler Macht im Verwaltungsapparat der Wehrmacht w\xe4hrend des zweiten Weltkriegs, von den Vorg\xe4ngen im Inneren des Staatsapparats, der Gesellschaft und der Armee bis hin zum Prozess gegen die deutschen]" time="0.283"><properties><property name="score" value="0.07903905" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Most of the novels I enjoy are focused on romance, in whatever form it may come. I believe that there\u2019s something for everyone to enjoy, as the author does such a great job of portraying the characters in all their strengths and flaws. Sometimes they go a little over the top with the angst, and it isn\u2019t very realistic, but I understand why. There are authors who never experience any type of conflict with their characters, and the books just feel very one dimensional. Some books can have some really crappy endings, but I have learned to stay away from books that end with the couple together and happy but someone was murdered or something along those lines. I don\u2019t care for books that have the couple separated, but they\u2019ll come back together in the end.\n\nWhat I want in a good romance book is a good, if not a great, ending that makes me feel good, no matter what happens to the characters. As I mentioned earlier, I don\u2019t like books that end in tragedy, and they usually do end in tragedy. There are some that aren\u2019t too tragic, but they just aren\u2019t the endings that I like. This is where the author\u2019s job becomes very difficult. They have to give the reader a reason to feel the way they want them to feel about the characters. If they feel bad, they\u2019ve done their job. If they feel happy, they\u2019ve done their job. As a reader, I\u2019m not looking to be outraged, nor am I looking to be happy. I\u2019m just looking for something that makes me feel.\n\nOn the flip side of that, I know a lot of people don\u2019t want to be emotionally manipulated. They just want to read a book and enjoy it. They don\u2019t want to be forced to feel one way or another. They want to feel neutral. Neutral, to me, is a huge accomplishment in a romance novel. To me, a romance novel has to be able to get a person, even if they don\u2019t think it will, to feel something for the characters. In most books, people want to know how they can make a particular character do what they want them to do. In a romance novel, that\u2019s the main character. They want to know how they can make the characters fall in love, because they see themselves in one or both of them. How would they do it? How would they fix it?\n\nThat is what a reader does when they read a romance novel. They want to know how to fix the problems that the characters have. This is why the ending is so important. It has to make the reader happy, but not to the point where they roll their eyes or feel like they were taken for a ride. I have a great example. In the movie Now and Then, a woman tells her daughter that she is happy. When her daughter tells her that she is, too, she tells her that it\u2019s because they\u2019re both lying. They don\u2019t want to make each other sad, so they\u2019re lying to each other. This is the exact thing that happens in a lot of romance novels, in my opinion. They\u2019re trying to make the readers feel good, but in the process they\u2019re lying. To me, the ending has to make the reader feel what the author was trying to make them feel, not what they want them to feel.\n\nI\u2019m not saying that the book has to end the way I want it to. What I\u2019m saying is that I want the author to be honest. I want them to give me a believable ending that isn\u2019t just thrown together so that they can end the book. I want the ending to mean something, and I think that\u2019s what most readers want. Most people like to be happy, and a good book will give them that. The ending has to be good enough that the reader doesn\u2019t feel like they wasted their time, but also good enough that they\u2019re not completely disappointed. They have to be happy with the story, even if it wasn\u2019t exactly what they wanted.\n\nWhat are some of your favorite romance book endings?]" time="0.312"><properties><property name="score" value="0.016885994" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[There\u2019s nothing more adorable than a real life couple who gush over one another on social media and share the same love story. What\u2019s even more adorable is when you know that they found each other through social media.\n\nTake Brandon Flowers and his wife, Tana. The two met on Twitter and now, they\u2019re celebrating their five year anniversary. If you follow either of their social media accounts, you may have noticed some cute posts from them about their relationship. We want to thank them for allowing us to have a look into their love story, because they\u2019re too cute!\n\nAs fans of The Killers, we love hearing about their adventures.\n\nThey\u2019re pretty cute!\n\nThere\u2019s nothing more adorable than a real life couple who gush over one another on social media and share the same love story. What\u2019s even more adorable is when you know that they found each other through social media.\n\nTake Brandon Flowers and his wife, Tana. The two met on Twitter and now, they\u2019re celebrating their five year anniversary. If you follow either of their social media accounts, you may have noticed some cute posts from them about their relationship. We want to thank them for allowing us to have a look into their love story, because they\u2019re too cute!\n\nAs fans of The Killers, we love hearing about their adventures.\n\nThey\u2019re pretty cute!\n\nI'd just like to say that my wife is everything. \u2014 Brandon Flowers (@flowerboy) August 5, 2017\n\nWedding Day. Not on social media. So I don't know what people think. I know my wife is everything. That's all I need. \u2014 Brandon Flowers (@flowerboy) August 5, 2017\n\nOn the last night of a tour, getting some wife-y kisses. And in case anyone was wondering. This is how we roll. pic.twitter.com/zSXlfUgKXd \u2014 Brandon Flowers (@flowerboy) August 7, 2017\n\nOh yeah. Still be on tour, still be making music. Not yet a father, but that's coming. Still have some things left to do. https://t.co/CJ1vOs8lYA \u2014 Brandon Flowers (@flowerboy) August 7, 2017\n\nYes. It's true. I am getting married. And I'm marrying my best friend. And my favorite person. https://t.co/uOe3DjtMtQ \u2014 Brandon Flowers (@flowerboy) August 5, 2017\n\nThe next night, he admitted that he has not yet become a father, but he is working on it.\n\nDidn't say I was a father yet. Wasn't pregnant before. Wasn't even married. But I love my wife and my future kids. pic.twitter.com/uVEXZHScGz \u2014 Brandon Flowers (@flowerboy) August 6, 2017\n\nYep. Only day two and already love you so much more than I did yesterday. No, that's not enough. Still not enough. pic.twitter.com/cItd8b8HxY \u2014 Brandon Flowers (@flowerboy) August 8, 2017\n\nYou are a goddamn genius. No one can make me laugh like you. \u2014 Brandon Flowers (@flowerboy) August 8, 2017\n\nThe next day, Brandon shared the first picture of the newlyweds.\n\nTana and I on our wedding day. pic.twitter.com/6R5xT0P5zT \u2014 Brandon Flowers (@flowerboy) August 7, 2017\n\nI can't wait to see you two together at our wedding. \u2014 Brandon Flowers (@flowerboy) August 7, 2017\n\nI love my wife and I'm going to spend the rest of my life loving her. https://t.co/2h7LXqHxjC \u2014 Brandon Flowers (@flowerboy) August 7, 2017\n\nBrandon gave a shout out to his brother and the rest of the band for not spoiling their special day.\n\nThis is how much I love my wife. I would've wanted to come here tonight. But I didn't. https://t.co/ox7XY3sPGO \u2014 Brandon Flowers (@flowerboy) August 8, 2017\n\nJust a normal day. A normal day with my wife. She is my favorite person in the world. We have no plans. pic.twitter.com/vNNkIOCcUQ \u2014 Brandon Flowers (@flowerboy) August 8, 2017\n\nCurious to see the rest of their love story?\n\nHappy 5 years to the love of my life, my best friend and my favorite person. I still feel like I'm the luckiest]" time="0.319"><properties><property name="score" value="0.39810044" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[To a certain extent, the goal of the Trump administration's trade policy, as explained in a speech given by Commerce Secretary Wilbur Ross on March 1, is the creation of a "reciprocal" or "two-way" trading system in which all nations treat each other equally. While not naming China, the intended target of that policy was clear. The Chinese government, on the other hand, was not impressed.\n\nWriting in the English-language edition of China Daily on Monday, Ma Kai, vice-premier of the State Council, or China's cabinet, and chair of the National Development and Reform Commission (NDRC), countered the Trump administration's position by arguing that China has been the most open to foreign investment in the world for the past three decades.\n\nIn Ma's view, China is playing by the rules of free trade. The problem is that the rules that America wants are not the same rules that America has been playing by. The United States wants to be able to sell its goods and services into China, but it wants to block Chinese goods and services from being sold in America.\n\nSpecifically, Ma pointed to the issue of the U.S. $347 billion trade deficit with China, which is the focus of a U.S. investigation to determine whether China's government has unfairly subsidized certain industries.\n\nBut China is not subsidizing its industries, according to Ma. The U.S. trade deficit is simply a function of America's industrial overcapacity and under-consumption, as well as Chinese market and regulatory restrictions on certain industries.\n\nIn Ma's view, there is an easy solution to the trade deficit, and that is to allow China to import more agricultural products, textiles, and auto parts from the United States.\n\nThis is not the first time Ma has been forced to explain the Chinese position in the ongoing trade war. Last week, he held an hour-long interview with Charlie Rose, the television host. In the interview, Ma also said that he would not criticize the Trump administration for the position it is taking. Instead, he is simply trying to point out to the Trump administration that it is China that has been working toward a free trade regime, and that the American government has not been as open as the Chinese government has been in allowing Chinese companies to invest in American businesses.\n\nWhat Ma is really doing is not simply trying to engage in a debate about the nature of free trade, but to make sure that Americans understand how the Chinese government is fighting to protect its own economy from the American tariffs, while at the same time, maintaining a narrative of the mutual benefits of free trade.\n\nMa's interview with Charlie Rose can be viewed here:]" time="0.468"><properties><property name="score" value="0.18100971" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.18100971 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.18100971
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[What can I say about Sweet Lou's Bakeshop and Cafe in L.A.'s Chinatown other than, well, it is a little gem. If I had to choose one thing to eat every day for the rest of my life it would be a quiche from Sweet Lou's. Seriously. When I went to the Farmers' Market on Monday I bought one. I bought a quiche at the bakery next door too but I'm not too sure how good that one is. But I am very sure that the quiche from Sweet Lou's is absolutely delicious. And it's made from scratch.\n\n\n\nLou is such a sweetie. I know he'd be a fun guy to have coffee with. He owns a gorgeous old school bakery in Chinatown and the smells of fresh baked bread and sweet treats are incredible. So if you are ever in L.A., and you happen to be in the Chinatown area, go on over and get a treat from Lou. You'll be glad you did. And he even has a menu for the cafe part of his establishment and everything on it looks pretty good too. I need to get over there soon and try it out.\n\n\n\nHis website is a little hard to find, I'm not sure if that's just me or if it's hard for everyone. But I did find it.\n\n\n\nI'm a big fan of Lou's pies. They look good enough to eat!]" time="0.299"><properties><property name="score" value="0.35373473" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The G20, the \u201cShangri-La\u201d and the Global Trade War\n\nThe G20 is currently gathering in the Chinese city of Hangzhou. China has been actively preparing for the summit and has invested in the improvement of its infrastructure and public services. However, the relationship between China and the US has deteriorated in the past few weeks. The US has asked the WTO to look into what it describes as unfair treatment of US companies in China. Furthermore, the EU, the US and Japan have called for retaliatory measures against China, after the announcement of a new Chinese law to allow China to bypass international patents. On the other hand, there are indications that the Chinese government will relax foreign ownership restrictions in its auto industry, and also encourage the outflow of capital from the country. The theme of the summit is "Better Growth, Better World", and the three themes will be "growth", "inclusive growth", and "sustainable growth".\n\nAccording to a recent report by the World Bank, China has a great economic potential, yet faces severe challenges. These challenges include maintaining the economic growth, the management of urbanisation, the fight against corruption, the increasing inequality and the aging population. On the other hand, the report also concludes that China has the opportunity to become a major contributor to global growth, thanks to the fact that China is an important producer of capital, the country is growing in the manufacturing sector, and is also important in terms of consumption, which is expected to grow by more than 6% this year. The report also highlights the fact that China has been the biggest contributor to the global GDP growth in the last 15 years, with a contribution of 30%.\n\nOn the other hand, China is also a top trading partner of the US, with trade between the two countries amounting to more than $600 billion. Therefore, the potential of a trade war between the US and China would be dramatic. As the leaders of the two countries are gathering in the same city, the G20 summit will be an opportunity to address many of the issues between the two countries. As an example, the summit will discuss the sustainability of trade, both for exports and imports.\n\nIt seems that the US and China may be heading towards a trade war. If such a trade war will occur, it will have devastating consequences on both the US and Chinese economies, as well as on the global economy. Furthermore, the WTO may face a severe problem, as it would probably have to be the court of the two parties involved in the trade war. Thus, the G20 summit will be an important meeting and will represent a key opportunity for the leaders of the two countries to reach an agreement.]" time="0.310"><properties><property name="score" value="0.03421068" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Takes place three months after the events of Season 4, 'Brother's Keeper'.\n\nMax and Liz's lives were put on hold after George's tragic death, but now that the madness of the wedding season has passed, they're finally ready to start their life together. They've settled into their apartment, they're adjusting to working as a team, and even Chompy's finally feeling more like family than just another new roommate. They're finally back to their normal routine.\n\nExcept now, it's not.\n\nNow it's crazy.\n\nMax and Liz are supposed to be getting ready to take their first vacation in a very long time, but it turns out Liz isn't feeling up to it. She has a persistent cough, she's not sleeping well, and she's even started getting headaches. Max tries to be supportive as she talks about calling their doctor, but the more she says it, the more certain he becomes that something is seriously wrong.\n\nAnd then Liz stops talking. She won't talk to the doctor on the phone, she won't talk to Max, and she won't talk to the doctor when he comes to their apartment. She just smiles politely and lies to the doctor's face about how she's been feeling, and then makes Max drive her home as soon as the appointment is over.\n\nMax finally gets her to talk to him once they get home, but she can't tell him what's wrong. She just says that she's been feeling off, and doesn't know why. She refuses to go to the hospital, and eventually falls asleep on the couch, leaving Max alone to think about the phone call he has to make the next day.\n\nHe tells Hank, and his mind immediately goes to the worst case scenario. It doesn't help that when he went to visit Liz earlier, he saw a few of the guys from work lurking around outside their apartment. He had a feeling they weren't just paying him a social call.\n\nHe ends up calling Hank at two in the morning, rambling and stuttering and eventually saying it all in one long string of words. When he's done, Hank doesn't even need to tell him he was right.\n\nThe next day, Max wakes up to find Liz looking better than she has in weeks. There's a huge smile on her face, and she looks so happy. He's thrilled to see her finally feeling better, but he can't help but wonder if she's just hiding the fact that she's sicker than ever.\n\nHe can't bring himself to ask.\n\nShe starts working on her first assignment with a new partner a few days later. This new partner's name is Adam, and he seems like a pretty nice guy. Max watches Liz interact with him and can't help but wonder if he's doing the right thing by keeping her away from the wedding business. He knows how much she loves the job, and this is the first time he's seen her truly smile in a while.\n\nOf course, he doesn't get the chance to mention that to her. The moment he opens his mouth, she cuts him off and says she has a date with Adam.\n\nLiz goes on a date with Adam, and comes home late again. Max's heart sinks when she opens the door and he sees the smile on her face. It's not her usual smile, the one she saves for Max. It's the smile she reserves for Chompy and her art, and it's a smile he hasn't seen in a long time.\n\nMax knows what he's supposed to do, and he knows what's best for Liz. He knows that keeping her away from the wedding business is the best thing he can do for her. But he can't bring himself to do it.\n\nHe still isn't sure how she's going to take it when he tells her.\n\n"Oh my god," she says, and Max's breath catches in his throat.\n\nHe doesn't get a chance to tell her that he's sorry.\n\nShe rushes off the bed and takes the two steps necessary to cross the room. She throws her arms around him, and Max's whole body tenses at the unexpected contact. He can feel her shaking in his arms, and the sound of her sobs echo through his apartment.\n\nShe tells him she loves him, and he tells her that he loves her too. She pulls away, and he can see the tears streaming down her face. She says that she has to go, and he knows he has to tell her what he did.\n\nHe knows she'll be angry with him, and he's not sure how she's going to react.\n\nShe kisses him on the cheek, and then disappears out the door.\n\nHe doesn't go after her.\n\nMax calls Liz the next day, and tells her to come over to his apartment. She's silent the entire drive, and he's not sure what she's going to do when she walks in.\n\n"I'm sorry," he says, and she freezes in the middle of the living room.\n\n"I have something to tell you," he says, "and I'm going to need you to promise me that you'll stay calm."\n\nShe gives him a slow nod, and he knows she's not going to like what he's about to say.\n\n"I called Hank, and I told him that you were sick. That's why you haven't been going to work. I told him that you needed to take some time off, because you had a really serious case of strep throat."\n\nShe opens her mouth to say something, but he interrupts her and keeps going.\n\n"He didn't want to believe me at first, but I convinced him. I told him that it wasn't a big deal, but he needs to know if you start showing signs of weakness. He's going to call in a few days to check up on you. I told him you wouldn't answer your phone, and that's why he's calling here instead."\n\nHe sees the expression on her face, and he knows it's time to tell her the truth.\n\n"You're really sick, aren't you?" she asks.\n\nHe nods.\n\n"How sick?" she asks, and he knows this is the moment he's been dreading.\n\n"Very sick," he says, "It's Hodgkin's lymphoma. And it's probably already in your lungs."\n\n"When did you find out?" she asks, and Max can't stand to look at her. He turns away, and he's silent for a few moments.\n\n"I knew as soon as we got home," he says, and she goes completely still.\n\n"Max," she says, and he turns around.\n\n"I was afraid," he says.\n\n"You didn't have any right," she says, and he can see the tears in her eyes.\n\n"It was a bad idea," he says, "I know it was a bad idea."\n\n"What about me?" she asks, and he knows what she's asking.\n\n"You have to promise me that you'll stay out of the wedding business for a while," he says, "I can't risk you getting hurt."\n\nShe shakes her head.\n\n"You can't stop me from doing this," she says.\n\n"Liz," he says, and his voice cracks.\n\n"I'm not giving up on my dream, Max," she says.\n\n"It's not a dream," he says, "It's your life. It's your job, and I can't risk you getting hurt."\n\nShe shakes her head again.\n\n"You can't tell me what to do," she says.\n\n"I can and I will," he says.\n\n"We're not a team," she says, "We're not the Millers."\n\n"You're not the Miller," he says.\n\n"No," she says, "I'm the Keller."\n\nHe's never seen her like this before, and he realizes she's not going to let him stop her.\n\n"I'm doing this," she says.\n\n"No, you're not," he says, and he can see the fire in her eyes.\n\n"Don't tell me no," she says, "Don't tell me I can't do this."\n\n"I'm not telling you that," he says, "You're going to do this, no matter what I say."\n\nShe shakes her head.\n\n"I can't stop you," he says, "I know I can't. I'm not going to force you to do anything, but I am going to ask you to think about what you're doing."\n\nShe just stares at him.\n\n"You're not going to stop, are you?" he asks.\n\nShe shakes her head, and then walks out the door.\n\nLiz calls Max from work a few days later.\n\n"Why did you do it?" she asks.\n\n"I thought I was doing the right thing," he says.\n\n"I don't want to be a burden to you," she says.\n\n"I thought you were sick," he says, "I was just trying to help."\n\n"I know," she says, "And I appreciate it. It's just\u2026I'm not really sick. At least, not anymore."\n]" time="0.703"><properties><property name="score" value="0.158063065" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.15806307 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.15806307
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In this section we describe and analyze the effects of different problems on the model performance. In particular we consider the following problems: the serial position effect, the order effect, the semantic (in)sensitivity, and the distance effect.\n\nFigure 6.16 shows an example of text results of three sequences of three sentences. The whole process of filling and querying a WBS model is shown in Figure 6.17.\n\nWe can observe that in all three sequences the first sentence (\u201cA citizen of A is driving a car\u201d) is more frequently retrieved than the second sentence (\u201cA citizen of B is driving a car\u201d). The number of retentions for the first sentence is also higher than the number of retrievals for the second sentence, which can be attributed to the lexical and syntactic differences between these two sentences.\n\nAnother common problem in short sentences is the inter-sentence association: if a WBS model is designed to store sentences and not words, then the grammatical order of the sentences is kept in the model. Thus, the sentences that have the same word but a different order in the two sentences will be retrieved as if they had the same word. Figure 6.18 shows an example of sentences with the same words but a different order. As expected, the same sentences will have a higher number of retentions than the same words in the same order.\n\nThe serial position effect can be observed when words that occur in a specific position in the sentences are more retrieved than the same words that occur in different positions. This effect can be attributed to the influence of the semantic context on the recognition of the words that are at the same position in different sentences, and the words that are not in the same position have a different semantic context that makes them not to be recognized as if they were in the same position. Figure 6.19 shows an example of sentences with the same words in the same order but with a different position in each sentence. In this example, the word \u201cof\u201d in the position 5 of the first sentence is more retrieved than the same word in the position 7 of the second sentence, and the word \u201cof\u201d in the position 3 of the second sentence is more retrieved than the same word in the position 6 of the third sentence. This effect is more noticeable when the word \u201cof\u201d is repeated.\n\nIn this section, we present the results of a search on the Corpus of Contemporary American English (COCA) [44] with the retrieved words and their respective sentences in a sentence. For each sentence, the average of the values of the retrieval frequencies for all the words in the sentence is computed. We show in Figure 6.20 the relative frequencies of the average values for each word-type for all the sentences of the corpus.]" time="0.444"><properties><property name="score" value="0.028417287" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In two years, after graduating with a master's in fine arts, he would do what he was paid to do: act in a studio's movies.\n\nBut then in the late 1960's, "you couldn't see any kind of independent films," he said. "We had two major studios, MGM and RKO. The independents didn't get a chance."\n\nSo he decided to make one of his own. After asking students at the graduate film program of the New York University Film School for help, he gathered friends and shot his first film, "Mr. Mom," about a laid-off advertising executive who becomes a housewife, in 1970.\n\nThe low-budget, independent film, directed by a woman and starring a cast of talented newcomers, was ahead of its time. Many viewers laughed, he said, at the notion of a housewife as a career woman. Others did not understand the film's subtle humor.\n\nPhoto\n\n"The primary thing people didn't understand was it wasn't supposed to be funny," he said. "It was dramatic."\n\nThe film cost $25,000, and he sold it to Warner Brothers for $50,000. "We got drunk for two weeks," he said. "It was our first film. We were elated."\n\nHe went on to make six more films as a director and actor. But the money he made was eaten up by the next movie, as well as his divorce, children and a country house in New Hampshire, he said.\n\nNewsletter Sign Up Continue reading the main story Please verify you're not a robot by clicking the box. Invalid email address. Please re-enter. You must select a newsletter to subscribe to. Sign Up You will receive emails containing news content , updates and promotions from The New York Times. You may opt-out at any time. You agree to receive occasional updates and special offers for The New York Times's products and services. Thank you for subscribing. An error has occurred. Please try again later. View all New York Times newsletters.\n\nThen he met Nancy Chase, a writer and former actress who would become his second wife. She had grown up in a suburb of New York City and attended St. Agnes School in the city's West Village and a private high school.\n\nAdvertisement Continue reading the main story\n\nMs. Chase knew nothing about film, he said. But she was interested in Mr. Moore's films, especially "Slackness," which came out in 1981. She asked if he would like to work on a screenplay she was writing. He agreed.\n\n"I thought this was a possibility to get out of the mess I was in," he said. "It was a partnership. I had a chance to work on a screenplay with her. And she had a chance to write something. And then we got married."\n\nThey met in 1983. A year later they married and went on to make several more films.\n\nMr. Moore said that he and Ms. Chase had a very "civilized" divorce after 23 years. "We've been married long enough that we have two children who are married, who are professionals," he said. "They're both people who are not into the entertainment business. So they're good children."\n\nMr. Moore also has two other children. He did not see his first wife, Kay, and their children after they divorced in 1973.\n\n"I didn't find it productive to go back into my son's life," he said. "I didn't want to be a hero and make up. I didn't want to see him have a second set of delusions about me. I've always believed that children should be given credit for being capable of determining who their parents are. I didn't want to be a subject of people's emotions."\n\nHe recently remarried, and now lives with his wife, Eileen Minnelli, in a three-story, six-bedroom house that sits behind a wrought-iron gate on a leafy residential street in Mill Valley, Calif.\n\nA self-described "indiscriminate reader," Mr. Moore spends much of his time writing short stories and screenplays. And he has plans for at least two more films. One is about a woman who was institutionalized in the 1960's, after becoming pregnant. The other is about the son of an interracial couple who is raised by his mother's relatives and becomes a neo-Nazi.\n\n"I have a lot of things to say, and I don't have a problem saying them," he said. "I haven't changed my approach to making films at all."]" time="0.355"><properties><property name="score" value="0.043445732" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04344573 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04344573
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Jets quarterback Mark Sanchez practiced for the first time this week and appears on track to start Sunday against the Tennessee Titans.\n\nSanchez's right shoulder strain limited him in practice Wednesday, but he took most of the first-team repetitions. He was 15 of 19 passing with no interceptions and no sacks against a second-team defense. He said after practice that he would play against the Titans if the game were today.\n\n"It's great, it's great," Sanchez said of his arm strength. "The most important thing with an injury is to get the strength back. We're seeing good results of that. ... That's the main thing."\n\nThe Jets quarterback was injured in the second quarter of Sunday's 24-17 victory over the Baltimore Ravens, and rookie Greg McElroy came off the bench and played well in relief. McElroy completed 13 of 19 passes for 153 yards and a touchdown and was sacked twice.\n\nSanchez said it's not hard to prepare to play in his first game since the injury.\n\n"This is the first week I'm really getting to throw a lot," he said. "I've got to get back into a rhythm. That's what it's about. ... I'm excited. I'm ready to go."\n\nThe Jets have to make a decision on their starting quarterback by Tuesday, when players return from their four-day Thanksgiving break. Coach Rex Ryan said it's not a tough call at this point.\n\n"We'll see," Ryan said. "We've got another day of practice. That's what we've got to look at and see how the situation unfolds.\n\n"If you just look at where he is at this point, he looks good. You look at what Greg did, too. You look at what we did against a good team with a lot of different players."\n\nRyan said the decision to start Sanchez or McElroy has "absolutely nothing to do with any kind of controversy or anything like that. We've got a good quarterback. We know we have two good quarterbacks. You guys want to make this some big controversy, but that's not the case."\n\nMcElroy said he is excited for Sanchez and happy for himself, as well.\n\n"When you have two quarterbacks, you're going to get one of them going," he said. "I'm excited to see Mark back. It's a good thing."]" time="0.284"><properties><property name="score" value="0.23760551" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Sir Robert Hart, 1st Baronet\n\nSir Robert Hart, 1st Baronet (22 November 1823 \u2013 1 September 1905) was a British diplomat who worked as chief inspector of Chinese Maritime Customs.\n\nHart was born in Fermoy, County Cork, Ireland. His father was a physician, and his mother was the daughter of another doctor. He was educated at Fermoy Grammar School.\n\nHart's father died when he was twelve, leaving the family in financial difficulties. Hart was forced to earn a living and so took a job as a clerk in the Civil Service of the East India Company at a salary of \xa3100 per year. He became fluent in Urdu and Hindi. After six years, he left the service of the East India Company and moved to China.\n\nHe joined the Chinese Imperial Maritime Customs in 1851. He worked at Amoy in Xiamen and at Shanghai. He worked at Fuzhou and Hong Kong. He spent some time in Macau before moving to Canton in 1859. In 1863, he was promoted to Inspector General. Hart was promoted again in 1871 to Chief Inspector, and became Inspector General in 1882. In that position, he was responsible for administering and enforcing the Chinese Maritime Customs' rules and regulations and for conducting negotiations with other governments. He negotiated many new treaties with foreign powers. He retired from that position in 1897. He died in London in 1905.\n\nThe famous novel "Lost Horizon" by James Hilton has a British consul who is modeled after Hart.\n\nHart was created a Baronet, of Claremont in the County of Cork, on 10 August 1899. He received several honours and decorations from foreign governments, including the Grand Cross of the Order of the Bath from the British government, the Grand Cross of the Order of Leopold and the Legion of Honour from the Belgian government, and the First Class Order of the Double Dragon from the Chinese government.\n\nOn his death, he was succeeded as baronet by his eldest son Sir Ronald Hugh Stewart Hart, 2nd Baronet.\n\n\n]" time="0.312"><properties><property name="score" value="0.30382717" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Chris Van Gorder\n\nChris Van Gorder (born March 16, 1955) is the former head coach for the women's basketball team at the University of Cincinnati. Van Gorder coached at Ohio University from 1985 to 1996, where he posted a 204-163 record.\n\nVan Gorder was the head coach at the University of Akron for ten seasons. During his tenure, he compiled a record of 157-108. Van Gorder was the first head coach of the Akron Zips women's basketball team.\n\nIn 2005, he was named Mid-American Conference Coach of the Year after his Zips finished 22-9 and went to the NCAA Tournament.\n\nIn the 2006-2007 season, the Zips started the season ranked 12th nationally but dropped out of the rankings following a 65-67 home loss to Western Carolina. Despite the loss to Western Carolina, Van Gorder's Zips won the Mid-American Conference regular season title and the Mid-American Conference Tournament. Van Gorder's Zips then lost to Tennessee in the first round of the NCAA Tournament.\n\nIn the 2007-2008 season, Van Gorder's Zips were not ranked to start the season. But after two early victories against ranked opponents, Van Gorder's Zips were ranked 25th in the nation. Van Gorder's Zips remained in the top 25 for a majority of the season and won the Mid-American Conference regular season championship for a second consecutive year. After a first-round loss in the NCAA Tournament, Van Gorder was named Mid-American Conference Coach of the Year for the second time in three seasons.\n\nVan Gorder was let go at the end of the 2012 season and hired by the University of Cincinnati on April 5, 2013. He resigned on May 4, 2015.\n\nVan Gorder is married to the former Deborah Beisecker, a native of Knoxville, Tennessee. The couple has a daughter, Jennifer, and two sons, Cody and Collin.\n]" time="0.294"><properties><property name="score" value="0.1860481" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[2010 Spanish Grand Prix\n\nThe 2010 Spanish Grand Prix (formally the XLV Gran Premio de Espa\xf1a Telef\xf3nica) was a Formula One motor race held on 28 May 2010 at the Circuit de Catalunya in Barcelona, Spain. It was the seventh round of the 2010 Formula One season. The 60-lap race was won by Red Bull driver Mark Webber, after he started from second position. Lewis Hamilton finished second for the McLaren team and Ferrari driver Fernando Alonso came in third.\n\nPirelli's prime tyre compound was the hard "primes", whilst the option tyre was the soft "option" compound.\n\nMark Webber took pole position for Red Bull, his first since the 2009 Belgian Grand Prix, while Fernando Alonso set the fastest time in Q2 and qualified second. The two Ferraris filled the next row with Felipe Massa ahead of Kimi R\xe4ikk\xf6nen. The two McLarens of Lewis Hamilton and Jenson Button were fifth and sixth, with Nico Rosberg in seventh place, having struggled all weekend with the handling of his Mercedes. Adrian Sutil in the Force India was eighth, followed by Sebastian Vettel in the second Red Bull and Nico H\xfclkenberg in the Williams. Paul di Resta, S\xe9bastien Buemi and Michael Schumacher rounded out the top ten. At the start, Mark Webber led away from Fernando Alonso and Felipe Massa while the two McLarens of Hamilton and Jenson Button slipped backwards, with Hamilton eventually being forced to pit with an electrical problem, and Button dropping to eleventh. Mark Webber's race soon went wrong as he came into the pit lane to switch to his wet weather tyres on lap 11, but was told to remain in his pit box as he had not switched off his engine, having forgotten to do so. This meant he was stationary for 23 seconds and dropped to fourth, before recovering to third by the time he rejoined the circuit. He also had to serve a drive-through penalty for passing Alonso on the grass, although he eventually finished fourth.\n\nAlonso and Massa pitted on laps 18 and 22 respectively, rejoining in second and third places behind the McLaren of Lewis Hamilton, who had made an early pit stop for dry tyres and was running a different strategy to the two Ferraris. With the track still wet, Hamilton, Massa and Alonso all switched to the intermediate tyres on lap 25, but at this point, the gap between the top three was only 1.3 seconds. The McLarens of Hamilton and Button were then unable to pass the Ferraris on the drying track and they began to slip backwards, eventually losing their fourth and fifth places to the two Force Indias of Adrian Sutil and Paul di Resta. The latter had passed Sutil on the main straight on lap 30 after the Force India driver had made a pit stop and had a clear track in front of him, and held on to fifth place despite being passed by Sutil a few laps later. The two Toro Rossos of Jaime Alguersuari and S\xe9bastien Buemi were the first of the lead lap cars to pit on lap 28, with Alguersuari dropping behind Rosberg in the standings after pitting earlier than the Mercedes driver. The other Toro Rosso of Sebastien Buemi managed to stay out longer and maintained his eighth place, before making a pit stop at the end of lap 34.\n\nFurther back, Jenson Button was the first of the two McLarens to pit for new tyres on lap 33, with a nine-second stop due to an electronics problem with the wheel gun which meant the front left tyre was not fitted correctly. Team-mate Lewis Hamilton followed suit a lap later and rejoined the race in twelfth place. Button rejoined the race behind S\xe9bastien Buemi and passed him on lap 36, but was behind Adrian Sutil when he stopped for fresh tyres on lap 38, although Button was able to pass Sutil a few laps later, with Buemi also getting ahead of the Force India. At the end of the 43rd lap, Lewis Hamilton had managed to pass Paul di Resta and move up to eighth place, with Sutil falling to ninth, having been passed by both Buemi and Button. Hamilton's battle with Buemi came to an end on lap 44 as the two McLarens pitted together, with Hamilton getting ahead]" time="0.317"><properties><property name="score" value="0.028957194" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02895719 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02895719
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[2015\u201316 UEFA Women's Champions League\n\nThe 2015\u201316 UEFA Women's Champions League was the 12th edition of the European women's championship for football clubs. The final was played between Frankfurt of Germany and Lyon of France, which Frankfurt won on a penalty shoot-out following a 1\u20131 draw. The win was the first time a German team had won the competition.\n\nGerman teams won both the main round groups, and Frankfurt also won the play-off round group, while German and French teams dominated the knockout phase. Frankfurt defeated Arsenal 3\u20131 in the final, while Paris Saint-Germain defeated Barcelona 3\u20132 in the match for third place.\n\nStarting from this season, the following changes were introduced:\n\nThe allocation of teams into qualifying and qualification is as follows:\n\nUEFA has scheduled the competition as follows (all draws are held at the UEFA headquarters in Nyon, Switzerland).\n\nThe schedule of the competition is as follows (all draws are held at the UEFA headquarters in Nyon, Switzerland).\n\nThe draw for the qualifying round was held on 22 June 2015. The first legs were played on 27 and 28 August, and the second legs were played on 3 and 4 September 2015.\n\nThe first legs were played on 17 and 18 September, and the second legs were played on 24 and 25 September 2015.\n\nThe first legs were played on 1 and 2 October, and the second legs were played on 22 and 23 October 2015.\n\nThe first leg matches were played on 6 and 7 November, and the second legs were played on 20 November 2015.\n\nThe first leg matches were played on 1 and 2 December, and the second legs were played on 13 December 2015.\n\nThe first leg matches were played on 17 and 18 January 2016, and the second legs were played on 24 and 25 January 2016.\n\nThe draw for the round of 16 was held on 27 January 2016. The first legs were played on 7 and 8 March, and the second legs were played on 14 and 15 March 2016.\n\nThe first leg matches were played on 7 and 8 April, and the second legs were played on 14 and 15 April 2016.\n\nThe first leg matches were played on 12 May, and the second legs were played on 19 May 2016.\n\nThe first leg matches were played on 25 and 26 September, and the second legs were played on 2 and 3 October 2016.\n\nThe final was played on 15 May 2016 at the Stadion im Borussia-Park, M\xf6nchengladbach, Germany.\n]" time="0.318"><properties><property name="score" value="0.0020866848" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Kawanishi N1K\n\nThe Kawanishi N1K "Ky\u014df\u016b" (\u5f37\u98a8, "Strong Wind") was a long-range single-seat carrier fighter aircraft, serving the Imperial Japanese Navy Air Service during World War II. It was a single-engined, single-seat monoplane fighter designed to replace the A6M Zero, which was designed for shorter ranges.\n\nThe N1K was developed to replace the Nakajima A6M Zero in the long-range fighter role, and was the first fighter in the world to use the Type 3 "Hakury\u016b" 18-cylinder air-cooled radial engine, which was also used in the Kawanishi N1K1-J "Shiden" fighter. The Japanese Navy also gave it the name "Kyofu" (meaning "Strong Wind") as the manufacturer's symbol, the first time a name was given to a Japanese military aircraft.\n\nIn the end, only a handful of N1K1 fighters (armed with two 20\xa0mm cannon and two 12.7\xa0mm machine guns) were deployed operationally before the end of the war, and none ever engaged enemy aircraft in combat. After World War II, the Allied Occupation forces in Japan took possession of six N1K1 fighters and four N1K2 fighters. These aircraft were studied and flight tested by the Technical Air Intelligence Unit (TAIU) at Tachikawa. Test flights and subsequent analysis revealed that the N1K2 was the faster of the two types, but its lighter armament was deemed inadequate for combat, and the aircraft was regarded as lacking in manoeuvrability.\n\nFollowing the war, some of the N1K2 aircraft were provided to the USSR, and some were used by the "Taiwanese Air Force" (ROCAF), until all remaining aircraft were destroyed by a typhoon in 1950.\n\n\n\nThe only two remaining airworthy N1K2-J Shiden, on display in Japan, are preserved at the following museums:\n\nThe only remaining N1K1-J is on display at the Planes of Fame Air Museum in Chino, California. The airframe was recovered from the ocean in 1994 by Paul Allen and Don Arndt, restored to static display configuration and placed on display at the museum in 2003. The N1K1-J was removed from display in late 2013 for a full restoration, including flight testing, and returned to display on March 10, 2017.\n\nThe Soviet Union took possession of several of the N1K2-Ja variants and used them as the prototypes for the development of the Mikoyan-Gurevich MiG-15.\n\nTwo Shiden's survive in Taiwan. They are located in the Republic of China Air Force Museum in Taipei.\n\n\n]" time="0.296"><properties><property name="score" value="0.84200984" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.84200984 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.84200984
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[BLACK SABBATH star Tony Iommi says that he has "no plans" to reunite with Ozzy Osbourne for another album or tour following the release of the group's new album, "13", in June (13).\n\nThe metal legends are about to launch their final world tour after performing in Latin America this month, but while fans can expect to see Osbourne and Geezer Butler at the shows, Iommi reveals that the band will not attempt to bring bassist Bill Ward back into the fold.\n\nHe tells Rolling Stone magazine, "There's no plans for another album or tour with (Ward). And the bottom line is that I wish him well, but I just can't go back. It's been too long. I just can't do it again."\n\nHe continues, "I'm not going to say that I'll never work with (Ward) again, but I'm not going to try to work with him again for the sake of the fans. It wouldn't be right. It wouldn't be fair."\n\nIommi also admits that he is baffled by the criticism Osbourne received for his behaviour during the band's Rock And Roll Hall Of Fame induction in April (13).\n\nHe says, "I know he's had problems over the years with drink and that, but I don't really know. All I know is what he did at the Hall Of Fame, which was absolutely incredible, because it was one of those rare moments when you see somebody and you know they're completely sober. It was really good."\n\nHe adds, "I really couldn't understand the criticism. But then again, I'm pretty thick-skinned about stuff like that. I can take it."]" time="0.339"><properties><property name="score" value="1.103002" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.103002 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.103002
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["When you have a lot of money and power, sometimes you think you can buy yourself out of anything." \u2015Ben Urich [src]\n\nJohn Bushmaster was a powerful crime boss and drug dealer, having inherited control of Harlem's Paradise after his brother, Quincy, was shot and killed by Luke Cage. Bushmaster was also the head of the ruthless Bushmaster drug cartel.\n\nContents show]\n\nBiography\n\nEarly Life\n\nNot much is known about John Bushmaster's early life, except that he was once involved in organized crime. He became a drug lord and took over his brother's position as head of Harlem's Paradise. He later became involved in the criminal organization known as the Hand.[1]\n\nLuke Cage's Power\n\n"Tell me where they took Misty Knight."\n\n"What are you going to do with me?"\n\n"Well, I'm not going to let you walk away."\n\n"Who's going to stop me?"\n\n"Luke Cage." \u2015Luke Cage and Bushmaster [src]\n\nWhen Bushmaster witnessed Luke Cage throw a man out of Harlem's Paradise for harassing some young women, he asked his brother, Quincy, to help him get rid of the unruly patron. The next day, Bushmaster called the man who was threatening to sue Harlem's Paradise and threatened to kill him. When Cage returned, Bushmaster tried to persuade Cage to leave by telling him he did not belong there. Bushmaster revealed to Cage that his name was John Bushmaster and that he was the owner of Harlem's Paradise. When Cage insisted that he would be staying, Bushmaster noted that he did not know who he was messing with before Cage told him he was messing with Luke Cage.\n\nCage remained in Harlem's Paradise and caused problems for Bushmaster, much to his annoyance. Bushmaster and his men began selling the Bushmaster drug throughout Harlem. Cage overheard Bushmaster's name when it was said by his brother Quincy during a phone call. When Cage visited Bushmaster at Harlem's Paradise and accused him of being behind the Bushmaster drug, he denied it and told Cage to leave. Bushmaster's men, however, confronted Cage and attacked him. Cage easily overpowered all of them and escaped from Harlem's Paradise.[1]\n\nChasing Misty Knight\n\n"I'm getting sick of your bullshit."\n\n"Is that what you tell all the girls?" \u2015Bushmaster and Misty Knight [src]\n\nWhen Cage attacked one of Bushmaster's drug warehouses and threatened to kill Bushmaster if he did not tell him where he was keeping Misty Knight, Bushmaster told him that he did not know what he was talking about and Cage attacked him. Bushmaster ordered his men to shoot Cage while he escaped. The bullets did nothing to Cage as they could not penetrate his skin.\n\nBushmaster visited Pop's Barber Shop and threatened to burn down Pop's Barber Shop and kill everyone inside if he did not get a haircut, including the young girl named Tilda Johnson, who could do a mean cornrows, before he left. Tilda snuck out of the shop and stole Bushmaster's car while he was inside getting a shave. Bushmaster ran outside and found Tilda attempting to get away. He then chased after Tilda in the stolen car.\n\nTilda was able to evade Bushmaster's pursuit until he was able to push her car off the road and caused her car to roll over and crash. Bushmaster dragged Tilda from her car and found out who she was. Tilda, however, was rescued by a bystander who had witnessed the entire incident and called the police. Bushmaster was arrested for kidnapping, but he was released from police custody later.[2]\n\nBusiness Proposition\n\n"Now, we are making money, yes, but not as much as we should. It's a competitive market, man. You're good. And that girl, well, she's something else. I'm offering you a piece of this action. 25% for the both of you."\n\n"That's not how this works."\n\n"You know what? It is how this works. It's time for you to grow up." \u2015Bushmaster and Shades [src]\n\nBack at Harlem's Paradise, Bushmaster offered Shades a percentage of his drug business, but Shades refused. Bushmaster made an offer to Diamondback to sell him some of his product in exchange for a fee. Bushmaster met with Shades, who berated him for not being a better businessman and selling to Diamondback. Shades told Bushmaster that he was selling drugs on his own, but Bushmaster told him that he had a plan to sell his drugs in Bushmaster branded bullets. Bushmaster then attempted to seduce Shades' wife, Tilda Johnson, but she refused his advances.\n\nThe next day, Bushmaster gave a speech to the patrons of Harlem's Paradise as they celebrated the end of their evening. Bushmaster boasted about his power and demanded that they bow to him, but was met with little response. Shades then insulted Bushmaster, who then drew his gun on Shades. Luke Cage then attacked Bushmaster, but Bushmaster managed to get the upper hand and beat Cage into submission. As Bushmaster prepared to shoot Cage, Tilda Johnson shot Bushmaster in the chest with a concealed gun and stole his gun, with Shades shooting the other members of Bushmaster's entourage before they could react.\n\nBushmaster and his men went into hiding at a warehouse, where Bushmaster furiously scolded Shades for his betrayal. Shades explained that he had been working with Diamondback, but now wanted to make a better life for himself and his wife. Bushmaster, realizing that Shades had a point, agreed to go into hiding for the night. The next day, Bushmaster was visited by Knight, Shades, and Cage. Knight had returned to take back Harlem's Paradise. Knight gave Bushmaster a chance to surrender, but Bushmaster refused and attempted to shoot Knight, but was overpowered by Cage and Knight, forcing him to surrender.\n\nWhile Knight and Cage prepared to transport Bushmaster to Ryker's Island, Bushmaster told them that the shipment of drugs would be arriving that night. The police tried to stop the convoy, but the SWAT team was gunned down by Bushmaster's men. Knight decided to attack the warehouse to stop the shipment from getting to New York. Knight, Cage, and Bushmaster fought his men while Tilda Johnson fought Diamondback and his men, although Diamondback managed to escape from the scene.\n\nOnce Knight and Cage subdued the rest of Bushmaster's men, Knight interrogated Bushmaster about where the shipment was. Bushmaster told them that the guns had already been sold to a man named Ricky. Knight and Cage traveled to a diner to look for Ricky, where they found Ricky talking to his partner Rico. Knight threatened Ricky into giving her the location of the shipment. Once Ricky told Knight the location, she and Cage drove to the location where the guns were being shipped. Knight was able to steal the guns from the men who were shipping them, but one of Bushmaster's men threw a grenade into the truck. Cage managed to catch the grenade and toss it back at Bushmaster's men, but was then hit by the truck, knocking him unconscious. Knight ran Cage to the hospital while Bushmaster's men reclaimed their guns and returned them to Bushmaster.[3]\n\nPersonality\n\nTo be added\n\nAbilities\n\nExpert Combatant : Bushmaster was an expert hand-to-hand combatant, as he was able to easily fight off Luke Cage with little effort.\n\n: Bushmaster was an expert hand-to-hand combatant, as he was able to easily fight off Luke Cage with little effort. Skilled Leader: Bushmaster was a skilled leader, as he was able to rally his men together in order to escape Harlem's Paradise.\n\nEquipment\n\nWeapons\n\n"9-milimeter. Take the cap off, and you got a little pipe bomb right here." \u2015Bushmaster to Tilda Johnson [src]\n\n9mm Pistol: Bushmaster often used this gun when threatening people. Tilda Johnson]" time="0.623"><properties><property name="score" value="0.014393823699999999" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01439382 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01439382
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[It's been more than a decade since the last major update to Britain's copyright law, and it's high time that the UK brought its copyright law into the 21st century.\n\nYou've probably heard that the Government wants to bring in a new Digital Economy Act, which includes a measure to require all ISP customers to opt out of a default-on filter for adult content. Here's how you can tell them that you're not happy with this proposal, using just your email address.\n\nWho?\n\nIf you're concerned about online porn, you might have already signed a petition on the government's website calling for the default-on filter to be dropped. And in the wake of the controversy around the DEA, you might also have signed a petition demanding that ISPs should automatically block sites known to be involved in the distribution of online child abuse imagery. (Both of those petitions are still open for signatures if you want to join in).\n\nBut now it's time to tell the Government about some of the other things they're doing that are not as sensible, and we'll help you do it.\n\nWhat?\n\nFor a long time now, the UK Government has wanted to bring in a new Digital Economy Act. Last summer, the new law was finally published. The Act is massive, and there's lots to argue with, but it looks like the Government may be preparing to rush it through Parliament without any further debate. That means there's a limited window of opportunity to discuss changes to the draft before it becomes an Act of Parliament, and the Government starts work on enforcing it.\n\nThe draft DEA proposes a number of controversial new laws, including the opt-out default filter that's being discussed so widely. But the Act also proposes lots of other worrying measures, and gives the Government a lot more power to interfere with our online communications. The Act's supporters will tell you that it will help to tackle online infringement, for example. But its many critics argue that it risks stifling innovation in online services, and giving the Government a free hand to censor the internet in other ways.\n\nOn Monday, we told you that you could email your MP to demand a debate on the DEA. Now we've got even more reason to tell the Government that we're not happy with the draft DEA.\n\nThis week, the Pirate Party UK submitted a response to the Department of Business Innovation and Skills (BIS) on the Digital Economy Act, which responds to the Government's consultation on the proposals. We're not the only ones with concerns about the proposals; the Open Rights Group has submitted its own response (pdf) to the Government's consultation, and Index on Censorship has produced a response (pdf).\n\nHere's why we think the Government's proposals are a Bad Thing:\n\nThe proposals for an "Extended Liability for Platforms" could have serious unintended consequences for small internet service providers and independent content sharing websites, making them responsible for policing their services and preventing copyright infringement. We think this is likely to stifle innovation in new services, and also has serious implications for our online privacy.\n\nThe plans for an automatic filtering system to block content that is not classified by the state could lead to a drastic over-blocking of content. It could block more than just "extreme pornography" - it could block access to anything the Government decides is inappropriate. There's no requirement for these filters to be accurate or transparent, so we won't even be able to tell what's been blocked.\n\nUnder the proposals, the Government would also have the power to block websites that it claims are "blatantly" or "unlawfully" infringing copyright. This could be a serious threat to online innovation, and to our online privacy. And again, there's no requirement for these blocks to be accurate or transparent.\n\nThe DEA would make it much easier for the Government to put in place more blocking orders, and extend their scope. The wording of the legislation is vague enough that it could be used to order ISPs to censor content that isn't even illegal. The Government has already said that it wants to use its new powers to stop us from accessing websites that might be used to share copyrighted material.\n\nThe DEA is the biggest threat to our online privacy since the Data Retention and Investigatory Powers Act. If the Government gets its way, then they'll have the power to block websites and track what we're doing online. And they'll be able to do it without even telling us that it's happening.\n\nYou can read the Pirate Party's full response to the DEA consultation here (pdf).\n\nNow we need your help\n\nIf you're concerned about the DEA, you can join us in telling the Government what you think about the proposed Act.\n\nThe Open Rights Group's response (pdf) to the DEA consultation is still open for signatures. Once they've got enough names on the petition, they'll send their response to the Government.\n\nAnd now we've got our own response to the Government's consultation on the Digital Economy Act. Please support our campaign to stop the Act by signing our response here (pdf).\n\nWe'll be sending our response to the Government later this week, and we hope that it will give people the opportunity to stop the Act before it's too late.\n\nThis is the one chance we have to stop the DEA. But we need your help. Please support our campaign to stop the Act.]" time="0.579"><properties><property name="score" value="0.6227758" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6227758 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6227758
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[BevMo Beverage Superstore in California is a chain of beverage and snack retail stores. Its headquarters are located in San Carlos, California. As of May 2015, it has 41 stores in California and Nevada. All the stores offer beer, wine and liquors. They also carry various snacks, health and beauty products, household items and automotive supplies.\n\nStore Manager and Assistant Manager jobs in BevMo are offered in different parts of the state. The company also offers Benefits for its employees and Manager Trainee Program.\n\nGet more information about Manager Trainee Program at http://www.indeed.com/cmp/BevMo/jobs\n\nBevMo Beverage Superstore provides competitive pay, benefits, and other programs to help develop employees' potential and achieve their career goals.\n\nApply today!\n\nIt's fast and easy to apply online for jobs in BevMo Beverage Superstore, at http://www.indeed.com/apply?q=beverage+superstore\n\nFrequently Asked Questions\n\nCan I find the career page for BevMo Beverage Superstore on LinkedIn?\n\nNo, the company doesn't have a LinkedIn page. However, you can find more information about the company at its official website: http://www.beverage.com/About-BevMo/Careers\n\nCan I connect with BevMo on Twitter?\n\nNo, the company doesn't have a Twitter page. You can follow them on Facebook at https://www.facebook.com/Bevmo/\n\nWhat is the number for the customer service center?\n\nBevMo doesn't have a customer service center. However, you can contact the company at 1 (877) 822-6692.\n\nIf you have other questions, comments, or concerns, please leave them in the comments section below.\n\nBest Regards,\n\nIndeed.com]" time="0.277"><properties><property name="score" value="0.31028306" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Indigenization policy announced by Zimbabwe\u2019s new president, Emmerson Mnangagwa, in 2017, has raised a lot of questions about the process of nationalisation and the methods that will be used to allow for equal distribution of capital, land, and business interests. It\u2019s a policy that seems to favour the government at the expense of foreign interests and brings into question whether or not the government has a commitment to fighting corruption and seeking justice.\n\nThe new policy has been met with much scrutiny both in Zimbabwe and internationally. Many have expressed concern that the implementation of the policy will be flawed and that it will ultimately lead to a worsening of the economic situation in Zimbabwe. The Zimbabwean opposition party, Movement for Democratic Change (MDC), has expressed its disapproval of the policy, stating that it will further marginalise Zimbabweans who aren\u2019t involved in the government or who support the opposition.\n\nOn the international level, the Indigenisation policy is one of the latest changes to the Zimbabwean government that have raised concern. Since he took office in November 2017, President Mnangagwa has brought the central bank and the national oil company under government control. This has led to further speculation about the political and economic direction that the government intends to take.\n\nIs the policy legal?\n\nThe Indigenisation policy was initially announced in 2010 and later replaced by another policy called the Zimbabwe Agenda for Sustainable Socio-Economic Transformation (Zim-Asset). The Zim-Asset policy, which was issued in 2013, introduced a set of guidelines for the process of indigenisation. It requires that 51% of all Zimbabwean businesses be transferred to the country\u2019s black majority. However, the policy has never been enforced.\n\nThe decision to revive the policy in 2017 has been widely criticised. Human Rights Watch (HRW) issued a statement urging Mnangagwa to repeal the policy. HRW believes that the policy will only exacerbate the poor economic situation in Zimbabwe. The statement also notes that the government has never properly implemented the policy. It states that \u201cthe fact that no businesses have been indigenized in the past six years suggests that it is unworkable, and that it will not contribute to economic development or job creation.\u201d\n\nAs a member of the African Union, Zimbabwe is bound to uphold the African Charter on Human and People\u2019s Rights, which contains specific provisions regarding the protection of private property. These provisions state that the Charter guarantees the rights to private property ownership and the right to participate in the management of natural resources]" time="0.284"><properties><property name="score" value="0.003272304" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0032723 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0032723
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[CALCUTTA, March 9\u2014 The daughter of an Indian freedom fighter who died recently in a Calcutta hospital may never find out the cause of her father's death because the hospital has no autopsy facility and the family has no money to send his body to another hospital.\n\nA.B. Ray, a professor of economics at Calcutta University, died last Thursday in Calcutta Medical College Hospital after a long battle with pneumonia.\n\n''I am running from pillar to post to try and get a post mortem,'' said Mrs. Ray, whose husband is also a professor of economics at Calcutta University. ''My father was very much against autopsy and it was his express wish not to have it performed.'' Ray A.B. Ray, 82, was born on the campus of Presidency College, one of the oldest seats of higher education in India. He came from a wealthy and cultured family and had gone abroad to study economics in London.\n\nOn his return he became a prominent figure in Calcutta's intellectual and literary circles, editing newspapers and translating the ''Futurology'' series of lectures by the great French writer Andre Malraux.\n\nHe was an adviser to Indira Gandhi in the early days of her political career. He served in Parliament as a member of the Congress Party until his retirement from active politics in 1976.\n\nHe was admitted to Calcutta Medical College Hospital on Feb. 4, and received treatment in the hospital's intensive care unit. His condition gradually deteriorated and he died last Thursday.\n\nHis daughter, Dr. Suchitra Ray, said she was not at all satisfied with the treatment her father received in the hospital and thought that medical staff had not done their job properly.\n\nShe said that her father had been suffering from pneumonia for three years and that he had been given an injection a few days before he was admitted to the hospital.\n\n''My father was extremely allergic to penicillin,'' she said. ''Injecting him with penicillin at a time when he was in a very bad condition was in my opinion a highly irresponsible act.''\n\nThe doctor in charge of the intensive care unit, Dr. Abhijit Gupta, said that he could not discuss individual cases but that he had had no complaints about the treatment of Mr. Ray.\n\n''We did all we could,'' he said. ''It was very sad. His condition was very grave. It was a heart attack that killed him.'']" time="0.311"><properties><property name="score" value="0.8167449" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8167449 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8167449
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[RIGS Creator Platform Playstation 4\n\nPC Genre Shooter, Sports Release Date 29th October 2016 Price $59.99 (PSVR Only) $19.99\n\nRIGS is an action sports game exclusively for PSVR. It was developed by Guerrilla Cambridge (and published by Sony) and released on October 29th, 2016. It takes place in a futuristic sci-fi setting, where you play as one of a number of different characters. Each character uses a different kind of battle suit, allowing them to take part in 3 different sports. Those sports are essentially the 3 main games. They are called RIGS, Megaton, and Gravity Wars. These games play as though they\u2019re real sports. They play more or less how you\u2019d expect them to. You score points by hitting goals, and your objective is to take the ball, and score it in the goal.\n\nThe first game is RIGS, which is essentially a shooting game. There are multiple game modes. Each mode is the same, except you\u2019re playing different characters, and there\u2019s a different goal for you to hit. RIGS is the most fun game in the package, simply because it\u2019s a FPS, which is something you don\u2019t get a lot of in VR games.\n\nMegaton is a sort of bumper-car football game. It\u2019s the second most fun game in the package, just because it\u2019s an interesting spin on something we all know. It is also a lot easier to master than RIGS.\n\nGravity Wars is a very interesting concept, and very hard to master. The game has no physics, and you have to control your direction by using the stick on the right. It\u2019s very challenging, and once you get the hang of it, it can be fun.\n\nRIGS: Mechanized Combat League is a game that is good fun for those who have VR. There\u2019s nothing else like it. It has an interesting concept, and it makes for an interesting single player experience. The multiplayer is there if you want it, but if you don\u2019t, you can use bots, and they will be enough to let you master the game. It does have a lot of potential, and if Guerrilla Cambridge do a sequel, it will most likely be worth it.\n\nPros:\n\nGreat for VR\n\nVariety\n\nWell made\n\nGood concept\n\nCons:]" time="0.353"><properties><property name="score" value="0.015095497" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0150955 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0150955
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Phantom ~ Opus 4 ~ Raw\n\n~ Chapter One ~\n\nTitle: Phantom ~ Opus 4 ~ Raw\n\nAuthor: Starfyre\n\nBeta: freddie-m\n\nPairing: Eventual MeixLu\n\nSummary: After 2 years of therapy, Liu is released back into the world and he returns to the only place he calls home. Only a few things have changed. He finds himself adjusting to the changes with more difficulty than he ever expected.\n\nGenre: Angst, Romance, Tragedy, Drama, Supernatural\n\nWarnings: none\n\nWord Count: 15,611\n\nAuthor Notes:\n\nA while ago I read a story called "Bloodlust" by Inu'sLurker. It's a beautifully written story and I recommend you all check it out. I loved it so much I was inspired to write my own story of 2 boys on a trip to Shanghai. Since I am in no way the author that Inu'sLurker is, I apologize for my lack of originality. But I thought that perhaps if I wrote about something that happened to me I would find it easier to write a story like this.\n\nAnd what happened to me was that one year, the day before my birthday, my mother and I went to China. Now that I look back on it, it was a very exciting trip, though at the time I was rather sad because I was turning twelve. I had been dreading the day, and it was nice to be with my mom because she always made me feel better.\n\nIt was also an interesting trip because we were staying with my Grandfather for a few weeks. He lived in Shanghai, and he was the one that took us to China in the first place. So it was an adventure for me to be in a place that he lived. I only saw my Grandfather on holidays, and it was a great experience.\n\nI hope you all enjoy this story as much as I enjoyed writing it.\n\n- - - - -\n\nIt was just before eleven in the morning when we arrived at my grandfather's house. We had been traveling for quite some time and I was very excited to see him. He came out of the house to greet us]" time="0.281"><properties><property name="score" value="0.46607116" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rideshare companies like Uber and Lyft are under increased scrutiny after a self-driving Uber killed a pedestrian last week.\n\nThey\u2019re called autonomous, but are they ready? It turns out not even close.\n\nYou might be surprised to learn that self-driving technology is more or less as old as the automobile itself. In fact, there are a number of cars on the road today with self-driving features, but they are only meant to assist the driver and not take over completely.\n\nOne such system, called Autopilot, was first launched by Tesla in October 2015. The main feature allows the car to drive itself on a highway, but it\u2019s still supposed to be monitored by the driver.\n\nUnfortunately, Tesla and Elon Musk have become a lightning rod for scrutiny after an accident last week that killed a Model X driver using Autopilot. A series of emails have revealed that Tesla has attempted to make it clear that Autopilot is not a \u201cself-driving\u201d feature.\n\nIn a recent letter to shareholders, Musk wrote, \u201cWhen used correctly, it is already significantly safer than a person driving by themselves and it would therefore be morally reprehensible to delay release simply for fear of bad press or some mercantile calculation of legal liability.\u201d\n\nWhat exactly does this mean? For one, this was an admission that the technology was not yet ready for public consumption.\n\nTesla is also being called to answer to whether or not the driver should have known that he was using the Autopilot feature. The company says the driver would have known since he was sitting in the driver\u2019s seat and the car\u2019s steering wheel was not in a locked position.\n\nA photo taken by a witness has been released, showing the driver looking down at something with his hands not on the wheel.\n\nThe automaker has since issued a recall to fix the issue and said it will be updating the Autopilot system to ensure that drivers stay engaged with the vehicle\u2019s operation.\n\nUber said it will be disabling the self-driving feature in its fleet of Volvo XC90s after one of its vehicles ran a red light in San Francisco last week, killing the woman. The car was in self-driving mode and the Uber employee behind the wheel wasn\u2019t able to take control of the vehicle in time.\n\nTesla and Uber are not alone in pursuing self-driving cars. Most automakers have some form of autonomous vehicle in the works, as well as companies like Google and Apple. Tesla is still the only automaker with a Level 5 vehicle that has no steering wheel or pedals, however.\n\nAccording to the National Highway Traffic Safety Administration, Google\u2019s self-driving cars have only been involved in 11 accidents over the course of 1.5 million miles of driving, but most were caused by human error.\n\nGoogle has said that the biggest hurdle for self-driving cars will be the creation of a trust between car owners and their vehicle. To that end, the company has been testing a number of prototypes over the last several years, which they claim have driven millions of miles without causing any accidents.\n\nVolvo has been developing its own version of an autonomous vehicle for some time now, but the company is not going at it alone. They\u2019ve partnered with Uber, which bought some XC90 vehicles from Volvo, to run a fleet of self-driving Volvos for ride-hailing in Pittsburgh, where Uber\u2019s research center is located.\n\nWith the recent incidents involving Tesla and Uber, the questions of what\u2019s right and what\u2019s safe have only been heightened. Tesla is going to fix the problem with its Autopilot system and Uber is pausing its own self-driving testing, but it\u2019s clear that these vehicles are a long way from being ready for mass adoption.\n\nWill the driverless cars revolution ever happen? The answer seems to be a resounding yes, but it won\u2019t be anytime soon.]" time="0.319"><properties><property name="score" value="0.0008673367" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00086734 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00086734
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The actual intent of the changes in the UK\u2019s regulation and taxation of ISAs and pensions has become muddled in translation.\n\nThe UK\u2019s changes in pension taxation may well reduce your contributions.\n\nThe investment management industry\u2019s drive to promote personal pension products as an alternative to ISAs may have got a little over excited.\n\nFirstly, the changes that the UK government has made to the regulation of pensions and ISAs has not in fact reduced the level of tax relief on ISAs. It has however changed the way in which tax relief on contributions to personal pensions is calculated.\n\nThe current situation, whereby the actual value of the tax relief received on the sum of a pension contribution, as opposed to the rate of relief, is included in the calculation of income tax, has led to some confusion.\n\nThere is a belief that the relief that is received on the sum of a pension contribution is reduced to 10 per cent and therefore is not as good as the relief received on ISAs, where the actual value of the relief is not included in the calculation of income tax.\n\nThis misunderstanding may well have led to some people contributing to ISAs rather than pensions in order to maximise tax relief.\n\nIn addition, if the actual value of the tax relief received on the sum of a pension contribution is used as a deduction from the gross amount of the pension contribution then the level of relief has not changed at all. The actual value of the relief received on the sum of a pension contribution in the income tax calculation has increased in line with the amount of gross income that is subject to tax relief.\n\nFor example, a gross contribution of \xa310,000 would result in an actual tax relief of \xa37,500 under the current arrangements (the gross contribution is grossed up by 50 per cent to give the net pension contribution of \xa37,500).\n\nUnder the new arrangements, the gross contribution would remain at \xa310,000, but the actual tax relief received on the sum of a pension contribution would be \xa37,000. The relief on the actual value of the pension contribution is not reduced to 10 per cent.\n\nThe amount of gross income that is subject to tax relief is now \xa340,000. If you earned this amount in income before your pension contributions, then the actual tax relief on the sum of the pension contribution would be \xa330,000, rather than \xa37,500.\n\nWhat has changed is the way in which the actual tax relief received on the sum of a pension contribution is calculated. The net pension contribution (the amount actually deducted from the gross income) will no longer be grossed up to produce the actual tax relief received on the sum of the pension contribution.\n\nTherefore, the actual tax relief received on the sum of a pension contribution will always be lower than the actual tax relief received on the actual value of a pension contribution.\n\nIt is important to note that it is not the rate of relief that is affected. It is the actual value of the relief that is reduced. The rate of relief is not affected.\n\nPension contributions are still exempt from tax, although the amount of income that is excluded from tax is less than it would have been if the relief was given on the actual value of the pension contribution.\n\nSecondly, the changes to the regulation of pensions and ISAs have not increased the level of tax relief on pensions. The actual level of tax relief on pensions has not changed. The maximum level of tax relief is still 40 per cent.\n\nThe regulation of pensions has changed. Under the new rules, the maximum amount that can be paid into a pension pot, subject to tax relief, is \xa31.8 million. The maximum amount that can be paid into an ISA, subject to tax relief, is \xa37,000.\n\nBoth the maximum contribution level of pensions and ISAs has increased, but the maximum tax relief that can be obtained on both types of products is the same.\n\nIf you have already opened a pension plan, then you can only increase the contribution amount by \xa32,880 per year. Any extra contribution beyond the annual limit will not be eligible for tax relief. The full value of the contribution, regardless of how much it is, will have to be paid from your gross income.\n\nThe actual level of tax relief on ISAs has not changed. The maximum amount of ISA contributions that can be paid into an ISA in any tax year is \xa37,000. This has not changed. Any amount that is paid into an ISA in excess of this amount will not be eligible for tax relief. The full value of the contribution, regardless of how much it is, will have to be paid from your gross income.\n\nSo in summary, the actual level of tax relief on ISAs has not changed. The maximum amount that can be paid into an ISA, subject to tax relief, is \xa37,000.\n\nThe actual]" time="0.350"><properties><property name="score" value="0.2880686" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.2880686 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.2880686
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[During the first year of life, children change more than they ever have before. At this stage, parents play an important role in influencing their child\u2019s development.\n\nPregnant mothers are able to greatly influence the infant\u2019s life in many ways. During pregnancy, a woman is able to optimize her diet and avoid environmental pollutants. Even while pregnant, it is important for her to stay healthy and happy, as this will in turn make the baby happier. All of this is important in a child\u2019s development.\n\nBelow are five milestones in a baby\u2019s development.\n\nMovement\n\nYour child has been feeling his own kicks and punches for a while now. He may have even kicked his mom and caused her some pain. The child will also be moving his arms and legs in a jerky fashion. As the baby grows, his movements will become more fluid.\n\nChild\u2019s Hand and Finger Development\n\nBabies are able to grab things because their hands are strong. They are also able to curl their fingers into a fist. During this time, the baby may be grasping onto a lot of things that are near.\n\nThe baby may also have strong movements, such as pinching your fingers. Babies begin to explore their world through their hands. They are also able to control their hands and fingers with ease.\n\nSitting\n\nA baby can begin to sit up on his own. This is because he has grown to a point where he is able to do this. The baby may also be able to hold his head up by himself.\n\nBabbling\n\nThe baby may also begin to make sounds that can be referred to as babble. Babies are able to make a lot of sounds and combine them together. This is a part of speech development.\n\nFeeding\n\nYour child may be starting to eat solid food. This may include mashed vegetables, cereal, and baby food. If your baby is too young to eat this type of food, it may not be a good idea to force it. This can cause choking or other complications.\n\nSource: BabyCenter]" time="0.281"><properties><property name="score" value="0.051144026" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05114403 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05114403
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[" Very nice high quality item, exactly what I expected, and quick delivery. " Very nice high quality item, exactly what I expected, and quick delivery.\n\n~Brian S., Australia\n\n" It arrived. It fits great and looks great. Thanks! " It arrived. It fits great and looks great. Thanks!\n\n~Paul L., San Luis Obispo, CA\n\n" The case arrived today as promised; it fits great! I\u2019m very impressed with the quality of materials and workmanship. I plan on ordering more from you in the future, as I have one other custom amp, and will probably get more vintage ones as time goes by. Thanks again for your assistance and awesome product! " The case arrived today as promised; it fits great! I\u2019m very impressed with the quality of materials and workmanship. I plan on ordering more from you in the future, as I have one other custom amp, and will probably get more vintage ones as time goes by. Thanks again for your assistance and awesome product!\n\n~Mark S., Harford, WI\n\n" I received the covers today....very nice job, they look great! I haven't tried them on the amp yet but I will be for a gig Sat. Thanks for everything! PS, I bought a Pma Board a few months back and ordered one of your covers with it.....nice fit! " I received the covers today....very nice job, they look great! I haven't tried them on the amp yet but I will be for a gig Sat. Thanks for everything! PS, I bought a Pma Board a few months back and ordered one of your covers with it.....nice fit!\n\n~Joe K., Williamson NY\n\n" The slip arrived today and fits perfectly, you hit the nail right on the head. Thank you for your professionalism and look forward to buying one for my 4x12 flextone cab!! " The slip arrived today and fits perfectly, you hit the nail right on the head. Thank you for your professionalism and look forward to buying one for my 4x12 flextone cab!!\n\n~Derek P\n\n" I got the new cases for my pedal steel and they are awesome, they fit perfectly. " I got the new cases for my pedal steel and they are awesome, they fit perfectly.\n\n~Earl F., Houston, TX\n\n" My padded cover arrived today for my Morgan PR12. The quality is superb, and the fit is perfect. It is refreshing to get a product delivered that exceeded my expectations. " My padded cover arrived today for my Morgan PR12. The quality is superb, and the fit is perfect. It is refreshing to get a product delivered that exceeded my expectations.\n\n~Larry G., Saskatoon, Canada\n\n" Hey just wanted to say i got the covers last week and they are awesome!!! i will definitely purchase more in the future.my amp and cabinets are bandmate protected " Hey just wanted to say i got the covers last week and they are awesome!!! i will definitely purchase more in the future.my amp and cabinets are bandmate protected\n\n~Pete G., Nova Scotia CANADA\n\n" The covers arrived yesterday and they are wonderful. The Two Rock & the Princeton covers fit like a glove. Thanks for your patience in getting the measurements right and the quick turnaround on my order! Appreciate it very much! " The covers arrived yesterday and they are wonderful. The Two Rock & the Princeton covers fit like a glove. Thanks for your patience in getting the measurements right and the quick turnaround on my order! Appreciate it very much!\n\n~Mark W\n\n" I just wanted to say a great big THANK YOU for my recent order. I thoroughly am impressed with my new studio slips. " I just wanted to say a great big THANK YOU for my recent order. I thoroughly am impressed with my new studio slips.\n\n~Tim S., Nashville, TN\n\n" The cover fits perfectly and looks great too! " The cover fits perfectly and looks great too!\n\n~Keith R., San Diego CA\n\n" I received the amp cover, you do fabulous work, thank you! " I received the amp cover, you do fabulous work, thank you!\n\n~Michael S., West Chester PA\n\n" I received the amp cover today. Perfect fit and fantastic materials and quality work as always! Thank you for your work! " I received the amp cover today. Perfect fit and fantastic materials and quality work as always! Thank you for your work!\n\n~Mel B., Taunton, MA\n\n" I received my order in perfect condition, the cover fits and looks great ! It was a pleasure doing business with your company. " I received my order in perfect condition, the cover fits and looks great ! It was a pleasure doing business with your company.\n\n~Jerry W., New Berlin WI\n\n" Received the studio slips cover today, perfect fit! Thanks Again for a great product! Great doing business with you again..... " Received the studio slips cover today, perfect fit! Thanks Again for a great product! Great doing business with you again.....\n\n~Joe V., Lindenhurst, NY\n\n" I just wanted to let you know I am thrilled with the new cover. It arrived today and fits perfect. Good job and well done!! " I just wanted to let you know I am thrilled with the new cover. It arrived today and fits perfect. Good job and well done!!\n\n~Kenny M.,]" time="0.351"><properties><property name="score" value="0.03804566" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[For many years, and at many different homes, the grand game of monopoly was a nightly staple of our game playing regimen. Most of the time the game was played with one of my kids as the banker. The game required a bit of accounting to keep track of all the money. More often than not the game was a heated one and everyone, particularly the banker, enjoyed counting out money while money was being piled up all around the board.\n\nMonopoly is an interesting game for a number of reasons.\n\nFirst, it requires the basic accounting function of making change. The cashier has to be able to count out the correct change for all the players. This seems like a very simple, but important function. If a cashier can\u2019t count change, you would have to return the money, and you might not get it back.\n\nAlso, with any money that comes into the game there are some decisions that have to be made. For example, with a loan, how much should be charged to each player. More importantly, how much can the players afford to pay back?\n\nIn addition, how much does the bank loan to the players and what are the terms? What does the bank require to be repaid? At what time? What happens if there is not enough money to pay back the bank?\n\nThis seems like an easy concept, but a lot of my kids had a difficult time trying to figure out what they had to do to get out of debt.\n\nFinally, there are times when players simply get too deep into debt. They are forced to sell off a building, or even the entire game.\n\nThis seems like a pretty simple concept, but I found it interesting because it taught some of my kids a very valuable lesson about life. They realized how important it is to have a budget. More importantly, they realized how much money they had to spend. They had to spend wisely because they couldn\u2019t go into debt.\n\nI think it\u2019s easy to teach kids to balance their checkbook and keep track of their spending, but it\u2019s much more difficult to teach them to spend wisely and stay out of debt.\n\nThe same goes for a family\u2019s bank account. Families, just like the player\u2019s in monopoly, need to keep track of the money coming into the bank account and what is going out. They need to make sure there is enough money to cover the things they need to pay for and that there is enough money to cover the things they want to spend money on. They need to be responsible with their money and realize they can\u2019t go into debt.\n\nThe game of Monopoly teaches a lot of these principles. It is not a game of instant gratification. There are no easy money schemes. It\u2019s a game that will test the mind and the ability to be responsible with money.\n\nIf you have kids, Monopoly is a great way to learn about personal finance. You don\u2019t need to be an expert, but you do need to be willing to show them how to count and account for money.]" time="0.289"><properties><property name="score" value="1.5322425" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.5322425 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.5322425
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Bengals fell just short of a win in Kansas City Sunday, falling to the Chiefs 31-13. The loss drops the Bengals to 7-9, a number that still includes a loss to the Jacksonville Jaguars in London.\n\nOne of the biggest stories to come out of this loss is the fact that star running back Jeremy Hill was benched in favor of Rex Burkhead. Hill didn't have a good game, and the Chiefs were able to put him in his place. Burkhead was also pretty good, and scored the only Bengals touchdown on the day.\n\nBoth running backs ran for over 100 yards, but the key difference was Hill fumbled twice, including once inside the Chiefs' 20. Hill had carried the ball 39 times before the benching, while Burkhead had just nine.\n\nIt was announced Monday that Hill is still the Bengals' starting running back going forward.\n\n#Bengals Jeremy Hill named starting running back in 2018, Mixon to see more action. https://t.co/jZ9624gBwO pic.twitter.com/jOKGewN4zq \u2014 Kevin Clark (@bykevinclark) January 1, 2018\n\nThis is an interesting decision, considering the way the Bengals used the two running backs in Kansas City. Hill has been a solid running back throughout his career, but has shown lapses in concentration, as well as fumbling issues. He's not been consistent, and that has made the Bengals hesitant to hand him the starting job.\n\nThe Bengals will likely be looking to get more out of their running backs next season. We saw how talented Joe Mixon is this year, and he's the one who should have the starting job next season.\n\nHill will still be involved in the offense, but this change is a sign that he won't be a starter for the Bengals next season.]" time="0.308"><properties><property name="score" value="0.39333582" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Transcript\n\n1 ADNOTAMENTO A FOGLIO NUMERO INDAGINI C.P.C.O. PROFESSIONE DISPONIBILE ORDINE CLINICO ED ORTOPEDICO 1. MEDICO ORTOPEDISTA 1 MEDICO ORTOPEDISTA ORTOTTISTA 1 MEDICO ORTOPEDISTA ORTOPEDISTA 3 MEDICO ORTOPEDISTA PSICOLOGO 1 MEDICO ORTOPEDISTA RIABILITATORE VISO 1 MEDICO ORTOPEDISTA ODONTOIATRA 1 MEDICO ORTOPEDISTA NEUROPSICOLOGO 1 MEDICO ORTOPEDISTA ASSISTENTE SOCIALE 1 MEDICO ORTOPEDISTA PSICHIATRA 1 MEDICO ORTOPEDISTA 1.1 FISIOTERAPISTA 1.1 FISIOTERAPISTA INFERMIERE 1.1 FISIOTERAPISTA OPERATORE SANITARIO 1.1 FISIOTERAPISTA DIETISTA 1.1 FISIOTERAPISTA ASSISTENTE SOCIALE 1.1 FISIOTERAPISTA COACH 1.1 FISIOTERAPISTA ELETTROMIOGRAFO 1.1 FISIOTERAPISTA DENTISTA ORTOPEDICO 1.1 FISIOTERAPISTA INFERMIERE CLINICO 1.1 FISIOTERAPISTA OSS 1.1 FISIOTERAPISTA TERAPISTA DELL AUTOMOBILE 1.1 FISIOTERAPISTA TECNOLOGO DEI MATERIALI 1.1 FISIOTERAPISTA 1.2 ORTOTTISTA 1.2 ORTOTTISTA ASSISTENTE SOCIALE 1.2 ORTOTTISTA ODONTOIATRA 1.2 ORTOTTISTA 1.3 OSTETRICA E GINECOLOGO 1.3 OSTETRICA E GINECOLOGO ASSISTENTE SOCIALE 1.3 OSTETRICA E GINECOLOGO ODONTOIATRA 1.3 OSTETRICA E GINECOLOGO 1.4 PROSTETICO IGIENE ORALE 1.4 PROSTETICO IGIENE ORALE ODONTOIATRA 1.4 PROSTETICO IGIENE ORALE 1.5 RADIOLOGO 1.5 RADIOLOGO ODONTOIATRA 1.5 RADIOLOGO 1.6 REUMATOLOGO 1.6 REUMATOLOGO MEDICO DELLA PREVENZIONE 1.6 REUMATOLOGO 1.7 OSTEOPATA 1.7 OSTEOPATA ASSISTENTE SOCIALE 1.7 OSTEOPATA ODONTOIATRA 1.7 OSTEOPATA\n\n2 1.8 PSICOLOGO 1.8 PSICOLOGO MEDICO DELLA PREVENZIONE 1.8 PSIC]" time="0.312"><properties><property name="score" value="0.0020725308" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Will the traditional establishment defend democracy?\n\nBy Alexandra Morton\n\nUBC-O Sea Around Us Project\n\nI am scared to my bones. For the first time in my life I am terrified that what I learned as a child is wrong. There is no more mother or father to turn to. There is no more food to count on. This is my last chance to sound the alarm that we are being systematically robbed and cheated and lied to and I don\u2019t know what we are going to do about it.\n\nA few years ago I could not have imagined that I would find myself writing this. I was born and raised in the village of Old Massett on Haida Gwaii, also known as the Queen Charlotte Islands, in Canada. We fish and hunt and gather food and make our own shelter and build our own community. This is how it has been for thousands of years. In modern language this is called subsistence living. We were the last people in Canada to sign treaties with our colonial oppressors in the 1800s. These documents were the foundation of our way of life.\n\nThen it all changed in the early 2000s when the first commercial aquaculture license was issued on our coasts. At first, like most people on Haida Gwaii, I thought that farming fish would provide income for our community. Little did I know that the promise of wealth would come with a heavy price.\n\nThe first evidence I saw that something was wrong was in 2006. The sea lice were everywhere and a fish farm had started using a pesticide called Slice. I saw the sea lice on the fish and sea lions. I saw sea lions coughing up blood, the bones on their backs visible through their skin.\n\nIn 2007, the open net pen at salmon farm salmon feedlots one kilometre off the coast of my village collapsed. An estimated two to three million Atlantic salmon, with a value of $6.5 million to $8 million, swam into the ocean. There was no monitoring, no analysis of the risk to wild salmon, not a word to local communities.\n\nAnd then the toxins appeared. In 2008 and 2009 people in my village became sick and died. In the village of Klemtu next door, children were born with flipper-like hands and feet. In Norway, which had a higher concentration of fish farms, brain tumours and other cancers were rising and women were giving birth to deformed babies.\n\nI looked at these stories and thought, \u201cThis can\u2019t happen to us.\u201d\n\nThis was followed by the closure of the Haida Nation\u2019s only grocery store. People in my village and community started suffering from serious health problems, especially neurological ones. We were told it was due to influenza or SARS. We had no idea that a toxin, which our bodies have not evolved to handle, was being released into the air and our water. The Sea Around Us reported that fish farms were creating the most toxic area in the world, right next to the First Nations in Haida Gwaii. This happened, and no one told us.\n\nI realized I had to do something. For the first time in my life I realized that what my ancestors had always taught me was wrong. It was not nature that took care of us. It was we who were responsible for taking care of nature.\n\nI wrote my first letter to the local newspaper. It was my story, and I was afraid to publish it.\n\n\u201cHow many people have to get sick and die before they take this seriously?\u201d I asked.\n\nWe waited and waited, and nothing happened. I wrote my second letter. Nothing.\n\nWe waited and waited. Still nothing.\n\nPeople in my village got sick and died, and the Norwegian scientists kept warning that their food supply was being contaminated. We were told that this was the price of progress, that it was our job to clean up the mess. And we had to do it on our own.\n\nAnd then the baby seals came. There are no young sea lions, so the seals started eating the herring. At first we thought it was cute. Then we realized they were killing the herring. There were too many seals.\n\nI wrote my third letter. I looked at the numbers and saw that Norway was killing 80,000 seals a year and there were only 80,000 seals left.\n\nI started to organize rallies and a campaign called Save the Herring, which caught the attention of major news outlets across the globe. By this time I had a voice. I was a professor of biology at UBC and one of the world\u2019s experts on fish farming, open net pen fish farms, and marine pollution. I knew the science.\n\n\u201cHow many baby seals have to get cancer before they take this seriously?\u201d I asked.\n\nIn the midst of this, Canada approved a massive new open net pen farm. This was the largest salmon farm in the world. Our local paper warned us that \u201cthe massive farm will increase marine pollution in the area.\u201d This farm started dumping blood and feces into our waters. The evidence was mounting that we were at risk of a catastrophic collapse in our food web.\n\nBut no one cared. The aquaculture industry is worth $400 million a year. We can\u2019t compete with that.\n\nA new form of ocean zoning called an impact assessment was supposed to keep salmon farms out of sensitive areas, but it was all a lie. The people who wrote it are in the industry. They gave themselves exemptions.\n\nThen I realized that I could make a living as a scientist. So I created a lab at the University of Victoria to study the toxins from fish farms. We started to find the pollutants in the mussels and the herring. I published more and more scientific papers.\n\nWe held more rallies, and I wrote more and more letters to the local paper. We were ignored and dismissed.\n\nSo we went to the Supreme Court. Our case was thrown out, but the judge was extremely critical of the Canadian government and gave them 18 months to fix their laws. But the government is now granting the aquaculture industry a blanket exemption from environmental laws and protections. The judge told them that they could not do this. But they did.\n\nI have studied toxicology for 30 years and I have never seen this. We know that these toxins are not getting into our environment accidentally. The only reason they are there is because someone put them there. It is like they are trying to poison us.\n\nAnd then we started to see a new toxin. This time it was a by-product of the feed used in the salmon pens.\n\nA Norwegian scientist tested a by-product of salmon feed. The test showed that it was toxic. The Norwegian government stopped using the feed. In 2015, that same scientist tested all the salmon feed used in the British Columbia industry. The results showed that there was another new toxin, this time a carcinogen. The Norwegian scientist said, \u201cIt is extremely unlikely that it could happen at such high levels by chance.\u201d\n\n\u201cHow many toxins have to get into our food before we take this seriously?\u201d I asked.\n\nThis time I knew that there was something wrong with my brain. We found out that Norway and Scotland were using the same feed. We had a toxic lab here in British Columbia, so what about Norway and Scotland? And the feed is approved by the Canadian Food Inspection Agency and used in these salmon farms.\n\nIt\u2019s hard to see who we are going to turn to.\n\nThen a woman in Ketch Harbour started asking questions. She wrote to the local paper and was ridiculed and insulted. She wrote to the Minister of Fisheries and Oceans. He never replied.\n\nShe was not from my village. She was a white woman from Newfoundland. Her grandfather was a fisherman.\n\nI wrote to her, and then I realized I could write to everyone. And I did. I started to get hundreds of people to write letters, and we wrote to the Minister of Fisheries and Oceans and to our Premier, the head of our government. We wrote to every MLA, the Members of the Legislative Assembly, and we were ignored and dismissed.\n\nSo we went to court again. This time we were supported by 30 affidavits from fishermen and local citizens.\n\nI went to the hearings. The minister did not even show up. His lawyer said that we should stop questioning him and just accept that he is doing the right thing. He had no explanation as to why the 30 affidavits were not enough evidence to put a stop to this industrial salmon farming.\n\n\u201cIf I had a million dollars, I could save Haida Gwaii,\u201d I said.\n\nBut I have never been able to raise that money. The man who tried to stop me is now running for Premier, and he is the frontrunner.\n\nSo I wrote my fifth letter to the editor. I warned that if we continued to use this feed, we would all get sick and die.\n\nAnd then I realized that I could put this on Facebook.\n\nA few months ago, the BC government ordered the feed company to remove this toxin from their products. But they still sell it in other provinces. There is still no ban on the feed, even though Norway has banned it, the FDA has banned it, and Health Canada has banned it.\n\nAnd then I realized I could just get on a bus and go to Toronto and speak to people directly.\n\nSo that is what I am doing. I am going to make this my life\u2019s work. I am going to stand in front of people, in universities, in public hearings, and tell them my story. I am going to explain that it is not]" time="0.628"><properties><property name="score" value="0.0049233106666666665" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00492331 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00492331
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Anselm and his ontological proof, is one of the most important Christian philosophers of the Middle Ages. He is also well known for his attempts to fuse the sciences with theology, something of a controversial topic for medieval theologians. The ontological argument itself is based upon the idea that God\u2019s nature is that of existence. Therefore, to say that God exists is to say that God has the greatest nature, which in turn leads to the conclusion that God must exist. Some scholars argue that this is the proof\u2019s most fundamental flaw, namely that God\u2019s nature is unprovable and thus, cannot be equated to the definition of existence. Other critics point out that the greatest nature is really a metaphysic and therefore cannot be understood by people. The latter claim has been supported by Immanuel Kant and many other philosophers since. Kant\u2019s work was not known to Anselm\u2019s, but it is clear that the German philosopher would not have found much use in Anselm\u2019s philosophy.\n\nThe foundation of Anselm\u2019s ontological argument is a branch of philosophy known as natural theology. Natural theology is the search for a knowledge of God through the use of reason. The argument\u2019s goal is to prove that God exists in some way, and as such is a concept that is widely accepted in the world of Christian philosophy. In many ways, Anselm\u2019s argument for God\u2019s existence shares many similarities with the arguments of many of his contemporaries. Anselm claims that God exists and that this conclusion can be proven using the method of defining terms. The proof proceeds from the claim that God is the greatest thing conceivable to the claim that God must also exist. Anselm\u2019s argument does not satisfy many people because it does not provide any evidence to support the claim that God is in fact the greatest conceivable thing. This is one of the major weaknesses of Anselm\u2019s argument, but it is also one of the weaknesses of most arguments for the existence of God. The ontological argument can be seen as an attempt to prove God\u2019s existence without supporting any specific philosophical view of God\u2019s nature.\n\nMuch of Anselm\u2019s work focuses on the attempts to explain and prove God\u2019s existence. He was one of the earliest of many philosophers to attempt to explain and prove God\u2019s existence. The debate over the existence of God has continued over the years, and the arguments have been supported and refuted on many different occasions. Anselm\u2019s work is important because he was one of the first philosophers to put forth the idea that existence itself was proof of God. He was also one of the first Christian philosophers to try and explain the idea of God in a non-theological way. Many of Anselm\u2019s contemporaries had rejected his view on God\u2019s nature, and they also criticized his work on natural theology.\n\nOne of the major debates over Anselm\u2019s work was that of the ontological argument. This is a popular concept that states that God\u2019s existence is a self-evident truth. The name of the argument comes from the phrase \u201csomething that is greater than which cannot be conceived\u201d. This concept became widely accepted in the world of Christian philosophy, and it is still being debated today. The concept of God\u2019s existence as a self-evident truth has been supported by many Christian philosophers, including Thomas Aquinas. Aquinas\u2019 view of God was one of the most influential views of God\u2019s nature in the Middle Ages. The ideas presented by Anselm and Aquinas on God\u2019s nature were among the first attempts to view God in a logical way.\n\nMost of Anselm\u2019s work focused on the idea of God and the way in which God was perceived. He focused on the idea that God was perceived through faith and that this idea had a real and substantial foundation. Many critics viewed Anselm as a philosophical follower of Augustine, and he was certainly influenced by many of Augustine\u2019s works. The Confessions of Augustine were written in the fifth century, and they discussed the views of the time on God and the manner in which people should understand God. Anselm\u2019s view of God is therefore quite different from many of his contemporaries, and he was heavily criticized for his work on natural theology.\n\nThe ideas presented by Anselm were extremely influential to his contemporaries. Although his ideas were at times criticized, many of his contemporaries found them to be the most logical views of God. His argument for God\u2019s existence was extremely popular among his peers, but it is one of his most controversial works.\n\nAnselm of Canterbury Biography\n\nAnselm of Canterbury was born in 1033 in Aosta. He was the second of four sons and his parents were wealthy. Anselm\u2019s father was an Italian who owned a noble estate. His mother was the niece of the archbishop of Rheims. Anselm was well educated, and he studied both rhetoric and literature as a young man. He studied law in 1057 at the cathedral school in Laon. During this time, he became close friends with Roscelin of Compi\xe8gne. Roscelin was an expert on logic, and he would be one of Anselm\u2019s best friends and mentors for the rest of his life. He was also close to Lanfranc and eventually became his student.\n\nAnselm studied theology in the early 1060s at the cathedral school of Chartres. He also spent a great deal of time studying theology and grammar at the school of Benevento. Anselm spent two years at the school and was then called to the cathedral school of Canterbury in 1062. Anselm was called to the cathedral school to replace the archbishop. The archbishop of Canterbury was the highest ranking prelate in England and he was charged with the administration of the Church in England. Anselm quickly gained respect in his new position, and he wrote a new rule for the cathedral school. The rule was based on the Rule of St. Benedict, which was the most important rule for monasteries at the time. He was also responsible for the cathedral school\u2019s many other duties and its administration. He established the system of electing canons and was also in charge of its finances. Anselm had a great deal of power in his new position, but he also was a reformer. He placed emphasis on the importance of education and scholarship, and he ensured that the students received high quality instruction. The rule at the cathedral school was seen as being high quality and the students at the school were trained in Greek, Latin, rhetoric, dialectic, and arithmetic.\n\nAnselm also established a library at the school. The library contained many ancient works, which were frequently read by students. He became an expert on the writings of Augustine, and he began his own writing career in the early 1060s. His writings were influential in the development of later philosophy, and his ideas on natural theology were both influential and controversial. In 1063, Anselm was appointed archbishop of Canterbury. This was an extremely important position, and Anselm would play a major role in the Christianization of England. He was a major contributor to the revival of learning in England, and he attempted to bring education to all of his subjects.\n\nHe was a skilled theologian, and he produced several important theological works. These included the Monologion and the Proslogion. The Monologion addressed the questions of the nature of God. The Proslogion addressed the questions of the nature of God\u2019s knowledge and the proof for God\u2019s existence. Anselm was influenced by Augustine in his writing of the Monologion]" time="0.580"><properties><property name="score" value="0.22423856749999999" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In California, a convicted pedophile is on the loose. The worst part? He's a convicted pedophile.\n\nFrancisco Felix-Jimenez was released from prison last week. He was convicted of molesting an 8-year-old boy in 2006.\n\nWell, it turns out that the Los Angeles County Sheriff's Department forgot to register Felix-Jimenez as a sex offender.\n\nYou may be asking yourself, "How does that happen?"\n\nThey may have simply forgot. It happens all the time, although it's usually because a sheriff's department employee who should have registered the convicted sex offender doesn't think the guy will do it again.\n\nSometimes a new chief or sheriff takes over the department, doesn't like the policy, and cancels the sex offender registry.\n\nHere's another scenario: When the convicted sex offender is released from prison, he is given a deadline by the parole board to register.\n\nIf the parole board gives the guy a year, the sheriff's department is probably going to give him a year.\n\nHowever, if the parole board gives the guy a year and the county sheriff wants him off the street, he will register the convicted sex offender that day.\n\nIn the case of Felix-Jimenez, the sex offender registry is mandatory and the deadline wasn't up yet, so how he is able to be on the loose is still unclear.\n\nThe good news is that Felix-Jimenez hasn't gone into hiding.\n\nIn fact, the most recent report shows that he is staying in a homeless shelter in Van Nuys.\n\nCalifornia doesn't want him there.]" time="0.309"><properties><property name="score" value="0.48903033" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.48903033 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.48903033
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Granted, my current policy does not meet what I want to do, so I have done some thinking on what changes would be nice. There are two major changes I think should be made.\n\nThe first would be to include the deletion policy as the first part of the \u201cFAQ\u201d section, as opposed to the second, where it is now. The issue here is that it is currently hidden away, and unless you know to go there, you might not even know it exists. This is why I believe the policy should be in the FAQ, in addition to the other policy changes.\n\nThe second major change would be to change the time periods for deleting and undeletion requests. Currently, these time periods are a month for both and can be extended for a total of 2 months. These time periods need to be shortened. If a user creates an account, and decides it is not for them within a week, they should be able to delete it without the issue being made public, since no other users have commented on it. If a user creates an account and decides that it is not for them within the first month, they should also be able to delete it without it being made public. Also, it is not fair to users who are newer, and decide that they do not wish to use the site for the first time period to only have it deleted. These users should be able to delete them after this time period if they choose. I believe these time periods should be a month for deletion requests, and 2 weeks for undeletion requests.]" time="0.277"><properties><property name="score" value="0.010463812" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Perhaps best known for their exploits during the First World War and the Gallipoli campaign in particular, the ANZACs, or Anzacs, are the legendary members of the Australian and New Zealand Army Corps.\n\nTheir contribution to the military campaign in the Middle East, including the battle at Gallipoli in 1915, will be recognised this year, with the 100th anniversary of the Gallipoli campaign being commemorated by the nations involved.\n\nThe events of the Gallipoli campaign resulted in heavy casualties, with a staggering 258,000 deaths and an additional 156,000 injuries for the Allied forces, including 44,000 British deaths and 29,000 French deaths.\n\nThe staggering casualty figures have subsequently been seized upon by those who question the strategic worth of the campaign.\n\nOne figure, British historian Niall Ferguson, wrote that \u201cthe Dardanelles fiasco was one of the greatest military blunders of all time, a story of incompetence, vanity and wishful thinking out of which could have been constructed a textbook case of how not to run a war\u201d.\n\nSo why were the Gallipoli campaign and the actions of the ANZACs so significant for Australia and New Zealand, and what did the battle mean for the two countries?\n\nArrival of the ANZACs\n\nFollowing the outbreak of war in 1914, the Australian and New Zealand forces began arriving in Egypt. On February 25 1915 the first ANZAC troops arrived at Gallipoli, a total of 11,000. The rest of the 20,000 strong force arrived over the following weeks.\n\nMany of the ANZAC troops had volunteered at the outbreak of war, lured by the romantic and patriotic view of warfare and by a yearning for adventure.\n\nJust as the troops were largely made up of volunteers, the casualties at Gallipoli were also predominantly made up of volunteers.\n\nIt has been estimated that 10 percent of all the Australian and New Zealand troops at Gallipoli were killed during the campaign.\n\nAustralian Prime Minister Sir Robert Menzies commented that \u201cthe experience of war for Australians would always be Gallipoli\u201d.\n\nPrior to the arrival of the ANZAC troops, the British had launched an attack on the Gallipoli peninsula on the 25th of April 1915.\n\nThe Allied attack consisted of five divisions, with most of the troops coming from the British Army. It was hoped that the landings would help the British Navy to get through the Dardanelles, a narrow strip of water separating the Aegean Sea and the Sea of Marmara, which leads to the Bosphorus and the Black Sea.\n\nHowever, the initial landings met with great opposition from the Turkish defenders, and the Allied forces soon became pinned down on the beaches and unable to advance.\n\nThe ANZAC troops arrived at Gallipoli, the capital of the Ottoman Empire\u2019s European territories, just over a month later on the 19th of May 1915.\n\nThe ANZACs had initially been part of the British and French force in Egypt. They were moved to a separate command under General Ian Hamilton, with Australian General William Birdwood as his deputy.\n\nA General Order issued on the 3rd of May stated that the Australian and New Zealand troops were to be given \u201cseparate and distinct\u201d duties from those of the British.\n\nThis was not intended to be interpreted as any form of segregation. Rather, it was due to the fact that the Australians and New Zealanders, despite being part of the British Empire, were soldiers who had volunteered from their own country, and who had formed a unique sense of national identity and pride.\n\nIn order to maintain a clear distinction between the Allied forces and the enemy, the ANZACs also adopted their own distinctive insignia, such as a yellow or red poppy on their badges and hats.\n\nHowever, despite the greater efforts to set the ANZACs apart from their Allied allies, the treatment of the soldiers at Gallipoli was the same as that received by the British.\n\nThe ANZACs were given responsibility for the defence of the Anzac Cove, at the northernmost tip of the Gallipoli Peninsula.\n\nThe cove was strategically important to the Turks because of its proximity to the Narrows, the strip of water which separated the peninsula from the Dardanelles.\n\nThe Anzacs were also expected to hold on to the various hills and ridges along the peninsula, despite the fact that the Allied positions were in constant danger of being shelled]" time="0.307"><properties><property name="score" value="0.006048653" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00604865 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00604865
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I love hand-cranked coffee grinders, but a fully automated device that grinds directly into the portafilter has always been one of the holy grails of coffee brewing. The Ekobrew takes a lot of the guesswork out of the whole process. Fill the hopper with whole coffee beans, twist the top to open, drop the portafilter in, turn the handle a few times and you\u2019re ready to make your espresso.\n\nThe container is made of a non-porous material, so you can put ground coffee in it. It also has a couple of holes on the side, so that you can clean it and store it without having to remove the portafilter. The concept is pretty ingenious, but I had some difficulty in actually getting it to work properly.\n\nIn theory, the machine takes a lot of the stress out of making espresso. When it works, the espresso is good. It has a big enough capacity that I could probably make it twice before having to refill it. It would be nice if there was a better way to tell how full it was.\n\nUnfortunately, it\u2019s a fairly unreliable method of extracting espresso. You can only have it set to brew for a specific amount of time. You can\u2019t use any sort of fancy steaming wand to make sure the pressure is exactly right, or adjust the grind to get a specific flavour. I think this device is designed for making a quick shot in the morning and then tossing the puck after the shot is made.\n\nThis is the kind of device that I can imagine being useful to take on a trip, or maybe for an RV or camper, but not in a regular espresso bar or cafe. At the price of $50, I can\u2019t really recommend it, though I do think that it has potential. If it were a bit more inexpensive, I think it would be worth experimenting with.]" time="0.289"><properties><property name="score" value="0.7543941" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Horses, rabbits and fish swimming around in glass globes are an enticing attraction at Hanging Lake Lodge in Fruita. But, for more than a century, the people have had a passion for Hanging Lake.\n\nChildren, horses, deer and pet dogs are all welcome to stay at Hanging Lake.\n\nDogs are welcome at Hanging Lake Lodge, as long as they don't swim.\n\n"There were (people) that were always trying to get to the lake," said Dale Hanks, whose great grandfather built the original Hanging Lake Hotel.\n\nHanks has been running Hanging Lake Lodge since 1972, and says his customers are almost always from out of town.\n\n"They've been told about it by their neighbor, they've been told about it by their son who visited last year, they've been told about it by friends in Colorado, and when they're here they just have to come," Hanks said.\n\nMany visitors are drawn to Hanging Lake by the nearby Red Canyon, as well as the Colorado National Monument. The lake is located in a canyon along the Colorado River, nestled at the base of a rock formation called the Palisades. The National Monument, also known as The Dots, is a rock formation of mostly red and orange that spans for about a mile along the Colorado River.\n\nThe Dots.\n\nHanging Lake is a water body that was formed by lava over millions of years, according to the National Park Service. The water body is fed by a small underground river and water seeps out through the canyon walls to form the lake.\n\nHanging Lake is known as one of the most picturesque lakes in the country, and often the photos seen online or on Instagram have a filter on them. The color of the water is bright blue, the rocks are a fiery red and orange, and the waterfalls are turquoise blue.\n\nA tourist sits by the Hanging Lake waterfall.\n\n"It's an excellent opportunity to do some waterfall photography," said Ben Lin, a Denver resident. "That is what drew me here, the waterfall, and I don't know why, but it is very hard to take a bad picture here."\n\nLin has been to Hanging Lake several times, the first time in 2015. He came with a small group of about 10 people, and the people in his group were in awe at the sight.\n\nThe fall\n\n"This is the best," Lin remembers one person saying. "This is the best picture, we are so lucky."\n\nThe water temperature in the summer is about 45 degrees, and not many people are willing to dive into the water, which Lin says is a shame.\n\n"I feel like you should be able to swim here, it's a beautiful place to swim," Lin said. "The problem is the lake is only as deep as your chin. When you're done swimming there is all that debris and gunk on the lake, you can't see it from up above, but as you're swimming you feel the gunk and rocks in the bottom of the lake."\n\nAlthough swimming is prohibited, people do still swim in the lake, which causes the algae to increase, according to the National Park Service.\n\nHanging Lake is one of the first stops for many travelers, but after leaving the picturesque sight, many people don't realize there is so much more to Fruita than Hanging Lake.\n\nNext time you are passing through the small town of Fruita, consider stopping at Hanging Lake Lodge for lunch, a short hike, or an afternoon in a hammock. The history behind the town and the visitors will not disappoint.\n\nEditor's note: This article has been updated to correct information about Hanging Lake. The photos seen on Instagram are not enhanced in any way.]" time="0.363"><properties><property name="score" value="0.5361507" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.5361507 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.5361507
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[During my first month of graduate school, I received a call from my aunt on a weekend when I was in the middle of working on my thesis. She needed help moving out of a rental property she owned. I went over that weekend and helped her clear out the house.\n\nAfter it was all done, she said to me, \u201cYou know, a lot of people would be really upset at me for making them do this.\u201d\n\nI smiled.\n\n\u201cThat\u2019s why I am here.\u201d\n\nIt\u2019s funny how a simple answer can change the dynamics of a relationship.\n\nI continued to help my aunt after that weekend. She would ask for my help, and I would drop what I was doing. She asked, I gave. I took it for granted that it was my responsibility to help her out, to be available. I also took it for granted that she was comfortable asking me for help.\n\nA few years ago, I went to see my aunt in the hospital. She was having a difficult time recovering from her medical procedure, and I was her first call. I didn\u2019t think twice about dropping everything and going over to her place to take care of her and her dog, especially since she had just moved to an apartment that didn\u2019t allow dogs.\n\nBut I got to the hospital and found out that my uncle was also at the hospital. I didn\u2019t realize that he was in the hospital, and, by the time I found out, he was asleep in a nearby room. I talked to my aunt and we came to the realization that it was important for her to have my uncle there. She needed him in a way that she didn\u2019t need me. I left.\n\nI don\u2019t think my aunt and uncle even realized how much I had changed. I was not as available to help as I used to be, and I knew my time was better spent on other things. I was a graduate student, after all, and I had a whole other life to live.\n\nAs a result of all of this, my aunt and uncle started to depend on others to help out more. They hired a house cleaner and a housekeeper. They began to call people in order to receive the help they needed. I had thought that they would not want to go through the hassle of finding someone to help, but they did.\n\nIt\u2019s as if they needed to be reminded that it was okay to ask for help. They needed to realize that asking for help wasn\u2019t a sign of weakness, but a sign of strength. That asking for help meant you were confident in who you were and what you had to offer, and that you weren\u2019t afraid to ask for help if you needed it.\n\nIn doing so, my aunt and uncle showed me what it meant to ask for help, and I realized that asking for help could be a sign of strength, not weakness.\n\nAdvertisements]" time="0.320"><properties><property name="score" value="0.044473473" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Overview\n\nGreta Esta\xf1ol's Carmina \xc1urea are sacred poems meant to inspire devotion in the faithful. They are simple in form, yet profound in content. The author has combined medieval traditions with a contemporary perspective on the faith, creating a simple, sincere, and authentic rendition of the Catholic religion. It was in this vein that she wrote these lyrical and enlightening poems. The collection consists of approximately two hundred poems, many of which have been translated from Esta\xf1ol's Spanish original by Michael Coffey. Carmina \xc1urea are an introduction to Christian spirituality. This collection contains the following poem: To Learn the Way\n\n\n\nThe Value of Purity\n\nLove Conquers the World\n\nHoly Bible\n\nThe Sacraments\n\nLiturgical Calender\n\nMy Jesus\n\nA Prayer for Peace\n\nGod Loves Me\n\nThe Feast of the Immaculate Conception\n\nThe Sacrament of Baptism\n\nFaith and Confession\n\nThe Sacrament of Holy Communion\n\nOur Father, Who Art in Heaven\n\nThe Story of Our Lord's Birth\n\nThe Easter Vigil\n\nThe Holy Mass\n\nThe Sacrament of Marriage\n\nThe Sacrifice of the Mass\n\nThe Sacrament of Confirmation\n\nHoly Mary, Our Mother\n\nSacred Heart of Jesus\n\nOur Lady of Sorrows\n\nThe Our Father and Hail Mary\n\nThe Great Love\n\nBlessed Virgin, My Mother\n\nThe Holy Rosary\n\nThe Sacrament of Penance\n\nThe Gifts of the Holy Spirit\n\nHoly Spirit, Breathe on Me\n\nThe Day of Judgment\n\nThe Second Coming of Our Lord\n\nThe Epiphany\n\nOur Lady of Guadalupe\n\nThe Holy Spirit\n\nHoly Trinity, Trinity\n\nO Lord, I Will Not Keep Silent\n\nThe Most Holy Eucharist\n\nThe Trinity\n\nO Most Holy Trinity\n\nJesus, Mary, Joseph\n\nAn Angel of God\n\nOur Father, Who Art in Heaven\n\nOur Lady of Guadalupe\n\nHoly Father, Have Mercy on Me\n\nThe Sacrament of Extreme Unction\n\nThe Incarnation of Our Lord\n\nIn the Beginning\n\nAmen\n\nThe Power of Prayer\n\nTo a Loved One\n\nThe Love of God\n\nThe Holy Spirit\n\nWho Is the Holy Spirit\n\nHoly Spirit, the Breath of Life\n\nGlory Be to the Father\n\nThe Holy Family\n\nOur Lady of Lourdes\n\nBlessed Mother, Behold Your Son\n\nHail, Holy Queen\n\nTo Mary, My Mother\n\nPraise the Lord\n\nHail, Holy Queen\n\nTo the Crucifix\n\nThe Angelic Salutation\n\nA Prayer for Parents\n\nTo the Sacred Heart of Jesus\n\nA Prayer of Thanksgiving\n\nCome, Holy Spirit\n\nJesus Christ, My Love\n\nThe Holy Spirit\n\nHoly Spirit, Dwell in Me\n\nO Holy Spirit, Thou Who Art Thrice Holy\n\nO Holy Spirit, Unction of God\n\nO Spirit of Love, Uniting Soul and Body\n\nCome, Holy Spirit, Come\n\nHoly Spirit, Light of Love\n\nHoly Spirit, Send Your Spirit of Love\n\nHoly Spirit, The Spirit of Love\n\nThe Holy Spirit\n\nThe Trinity\n\nAll Creation Loves You\n\nThe Baptism of Jesus\n\nAn Angel of God\n\nHe Is a Man Who Sees\n\nBehold the Word Made Flesh\n\nSing a Song of Incarnation\n\nBehold the Door of the Kingdom of Heaven\n\nMay the Glorious Mysteries of Jesus\n\nCome to Us, O Jesus\n]" time="0.306"><properties><property name="score" value="0.15941599" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.15941599 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.15941599
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Canonical Path for Classes\n\nLast Updated on Wed, 04 Jan 2016 | Excel 2003 VBA\n\nWhen you create a class module, you must specify the following items in the declaration:\n\n\u25a0 The class name\n\n\u25a0 The objects that are instances of the class\n\n\u25a0 The properties that the class will support\n\n\u25a0 The methods that the class will support\n\n\u25a0 The events that the class will support\n\nAll classes in Excel derive from a generic base class called Object, which is an instance of the class of the same name. The Object class is an abstract class and doesn't have a constructor. If you don't have any idea what I'm talking about here, don't worry about it for now. I'll explain it in detail in Chapter 5. You can't instantiate an object from the Object class, so the only real purpose of the Object class is to serve as a base class for other classes. You can think of the Object class as being like a template that all other classes derive from. If you want to learn more about how classes work and how you can customize Excel's classes to create your own customized classes, check out my Microsoft Press book Microsoft Excel VBA and Macros (ISBN 0-7356-1845-0).\n\nWhen you create a class module in your Excel application, you must specify the class name as a string literal. For example, if you create a class module called Class1, Excel uses the following syntax in the declarations area of the class module to specify the name of the class:\n\nPublic Class Class1 End Class\n\nAs with any other module in Excel, a class module doesn't do anything until you create an object from the class module. Creating an object is a two-step process: You first instantiate the object, and then you call the methods and properties of the object. For example, to create an object from the class named Class1, you use the following code:\n\nDim obj1 As New Class1\n\nOnce you create an instance of the object, you can call the methods and properties of the object by preceding the method or property name with the name of the object. For example, if you created an instance of the class named Class1, you would use the following code to call the method named Display:\n\nobj1.Display\n\nIf the object contains an object variable that represents another object of the same class, you can also call the methods of that object. For example, if the object named obj1 created in the preceding code contained an object variable named obj2 that represented another object of the same class, you would use the following code to call the Display method of the object named obj2:\n\nobj1.obj2.Display\n\nThe property and method names of a class are preceded by the name of the class, as shown in the preceding examples.\n\nIf you create a class module that contains a custom collection object, such as a collection of cells in a worksheet, you must use a new operator to create the collection object. For example, the following statement creates a collection object named myCol1 that is a collection of worksheet cells:\n\nDim myCol1 As New Collection\n\nWhen you create a collection object, you specify the type of object that the collection can contain when you define the type of the collection.\n\nFor example, the following statement creates a collection object that can contain only the cells in a worksheet:\n\nDim myCol1 As New Collection(Worksheet.Range)\n\nWhen you create a collection object, you can add items to the collection object by using the Add method of the collection object.\n\nFor example, the following statement adds a range named "Region" to the collection object named myCol1:\n\nmyCol1.Add mySheet.Range("Region")\n\nThe Add method takes two arguments:\n\n\u25a0 The object that you want to add to the collection object\n\n\u25a0 The collection that you want to add the object to\n\nWhen you create a collection object, you can add an object to a collection object that is an instance of a different class, but the type of the objects in the collection must be the same.\n\nThe following code example adds the range named "Region" to the collection object named myCol1. This code example assumes that you've created the objects in the declaration section of the class module.\n\nSub AddObjectToCollection() Dim myCol1 As New Collection(Worksheet.Range) Dim myRow As Long, myColumn As Long Dim strName As String ' Obtain a reference to the collection ' that contains the first worksheet in ' the active workbook. Set myCol1 = Sheets(1).Range(1, 1). _ SpecialCells(xlCellTypeVisible) ' Initialize the name of the cell ' to the value of the Name property. strName = myCol1.Cell(1, 1).Value ' Determine the address of the cell ' and store it in the myRow and myColumn ' variables. myRow = myCol1.Cell(1, 1).Address myColumn = myCol1.Cell(1, 2).Address ' Create a new Range object. Set myRange = Worksheets("Sheet1"). _ Range("Region") ' Add the new range to the collection. myCol1.Add myRange End Sub\n\nThe following code example calls the AddObjectToCollection method to add the range named "Region" to the collection object named myCol1. This code example assumes that you've created the objects in the declaration section of the class module.\n\nSub AddObjectToCollectionWithMethodCall() Dim myCol1 As New Collection(Worksheet.Range) Dim myRow As Long, myColumn As Long Dim strName As String ' Obtain a reference to the collection ' that contains the first worksheet in ' the active workbook. Set myCol1 = Sheets(1).Range(1, 1). _ SpecialCells(xlCellTypeVisible) ' Initialize the name of the cell ' to the value of the Name property. strName = myCol1.Cell(1, 1).Value ' Determine the address of the cell ' and store it in the myRow and myColumn ' variables. myRow = myCol1.Cell(1, 1).Address myColumn = myCol1.Cell(1, 2).Address ' Create a new Range object. Set myRange = Worksheets("Sheet1"). _ Range("Region") ' Add the new range to the collection. myCol1.AddObject myRange ' Add another range to the collection ' and display the number of elements in the collection. myCol1.Add myRange MsgBox myCol1.Count End Sub\n\nThe final statement in the AddObjectToCollectionWithMethodCall subroutine is a good example of how you can use a method that belongs to a class to call the methods of the collection object.\n\n0 0]" time="0.712"><properties><property name="score" value="0.0154751043" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Many people who oppose the minimum wage assume that raising the minimum wage is bad for the economy and will cause a lot of unemployment. This is mostly false. A new study has revealed that raising the minimum wage does not kill jobs. This is not just good news for the people who will now get a raise, but also for the economy as a whole.\n\nOpponents of the minimum wage often say that it will create a lot of unemployment and that this is proof that the minimum wage should be abolished. They argue that it creates a job loss on an economy-wide scale. However, this new study has proved that the minimum wage will not cause massive job loss. This is not just great news for the people who get a raise, but it also means that the economy will benefit.\n\nThe study comes from the National Employment Law Project (NELP) and reveals that raising the minimum wage does not cause massive job loss. In fact, only two percent of the workforce is impacted by a minimum wage increase. This means that the economy will benefit, but not that much. However, it is still a positive impact.\n\nHowever, the study also shows that the country would have to raise the minimum wage by $2.13 to achieve the same number of jobs as a similar increase in the 1990s. This is not really a surprise, as the economy was growing more rapidly back then.\n\nRaising the minimum wage was also seen to boost the economy. The study found that a $1 increase in the minimum wage would increase the GDP by $2.62. This is a significant amount and would be great for the economy as a whole. In fact, it could even boost the economy so much that it could lift more people out of poverty.\n\nWhile a raise in the minimum wage does not have a massive impact on the economy as a whole, it still has a positive impact. This means that the people who will now get a raise will enjoy it. This will also help the economy, and make the country a better place to live in.\n\nThose who oppose the minimum wage should know that it does not create massive unemployment. This is also great news for the economy, and it means that raising the minimum wage is great for everyone.]" time="0.364"><properties><property name="score" value="0.0014465919" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[READ MORE Wall Street: Online poker rooms are fading, but who is 6/10/2018 \xb7 As online poker room software and banking options face an uncertain future in the U.S., many of the sites that are still online are trying to\n\nREAD MORE Exclusive: Where do U.S. poker players play online poker 7/10/2018 \xb7 With the April 15th deadline for Nevada-based online poker rooms to stop offering real-money games, where will the displaced players go next?\n\nREAD MORE Online poker room ratings, reviews, and deals - Poker In the wake of Black Friday, you can\u2019t walk three feet in a Las Vegas casino without bumping into someone who\u2019s looking for a blackjack\n\nREAD MORE Nevada Online Poker Rooms On Verge Of Exiting Market Online poker rooms in the United States are in a precarious position right now. They still have a month left to get their affairs in order,\n\nREAD MORE What Happens To U.S. Poker Players Now? - Card Player 4/3/2019 \xb7 For a site to be eligible for inclusion on the Upcoming US-facing Online Poker Sites list, it must be confirmed to launch in the United States. This means\n\nREAD MORE Who are the best US poker sites in 2019? | Best US poker 3/11/2019 \xb7 The only active and legal online poker room in the U.S. is currently the 888 Poker. The American online poker has not gone anywhere since Black Friday,\n\nREAD MORE Gambling in the United States - Wikipedia Online Poker Reviews - Top Rated Online Poker Sites for 2018. Online poker rooms in the United States are not as popular as in other countries due to\n\nREAD MORE Online Poker Sites in the United States, All Active and Are Online Poker Rooms Still Profitable? Find out more about the best online poker rooms in the United States today.\n\nREAD MORE Poker News & Articles: Read Online & Watch the Live Videos A ranking of the best online poker rooms in the United States, including casino sites for U.S. players and trusted online poker rooms with\n\nREAD MORE Casino Game Reviews - Top Rated Online Poker Sites for 5/22/2016 \xb7 Though not as big as the gambling industry in other parts of the world, the United States does offer a number of legal gambling options to its\n\nREAD MORE Online Poker News - Latest News from Online Poker Rooms 2018 Online Poker Sites 2018 is a collection of the best online poker rooms available today for US players. You can find all of the important info\n\nREAD MORE Where are the best US online poker rooms right now? 7/17/2017 \xb7 The legal US online poker landscape could be getting a little bit clearer, as Nevada has once again made a bill that would create an online poker licensing\n\nREAD MORE Online Poker News & Articles - Poker News | Upswing Poker Blog 4/29/2015 \xb7 Online poker in the U.S. has long been an industry in limbo, with the legality of the business depending on how you define it. Now the U.S.\n\nREAD MORE Las Vegas Poker Rooms, Poker Tournaments and Game The list of best US poker sites in 2019 includes the latest online poker rooms that cater to United States-based poker players. Read about the top U.S. poker\n\nREAD MORE Online Poker in the U.S. \u2013 The Ultimate Guide | Upswing Poker Online poker room reviews featuring top sites for US players. Exclusive poker bonuses, promotions and expert reviews.\n\nREAD MORE Online Poker Guide for U.S. Poker Players - US Poker Guide 4/29/2015 \xb7 Online poker is now more popular in the U.S. than in Europe. In the U.S., state laws and gambling regulations differ by state, and some states have\n\nREAD MORE Vegas Palms Online Casino, Online Poker & Online Slots Join PokerStars and enjoy top quality online poker. New players get a 100% match bonus up to $600. Play on Windows PC and Mac with our instant download client.\n\nREAD MORE Gambling in the United States - Wikipedia The U.S. online gambling market is the largest in the world. By some estimates, the U.S. accounts for one-third of all online gaming revenue.\n\nREAD MORE Online Poker in the U.S. \u2013 The Ultimate Guide | Upswing Poker Online Poker Guide for U.S. Poker Players. If you are a poker player looking to play online poker in the United States, here you will find the latest\n\nREAD MORE Online Poker and Gambling Laws for 2018 - Casinolistings.com 4/15/2017 \xb7 In the wake of Black Friday, the number of online poker rooms in Nevada dwindled from six to just one, and the number of players dropped\n\nREAD MORE Poker Players on a Dime: What US Online Poker Rooms Are 2014 Online Poker Sites - US Online Poker Guide. List of Top USA Poker Sites accepting U.S. Players including all the latest bonuses and promotions.\n\nREAD MORE Online Poker USA \u2013 Online Poker Sites for US Players A brief introduction to online poker and online gambling in the United States.\n\nREAD MORE USA Online Poker Guide - UsaPokerOnline.com 5/12/2019 \xb7 "We are going to be online, we are going to be regulated," said Robert Capecchi, director of federal legislation at the Marijuana Policy Project, who led a\n\nREAD MORE Online Poker and Gambling Laws for 2018 | GamingLawOnline.com Gambling in the United States has been legal in each of the 50 U.S. states since 1911, except for a brief prohibition after World War I. At the\n\nREAD MORE 5 Must-Visit Online Poker Rooms for U.S. Players 4/15/2017 \xb7 Exclusive: Where do U.S. poker players play online poker now? We asked, and you answered. We asked, and you answered.\n\nREAD MORE Online Poker in the US in 2017 - Online Poker Guides, Tips U.S. online poker has a dark history, littered with fraudulent players and hacked accounts. This guide will help you find a safe place to play.\n\nREAD MORE Online Poker Rooms - ThePokerBank.com Nevada-based poker rooms have until April 15th to exit the US market or risk being shut down. Players are looking for a new online poker home.\n\nREAD MORE Online Poker Room Rankings - ThePokerBank.com Learn more about top online poker sites and poker rooms in the United States.\n\nREAD MORE USA Online Poker Guide | Play Poker Online in the US U.S.A. Online Poker Sites. A list of all the best USA online poker sites, casino sites, and sportsbook sites with information on bonuses, games, and more.\n\nREAD MORE USA Online Poker Guide: Reviews, News, & Tips - Worldwide 7/16/2015 \xb7 The status of online poker in the United States is likely to remain a confusing mess for a]" time="0.765"><properties><property name="score" value="0.047610949999999985" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04761095 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04761095
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Michal Ha\u0161ek\n\nMichal Ha\u0161ek (born April 8, 1980) is a Czech professional ice hockey goaltender who is currently playing with HC Pardubice of the Czech Extraliga. He previously played in the National Hockey League for the Detroit Red Wings, Chicago Blackhawks, Colorado Avalanche, Ottawa Senators, and Florida Panthers.\n\nHa\u0161ek spent the 1996\u201397 season with HC Pardubice's junior team, and then joined the Czech Extraliga club HC Vset\xedn, appearing in 29 games. Ha\u0161ek was a member of the Czech Republic national under-18 team at the 1997 European Junior Championships, playing in two games and posting a 1.51 GAA.\n\nThe next season, Ha\u0161ek joined HC Pardubice, which was then playing in the Czech 1. Liga. Ha\u0161ek played well for the team, and was chosen by the Colorado Avalanche in the sixth round, 162nd overall, in the 1998 NHL Entry Draft. He remained with HC Pardubice, and in his final season with the club, he posted a 2.30 GAA in 37 games. Ha\u0161ek was signed by the Avalanche, and on March 9, 2000, he made his NHL debut, against the Detroit Red Wings. He played two more games for the Avalanche before returning to the Czech Republic to join HC Pardubice for the 2000\u201301 season.\n\nHa\u0161ek played in 11 games for the Avalanche the next season, but spent the majority of the 2001\u201302 season with the Hershey Bears of the American Hockey League, where he posted a 2.20 GAA in 44 games. He remained in North America the next season, playing five games for Colorado and 59 for Hershey, and was then traded to the Chicago Blackhawks for a sixth-round pick in the 2004 NHL Entry Draft on March 10, 2003. Ha\u0161ek played well for the Blackhawks in 2003\u201304, with a 2.11 GAA in 37 games.\n\nThe next season, Ha\u0161ek played well for the Blackhawks, with a 2.22 GAA in 36 games. However, he was unable to maintain his form, and was replaced as Chicago's starting goaltender by Nikolai Khabibulin, who had been acquired by the Blackhawks in a trade with the Tampa Bay Lightning. Ha\u0161ek was then traded to the Ottawa Senators on March 9, 2005, for a second-round draft pick in the 2005 NHL Entry Draft.\n\nIn his first season with the Senators, Ha\u0161ek played in 40 games, and posted a 2.26 GAA. He then missed the majority of the 2005\u201306 season after suffering a shoulder injury. He appeared in just five games for the Senators, and was traded to the Colorado Avalanche for Patrick Eaves, a second-round draft pick in the 2006 NHL Entry Draft, and a third-round pick in the 2007 NHL Entry Draft on September 25, 2005.\n\nHa\u0161ek quickly returned to form with the Avalanche, playing in 54 games and posting a 2.22 GAA. In 2006\u201307, he played in 57 games, and posted a 2.30 GAA. Ha\u0161ek was an important factor in the Avalanche's playoff run, as he posted a 1.65 GAA in eight games.\n\nOn June 19, 2007, Ha\u0161ek signed a two-year contract extension with the Avalanche. The following season, he played in just 35 games due to a groin injury, and his GAA rose to 2.88. He was then sidelined for the rest of the season after having shoulder surgery.\n\nOn June 30, 2009, Ha\u0161ek signed a two-year contract with the Detroit Red Wings. He recorded the first win of his Red Wings career on January 2, 2010, in a 3\u20131 victory over the Chicago Blackhawks.\n\nOn January 1, 2011, Ha\u0161ek was named the First Star of the Week for the week ending December 26. Ha\u0161ek compiled a 3\u20130\u20130 record, a 0.67 goals-against average and a .984 save percentage. He led the Red Wings to their fifth four-game winning streak of the season. During the streak, Ha\u0161ek stopped 135 of 138 shots and yielded only one goal in a span of 140 minutes and four seconds.\n\nOn January 20, 2011, Ha\u0161ek was selected as the NHL's Third Star of the Week. He went 2\u20130\u20131 in three appearances, with both victories coming against Central Division rivals (January 14, 3\u20130 win at Chicago and January 16, 4\u20131 win at St. Louis), and recorded a 1.00 goals-against average and a .962 save percentage.\n\nHa\u0161ek finished the 2010\u201311 season with a career-high 41 victories, just one win behind league leader Martin Brodeur.\n\nOn March 29, 2011, Ha\u0161ek scored a goal against the Los Angeles Kings. The goal, a result of a breakaway due to an errant pass by Kings defenseman Slava Voynov, was the second of Ha\u0161ek's career. His first goal was scored against the Tampa Bay Lightning in 2008. The goal also made him the oldest goaltender in NHL history to score a goal in a game. The record was previously held by Tommy Salo, who scored a goal in a game at the age of 35.\n\nOn May 31, 2011, Ha\u0161ek underwent surgery to repair a torn labrum in his right shoulder.\n\nHa\u0161ek was injured during the 2011\u201312 preseason, and on October 2, 2011, was placed on long-term injured reserve by the Red Wings. He returned from his injury to back up Ty Conklin for a game against the Phoenix Coyotes on November 29, 2011.\n\nOn July 5, 2012, Ha\u0161ek signed a one-year, $2.05 million contract with the Florida Panthers. He was named the starting goaltender in the Panthers' inaugural game in the 2012\u201313 season against the New Jersey Devils. He was subsequently pulled in the first period after allowing 4 goals on 15 shots. He was replaced by Scott Clemmensen, and on January 24, 2013, Clemmensen was named as the Panthers' starting goaltender for the remainder of the season.\n\nHa\u0161ek was placed on waivers by the Panthers on June 13, 2013. Ha\u0161ek was then bought out from the final year of his contract on June 15, 2013. He was then signed by the Detroit Red Wings for the 2013\u201314 season to backup starter Jimmy Howard.\n\nHa\u0161ek became an unrestricted free agent in the off-season, and on September 11, 2014, signed his first contract abroad, agreeing to a one-year deal with HC Pardubice of the Czech Extraliga. After one season in Pardubice, Ha\u0161ek opted to continue in the Extraliga, signing a two-year deal with HC V\xedtkovice. In his second season with V\xedtkovice, Ha\u0161ek helped his club claim its first league title since 1999, appearing in 15 playoff games. He left as a free agent to sign a one-year contract with HC Pardubice on June 19, 2017.\n\nHa\u0161ek played for the Czech Republic at the 2002, 2003, 2004, and 2005 World Championships, winning bronze in 2004 and 2005. Ha\u0161ek was the starting goaltender for the Czech Republic team that won the gold medal at the 2004 World Cup of Hockey.\n\nIn 2003, Ha\u0161ek became a Canadian citizen, but had already represented the Czech Republic in international competition, and he was therefore eligible to play for either national team. On November 7, 2005, he announced that he would continue to represent the Czech Republic, even though he had been approached by the Canadian team and was eligible to play for Canada. Ha\u0161ek's younger brother Ond\u0159ej also plays professional hockey.\n]" time="0.621"><properties><property name="score" value="0.31033863" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Bitcoins are widely considered a great way to make purchases, but it is much harder to pay someone with them. That is exactly the case with Andreas Antonopoulos. He has reportedly been bombarded with requests from individuals who want to make donations to his projects. But he has no means of receiving them.\n\nIs Andreas Antonopoulos Being Misled?\n\nMost people know Andreas Antonopoulos by now. He is one of the most popular and prolific figures in the Bitcoin world. However, the widespread adoption of Bitcoin has led to a lot of new users, many of whom do not have a great understanding of the technology. That is not necessarily a bad thing, though.\n\nIt now appears as if a lot of people think Andreas Antonopoulos accepts donations, whereas he doesn\u2019t. As such, people keep bombarding the Bitcoin community icon with messages asking how they can make a donation. This leads to quite a few jokes being made about it on social media. However, Andreas Antonopoulos is well aware of the situation, as he keeps getting the same questions.\n\nHowever, the most intriguing part of this situation is how Andreas Antonopoulos makes it clear he doesn\u2019t accept donations. For some reason, some people continue to pester him about it. Some individuals even claim they are only able to donate a small amount of money, which would make no sense whatsoever.\n\nThe Andreas Antonopoulos Donation Account\n\nInterestingly enough, Andreas Antonopoulos is quite open about Bitcoin donations, but only to the extent of signing them over to projects. That is not what most people would expect, but it makes a lot of sense to give this money to a good cause. For example, Antonopoulos has donated over US$5,000 worth of Bitcoin to help rebuild the war-torn Marawi in the Philippines. It is evident this money came from donations he received, which is a very interesting development.\n\nThat being said, donations can still be made to Andreas Antonopoulos, even though it is done in a different way. Instead of sending money to his personal wallet, a public Bitcoin wallet has been created for donations to be sent to. That wallet has been active for some time now, and users can send money to a wide range of Bitcoin and Bitcoin Cash wallets.\n\nDo you think donations should be sent to Andreas Antonopoulos? Let us know in the comments below.\n\nImages courtesy of Shutterstock\n\nread original article here]" time="0.289"><properties><property name="score" value="0.0013766944" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00137669 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00137669
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rottnest Island\n\nThe second island in the chain, after its neighbours Fremantle and Rottnest, is Barrack Street. In 1831, a convict ship called the \u201cDuke of Wellington\u201d (there are other tales about the origins of the name) ran aground here and was eventually abandoned. The women were moved to Fremantle Prison. The wreck is still there, but it is being eaten by the sea. You can walk to it on a path from Waterhouse Beach. The best way to see the island is by bike, though, because it is so small and flat. The bikes are provided by a company called Island Experience Rottnest. This is a great way to see the island. It costs around $25, which gets you a bike and the unlimited use of it for three hours. They give you a map and instructions, but you can see the whole island by walking in about an hour.\n\nThere are very few buildings here, but what there are have a very interesting history. For example, there is the Weeroona Hotel, the oldest operating hotel in the state. It is run by a company that is owned by the island\u2019s inhabitants. The oldest building is called the Round House. It was built in 1833 and has been restored to the 1830s period. It used to be the men\u2019s quarters. There is also a small cathedral that was built in 1901, and is called St Mary\u2019s Cathedral. There is also a cricket ground here that was originally established in the 1840s. This island was once the penal colony. The ruins of two of the prisons, the Governor\u2019s residence and the convicts\u2019 huts can be seen. They are located at a place called Settlement.\n\nCamel Rock\n\nThis is the most important landmark of the island. It is visible for many miles, and is sometimes mistaken for a camel. The sandstone is interesting, as it was formed from quartzite, which is a very hard stone. Some of the grains have been turned to iron oxide, which is a reddish brown. This was done by chemical reactions that were the result of oxygen and iron.\n\nSome rock formations can also be seen at the Quobba station, which is a restored 19th century railway station. There are a few lookouts here, but the best is at Arch Rock, which is a short distance from the main road. There are about 200 species of birds here, and there is a sanctuary that is managed by a conservation group called the Rottnest Island Conservation Society. This is home to the Tawny Frogmouth, the Black-breasted Button-quail, the Malleefowl, and the Rottnest Island White-tailed Black-Cockatoo.\n\nThere is also an Interpretive Centre that explains the history of the island and its different birds. Another reason to visit this island is the fact that the Aboriginal people, the Wadjuk, were here first. There is an Aboriginal reserve that is in the northern area of the island, and there is also a sacred site that can be seen there. The site is called Yanjul, which means \u201cman with spear\u201d. The local Aboriginals still refer to the island as Wadjemup, which means \u201cIsland of Peace\u201d. The First Fleet stopped at this island, and as such it is the only island in the world where two different nations fought for control.\n\nPlaces to Stay\n\nThere are a few different places to stay on this island. Most of the accommodations are self catering. There are also a few bed and breakfasts, and there is even a four star hotel called the Sheraton Rottnest Island Resort. There are over 250 different cottages to stay at, some of which have been converted from old army barracks. The Great Western Hotel is the only hotel here that has electricity and telephone connections, so you may want to stay there if you want to be near the center of things. There are many hotels here, but most of them are more expensive than the average.]" time="0.329"><properties><property name="score" value="0.12745926" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.12745926 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.12745926
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[So, I never thought this day would come, but after several years of wrestling with this series, I have finally been forced to give up on it.\n\nI read The Fellowship of the Ring many years ago, and loved it. It was one of the books that inspired me to get into fantasy fiction. The author, J.R.R. Tolkien, was a legend in the world of fantasy fiction, and it was considered one of his greatest works.\n\nAt the time, I hadn't heard of this series. If I had, I probably would have thought "Ew, it's another fantasy book." It would take me several years to learn that it's not another fantasy book. This is the one that started it all.\n\nThe story was great, and I really liked how Tolkien put all his imagination into it, and wrote a story that was unique and innovative. The story itself was fascinating. I loved the idea of Hobbits, which are little people that lived in an idyllic area, with their own language and customs. This book had a dark side, and even the humor in it was dark. There was a lot of death, evil, and destruction in the book. That's something that stuck with me, even though I really didn't appreciate it at the time. I was in my tween years, and just didn't understand it.]" time="0.310"><properties><property name="score" value="0.035048194" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Reviews (15) Write a Review\n\nCool costume Perfect fit and great quality. Looks just like the picture. Happy with purchase\n\nDoesn\u2019t fit like the other girls ones! The body piece is way too long for a normal sized girl, there\u2019s so much extra material, you can barely make it look like the girl in the picture. It doesn\u2019t look as cute as the other girls ones, and the extra length isn\u2019t easy to shorten, because of the netting on the bottom.\n\nFun! Love this costume! My daughter is small and the medium was perfect! Can\u2019t wait to see her in it at school on Halloween!\n\nBeautiful! This costume is beautiful! It fits true to size and looks great!\n\nGorgeous costume I love this costume and it fits true to size. I have a slender 7 year old, ordered the size 6-8, and it fits well with some room to grow into. The only drawback I see is the flippers are sewn into the gloves so she won\u2019t be able to wear them separately, but that\u2019s a small sacrifice for the beauty of this costume!\n\nCutest! Love it! My 5 yr old loves her new swimmer costume. It's made well, super cute and just the right amount of "bling"!\n\nSO STINKING CUTE! This costume is exactly what I was looking for! It\u2019s super cute and fits well. My daughter is a 4t and I got her a 5-6 and it fits great! It\u2019s also not super thin. It\u2019s very well made!\n\nWonderful costume! Beautiful! Super cute and made well.\n\nExcellent quality! I\u2019m always apprehensive when ordering on-line, but was very pleased with the quality of this costume!\n\nBeautiful This costume is so beautiful! The colors are vibrant and fun, the quality is fantastic and the fit is perfect!\n\nSo pretty I bought this for my 4 year old daughter and she loves it! She is tiny so I ordered her a 4-6 which fit perfectly. It's well made and super pretty. Can't wait to see her wear it for Halloween\n\nadorable It is very pretty. The top is pretty sturdy. The bottom is light. It fits my 4 year old perfectly. My daughter is little and will not fit for very long. I love it!\n\nsuper cute This costume is so cute! I ordered the size 4-6 for my daughter who wears a size 4 in girl clothes and it fit perfectly. The material on the body piece is thick and the arms and feet are easy to get on and off, without being too loose.\n\nVery pretty I am very pleased with this costume. The colors are so vibrant and the quality is good. The size fits perfect.]" time="0.286"><properties><property name="score" value="0.43850362" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.43850362 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.43850362
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[2013 Crime Rate Indexes North Little Rock, AR 72223 Arkansas United States Total Crime Risk 170.0 91.0 100 Murder Risk 165.0 94.0 100 Rape Risk 164.0 90.0 100 Robbery Risk 157.0 93.0 100 Assault Risk 162.0 92.0 100 Burglary Risk 155.0 89.0 100 Larceny Risk 105.0 92.0 100 Motor Vehicle Theft Risk 132.0 89.0 100\n\nThe data for North Little Rock, AR 72223 may also contain data for the following areas: North Little Rock\n\n\n\nCrime Risk Index (100 = National Average): Index score for an area is compared to the national average of 100. A score of 200 indicates twice the national average total crime risk, while 50 indicates half the national risk. We encourage you to consult with a knowledgeable local real estate agent or contact the local police department for any additional information.\n\n\n\nCrime Indexes are based on numerous current and historical datasets as well as proprietary modeling algorithms which estimate values at more granular geographic levels when specific data is either unavailable or impractical to aggregate. While every effort is made to ensure accuracy, these are estimates and should only be used as a guide. For detailed information regarding crime and safety in a community, please contact local law enforcement agencies.]" time="0.283"><properties><property name="score" value="0.17493972" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Jonathan Daniel/Getty Images\n\nAccording to a source, the Miami Heat has signed Mike Miller to a two-year, $5.5 million contract, and may be on the verge of completing a deal with Rashard Lewis for the veteran minimum.\n\nThe Miller signing comes as the Heat are preparing to play the Chicago Bulls in Game 4 of the Eastern Conference quarterfinals.\n\nMiller averaged a career-low 4.8 points and 1.8 rebounds in just 22 games during the regular season.\n\nHe did not play in Miami\u2019s first-round series against the Milwaukee Bucks, after undergoing surgery to repair a torn tendon in his left foot.\n\nHe played in just two games during the second round series against the Indiana Pacers.\n\nThe Heat's move is somewhat surprising because they're already stacked at the wing position, with LeBron James, Dwyane Wade, James Jones, Mike Miller, and James Jones.\n\nMiller will be limited to roughly 25 minutes a game, according to a source.\n\nMiller has won two NBA titles with the Heat.\n\nHe was the MVP of the NBA Finals in 2006, and has averaged 10.7 points and 4.5 rebounds for his career.\n\nThe Heat are in need of frontcourt depth, because they only have three true big men on the roster, and could use more depth, with Greg Oden having his contract purchased by the team, but not likely to play during the playoffs.]" time="0.271"><properties><property name="score" value="0.0052802633" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00528026 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00528026
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Riot seems to be slowing down its champion creation process. Since the release of the current champion rotation, only five champions have been released. Each of these champions (except for Xerath) was tested in the PBE at some point, so we knew what to expect when the champion was released.\n\nXerath was the next to last champion to be released. He came out in the middle of the season and, because of his kit, has been popular for quite a while. He didn't really have that many people against him, and it didn't take him long to climb into the current meta. He was picked a total of 11 times in the North American Championship Series and showed a 65 percent win rate.\n\nZed, like Xerath, was released at the beginning of the season, but there are still people who have not really mastered him yet. His popularity in the NA LCS was fairly low and his win rate was only 58 percent. Zed's popularity has since risen to the top and he is now played regularly in the NA LCS.\n\nBrand is another interesting case. His play rate has risen from 0 percent in the NA LCS to 3 percent. His win rate is not that great (44 percent), but because he is a burst caster, he fits in with the current meta. As long as you have the ability to lock down one person for a period of time, Brand is pretty strong.\n\nFinally, Vi was the last champion to be released, but her popularity is still a bit low. She has been played nine times in the NA LCS, with a 43 percent win rate.\n\nWith those three champions, Riot has shown that it will not just dump out new champions on the game, and that champions will still have to be tested on the PBE before being released.]" time="0.266"><properties><property name="score" value="0.1678443" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Photo by Gracie Malley for Cannabis Now\n\nAs California rolls out its new cannabis rules \u2014 the most relaxed marijuana laws in the country \u2014 state and local law enforcement officials are attempting to implement the new system with an unprecedented blitz of raids on illegal pot businesses.\n\nWith the stroke of Gov. Jerry Brown\u2019s pen, California became the largest state to legalize marijuana for recreational use and the sixth in the nation to make cannabis available to the general public. Yet, the history of cannabis in California has been a long one \u2014 and not without its rocky moments.\n\nCalifornia\u2019s medical marijuana laws were first approved by voters in 1996 and ushered in a sea change in cannabis culture and use. Yet even in the heyday of Proposition 215, there were raids on medical dispensaries, law enforcement shutting down shops for violation of local zoning codes and municipal zoning laws, local municipalities levying taxes on dispensaries and even offering up community space in which to open shops.\n\nThe result of these early legislative setbacks? The displacement of a long-established network of dispensaries and cultivators. Those who could no longer get by in the state moved to Oregon, Washington, Colorado and other legal states \u2014 essentially exporting the cannabis culture they had created. Now, a new generation of cultivators and distributors are starting businesses in California, with new methods and processes that are a result of the new cannabis industry.\n\nEven as recreational marijuana use became legal in California in January 2018, there has been an uptick in raids of these newly legal businesses, which remains illegal under federal law. In the first week of 2018, there were a reported 26 raids of legal dispensaries in the Bay Area, with 25 arrests and the seizure of $16,000 in cash and seven pounds of cannabis.\n\n\u201cLaw enforcement is going to go after illegal operations in any case,\u201d said Sean Donahoe, executive director of the California Cannabis Industry Association. \u201cThese folks who are doing illegal activities, that\u2019s something they have been doing all along.\u201d\n\nIn California, the rules on commercial cannabis businesses are numerous and complex, he said. The fact that a business may be operating legally, that doesn\u2019t mean it isn\u2019t being targeted for a raid, according to Donahoe. In order for businesses to get permits to operate legally, they have to first get permits to be established.\n\n\u201cSome of the communities, their local government entities have decided]" time="0.307"><properties><property name="score" value="0.0039982432" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00399824 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00399824
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Hillary Clinton was a no-show at the opening of a new museum dedicated to women's history and equality in New York City on Tuesday, a day after she cancelled campaign events because of a stomach virus that left her dehydrated and dizzy.\n\nClinton's Republican opponent Donald Trump and his wife Melania did not attend the high-profile opening either.\n\nClinton's doctor said in a statement Monday that the Democratic presidential candidate had been "diagnosed with pneumonia" on Friday.\n\nThe museum is dedicated to women's history and feminist causes. Clinton's ties with the National Museum of Women in the Arts go back many years.\n\nShe presented the museum's founding patron, Mercedes T. Bass, with a leadership award in 2009. The museum's chair, Susan Henshaw Jones, has been a top Clinton donor.\n\nA spokesman for Clinton said on Monday that the former secretary of state "continues to feel better," but he didn't indicate when she would resume campaigning.\n\nCampaign spokesman Nick Merrill said the Democratic presidential nominee has had an allergy-related cough, and that "several hours of sleep" and some antihistamines helped.\n\nThe illness struck just after Clinton flew back to New York City from a weekend trip to California.\n\nOn Monday, her doctor Lisa R. Bardack said in a statement that Clinton had had an examination of her pneumonia in a chest CT scan.\n\nBardack said the Democratic nominee "is recovering nicely" and has been "advised to rest and modify her schedule" as she continues to recuperate.\n\nClinton abruptly left a 9/11 anniversary ceremony Sunday in New York City after feeling overheated, according to her campaign. She retreated to her daughter's nearby apartment, but later emerged and told reporters: "I'm feeling great. It's a beautiful day in New York."\n\nShe left Sunday's event at Ground Zero shortly after she arrived. Her campaign said she felt "overheated" and departed for her daughter's apartment in New York's Flatiron neighborhood.\n\nVideo captured by a bystander showed Clinton apparently struggle to get into a vehicle as staff members held her up by the arms.\n\nClinton, 68, did not immediately disclose the pneumonia diagnosis. Her aides initially said she had overheated.\n\nBardack said Clinton is "re-hydrated and recovering nicely" after attending a 9/11 anniversary event Sunday.\n\nThe health issue was not mentioned at a fundraising event Monday in Manhattan for Democratic Senate candidate Ted Strickland of Ohio, according to participants.\n\nAsked if the candidate's health was a campaign issue, spokesman Jesse Ferguson said, "No."\n\n___\n\nAssociated Press writers Jonathan Lemire in New York and Ken Thomas in Washington contributed to this report.]" time="0.301"><properties><property name="score" value="0.0061771357" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00617714 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00617714
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The former CEO of St. Louis-based Boeing said he will plead guilty to charges that he approved the improper use of millions of dollars in company funds on home furnishings, a casino and a separate investor-relations matter.\n\nThomas W. Jones, 67, was charged with approving improper expenditures at the request of his predecessor as CEO, Philip M. Condit, 63.\n\nBoeing Co. fired both men after the company's internal investigation uncovered what prosecutors called "improper and illegal conduct."\n\nProsecutors said that, in addition to Condit, four other Boeing executives and a Chicago interior designer would plead guilty to various charges related to the kickback scheme.\n\nJones and Condit each face up to 10 years in prison and fines of $250,000 on the conspiracy charge. The other defendants face up to five years in prison and $250,000 fines.\n\n'Systemic fraud'\n\nU.S. Attorney James A. Graves Jr. described the alleged conspiracy as "systemic fraud."\n\n"This was a company that had an ethical culture, and we find it deeply disturbing that a company like that could have employees commit such fraudulent acts," he said.\n\nCondit, Boeing's former chief operating officer, said in a statement that he agreed to plead guilty "to the company's disappointment, but to help resolve the situation and put this issue behind us."\n\nA number of the alleged kickbacks involved funds that were earmarked for aircraft engine development, according to the criminal information filed in the case.\n\nBoeing is based in Chicago, but the scheme occurred in St. Louis, which was home to its defense and space unit until 2003, when the company moved it to Washington state.\n\nBoeing spokeswoman Bonnie Rodney said Friday that the company has cooperated with authorities and overhauled its expense approval procedures. She said the company is not aware of any illegal expenses related to the company's government contracts.\n\n'Widespread misconduct'\n\nIn a filing Friday in U.S. District Court in St. Louis, prosecutors said that "certain Boeing employees, including several executives, had conspired to engage in the improper and illegal approval of corporate expenditures."\n\nThe filings said that Boeing officials believed there was "widespread misconduct" that included theft of company funds and illegal personal use of company funds.\n\nIn a "factual resume" filed in court, the government alleged that the executives conspired to authorize company expenses for a variety of items, including theater and concert tickets and interior furnishings for Condit's home, without any business justification.\n\nThe money was funneled through a design company in St. Louis. Prosecutors alleged that about $2.5 million was spent on the house, including $130,000 for a floor-to-ceiling stone fireplace, and $18,000 for a home theater with stadium seating.]" time="0.332"><properties><property name="score" value="0.011305182" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01130518 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01130518
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The mooring cable holding the stricken Rena, which has been stranded on the Astrolabe Reef off the north east coast of New Zealand's North Island since October 5th 2011, is fraying at an "unacceptably rapid rate" and the ship could break up in as little as a week.\n\n\n\nIt could even go as early as Tuesday night, according to New Zealand authorities.\n\n\n\nThey had been expecting the ship to sink, as currents beneath the sea would pull the vessel into the reef, and it would begin to break apart as the tides took it apart. However the "churning" around the ship has actually been slowing the process of the ship disintegrating.\n\n\n\nMeanwhile the crews on board are clearing the decks of the ship, as the removal of the fuel is to begin today, a job which should take a week or two. The removal of the fuel would then free up the mooring cables and allow the ship to break apart and eventually sink.\n\n\n\nHowever if the cable did break, the pieces of the ship could drift away, or worse, float across the Hauraki Gulf and into the Bay of Plenty.\n\n\n\nThe most recent attempt to free the ship from the reef failed, with the bow slipping from the rocky coral. No one has been aboard the ship since a New Zealand Navy ship fired shots at it in January, when the Rena's crew threw their passports over the side.\n\n\n\nThe Chinese-flagged vessel broke free from its tugs in the Bay of Plenty and hit the Astrolabe Reef, spilling 1,700 tons of fuel into the sea. The damage to the reef has been assessed as being very severe.]" time="0.318"><properties><property name="score" value="0.08497965" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08497965 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08497965
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[To help raise awareness of depression and suicide, a group of engineering students from the University of Waterloo have designed a robot that can create artwork with the help of artificial intelligence (AI).\n\nMental illness is a huge problem that often gets ignored, or underplayed. Although the majority of the time you can tell if a person is suffering, there are some cases where it can be harder to identify, especially if you're just talking to them on the phone.\n\nThe team of eight, led by Chris Cui, spent four months designing their robot, which is called DepressionBot.\n\nDepressionBot is now available to help raise awareness of depression and suicide 1:03\n\n"The robot is meant to help raise awareness for depression and suicide," said Cui, a third-year industrial design student, in an interview with CBC's The Morning Edition host Craig Norris.\n\nIt's no secret that mental health issues affect a lot of people, but it's not often that we see people, especially students, take time out of their day to help those affected.\n\n"It's a really personal subject to a lot of people, but there's a lot of stigma around it, so a lot of people don't want to talk about it," said Cui.\n\nSketchbook artwork from DepressionBot. (Submitted by Chris Cui)\n\nGetting the right artwork\n\nIn order to create the artwork, the team taught the robot to look for certain patterns in its black-and-white drawings, then draw similar patterns in its next sketch.\n\n"We had a bunch of example pictures, some]" time="0.319"><properties><property name="score" value="0.71338826" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.71338826 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.71338826
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[To be blunt, the video you linked to does not really prove anything one way or the other. That video is trying to make it seem like some statements made by Dan Abnett about the use of the term "boy" or "son" when applied to the Raven Guard during the Horus Heresy was a form of apologism for using "boyz" when referring to Orks. This is not the case. While it is true that Abnett's statements were inappropriate, the content of that video fails to really show it. For example, where the video claims that Abnett said "Raven Guard don't ever call themselves boys", Abnett was in fact saying that Raven Guard did not ever call themselves "boyz" or any other similar slang. He specifically mentioned "boyz" in the context of Orks as an example, and it is the video that is now misrepresenting his words. In other words, Abnett's statements on the subject of Orks are accurate, and the video's attempt to show him in a negative light is based on a misrepresentation.\n\nAdditionally, your claim that the Imperium is "far from perfect" is not true, as the Imperium's culture is based around the worship of the Emperor, who has deified himself and is often referred to as a god by Imperial citizens. This means that the Imperium has absolutely no separation between religion and government, which means that your claim that the Imperium is "far from perfect" is also a form of apologism, as it is ignoring a key element of the Imperium that should be readily apparent to any Imperial citizen. The use of "Apologetic" is a misuse of the word and also misrepresents what the author is trying to say, as you have misrepresented the claim he is making.\n\nThe author's second "claim" is incorrect on many levels, and is also based on a misrepresentation of facts. Firstly, let's take a look at the quote he links to:\n\n"If we wanted to do a straight-up Space Marines game, we would have done Space Marines, right? They\u2019re the coolest guys."\n\nThis quote is taken out of context. The quote actually goes on to explain why they chose to do the Space Marines as they did. In fact, the quote was in response to a question about why they decided to make Space Marines so "stereotypically heroic" in terms of a tone. The statement that follows in the quote states that it is because Space Marines are the "coolest guys" in the galaxy. What the author is doing here is taking a single quote and presenting it as if it is the entirety of the explanation of why Space Marines are the way they are in this game, when that is not the case.\n\nThe author's next claim is that he does not agree with the statement about the inclusion of certain races, but instead of explaining why he disagrees, he simply says that it is "wrong". This does not actually prove that the statement is incorrect, and is a form of dog-whistle politics, as it is deliberately vague and meant to be interpreted as "political correctness" or "SJW" or "Cultural Marxism" and similar things, all of which are highly charged words. He could very easily have explained why he disagrees with the statement, but he did not. Instead, he chose to attempt to shut down any further discussion of the topic with a rather obscure quote, while also using a misrepresentation of the quote to try and do so.\n\nThe author's final claim is based on another misrepresentation of the source material. In his article, the author linked to an article that states that the developers actually took fan-feedback into account when designing the Space Marine Chapters. In fact, the developers mentioned that they were "watching" the fans' reactions to the game, and were taking note of how the game was received and what fans' concerns were, which is in line with what the developers have said about their reasons for making the Space Marine Chapters they did.\n\nOnce again, the author is trying to use his article as a form of dog-whistle politics, as he is taking these claims and trying to make it seem as if the developers were lying. However, even if the developers were lying about this, which they are not, that does not invalidate the author's argument. In other words, the author's claims that the developers are lying about this are irrelevant to the argument the author is making, and should not be considered when assessing the validity of his arguments.\n\nIn the author's first sentence, he claims that it is "common knowledge" that the Imperium of Man is based on Nazi Germany. However, I do not believe that this is actually true, as I have never heard this before, and the idea seems rather outlandish. In fact, the idea that the Imperium of Man is based on Nazi Germany is so outlandish that it makes me question the author's sanity. Furthermore, his claim is an appeal to emotion, as the author does not really explain why he thinks this, and instead simply uses an emotionally charged accusation.\n\nIn the author's second sentence, he claims that the Space Marine Chapters, as well as the Emperor, are based on "fascist leadership". I have already addressed the author's claim about the Space Marine Chapters, and I will now address his claim about the Emperor. While I cannot speak for the Emperor's actual policies, he is still worshiped as a god by most of the citizens of the Imperium, which does not actually fit with the definition of "fascist leadership". Furthermore, the author does not really explain how he came to the conclusion that the Emperor is based on fascist leadership, and instead simply asserts it without any real explanation.\n\nThe author's third claim is based on a misrepresentation of facts, and is yet another form of dog-whistle politics. His claim that a representation of the logo of the White Legion is on the flag of the Imperium is a misrepresentation of the source material. In the source material, it is explicitly stated that the White Legion and the Imperial flag are two separate things, with the author's claim making it seem as if the White Legion is the official flag of the Imperium of Man. This is, of course, untrue. In fact, the White Legion is not even in the same star system as the Imperium, so the White Legion's flag is actually irrelevant to the argument that the author is making.\n\nThe author's fourth claim is also based on a misrepresentation of facts, as well as yet another form of dog-whistle politics. The author claims that the developers stated that the Imperium is "an alliance between Humans and aliens". While I cannot speak for what the developers actually stated, I can point out that they did not state that the Imperium was an alliance between Humans and aliens. The author's statement that this claim is "common knowledge" is false. In fact, if this was common knowledge, then the author would not have needed to claim that this was what the developers had said. Instead, he would have just cited the developers as having said it. In other words, his claim that this is "common knowledge" is also a form of dog-whistle politics, as it is a claim that is designed to be interpreted as "political correctness" or "SJW" or "Cultural Marxism" and similar things, all of which are highly charged words.\n\nIn the author's final claim, he says that the Orks are portrayed as a generic enemy of the Imperium, when in fact they are a threat to the Imperium. The author claims that "Boyz" is used as an insult by the Imperium, when in fact it is used to refer to any Ork. In other words, his claim that the Imperium is "far from perfect" is incorrect, and in fact is a form of dog-whistle politics.]" time="0.588"><properties><property name="score" value="0.00707266875" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The general consensus in psychology is that intelligence is a singular entity that can be measured and is unchangeable, and that any issues with intelligence will remain constant throughout a person\u2019s life.\n\n\n\nIn general, the accepted view of intelligence is based on a series of experiments carried out in the 1940s and 50s, commonly referred to as the IQ tests. These intelligence tests measured intelligence by identifying patterns and memory, and tested mental agility. But the modern view of intelligence is much broader, and focuses on a person\u2019s ability to learn and their capacity to understand their environment.\n\n\n\nResearch carried out by a group of psychologists in New York have challenged the accepted view, and shown that people\u2019s IQ levels do not necessarily remain the same throughout their lives.\n\n\n\nThey found that if a person has an early traumatic experience, then the level of intelligence is likely to reduce significantly.\n\nThe study\n\nThe study used a database of IQ scores for each person, which was then divided into three groups: people who were not exposed to early trauma, people who had experienced trauma before they were 18 and people who had experienced trauma before they were 16.\n\n\n\nThe study then looked at how the group with early trauma had scored after 16 years. What they found was that people who experienced trauma before the age of 16 scored lower on intelligence tests at the age of 30. Those who experienced trauma before they were 18 scored even lower than those who were traumatized before they were 16.\n\n\n\nThey also found that the difference between the group who experienced trauma and those who did not was three to five points, which is a significant amount.\n\n\n\nThese findings highlight the importance of understanding trauma and how it can affect people throughout their lives. It also shows that traumatic events can influence how a person learns and that this will have a lasting impact on their lives.\n\n\n\nThe other important thing to note from this study is that the effect of trauma was found to last for 20 years. Even though trauma had occurred so early in a person\u2019s]" time="0.309"><properties><property name="score" value="0.37275338" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Unfortunately, in both cases the occupants were intoxicated. The first house we went into was this guy's.\n\n\n\n\n\n\n\n\n\nHere's a look at the bar. The beer fridge was in the shed in the back.\n\n\n\n\n\nWhat's a bachelor pad without a recliner?\n\n\n\n\n\nThe back yard had a trampoline. That's all the beer this guy was going to need for a while.\n\n\n\n\n\nNow we move to the house that had the party. There were lots of people at this house, and not a lot of time to take pictures. However, I did get a few that I think will give you an idea of the festivities.\n\n\n\n\n\nThe Docks!\n\nGood spot for the porta potty.\n\n\n\n\n\nWho's ready to rumble?!\n\n\n\n\n\nThe front lawn!\n\nGolf tournament!\n\n\n\n\n\nWhen all was said and done, we had collected 8 trucks, a garbage truck, and a car from both houses.\n\n\n\n\n\nOh, and no injuries.\n\nThe general area of the party was right next to a creek. There were numerous signs saying how you would be arrested if you went in the creek. Well, as it turns out, there was a reason for those signs.Last year, the creek flooded, and one of the houses nearby was torn from its foundation and carried downstream. This was the home's fate.]" time="0.406"><properties><property name="score" value="0.06788054" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.06788054 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.06788054
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A human being is a part of the whole, called by us "Universe," a part limited in time and space. He experiences himself, his thoughts and feelings as something separated from the rest - a kind of optical delusion of his consciousness. The striving to free oneself from this delusion is the one issue of true religion. Not to nourish the delusion but to try to overcome it is the way to reach the attainable measure of peace of mind.\n\nAlbert Einstein (1938)\n\nWho would have thought that the the famous scientist, whose ideas took a leap of imagination that seemed to defy common sense, had so much wisdom to share.\n\nEinstein's wisdom, delivered in a simple, direct manner, is of a philosophical nature. And yet, as we have seen, his wisdom is based on a scientific perspective, not a philosophical one. It is a perspective that, as we shall see, stands in contrast to the beliefs of the average person.\n\nThe ultimate source of Einstein's wisdom is his sense of awe. He speaks of being in awe of what he observed in nature, as if these observations of nature had moved him to the core of his being. But this awe was not the end of the matter for Einstein. He does not speak of being in awe and then simply stop and say: "What a wondrous world it is." Rather, he looks to this sense of awe as a source of inspiration to do more.\n\nEinstein's wisdom is the result of a personal approach to understanding and the sense of awe that this approach has produced. It is, therefore, both a personal and a shared source of wisdom. The person sharing this wisdom is not speaking on behalf of some outside authority, like a philosopher or a scientist. His wisdom is simply the result of a personal quest, not a more generalized, impersonal, public investigation.\n\nEinstein did not discover his wisdom by himself. He spoke about his awe at the "dignity" of nature, by which he meant that the world of nature is majestic, not cheap. Einstein was aware of the sense of awe that his discoveries had evoked in him and he wished to share this feeling with others. In this way, Einstein's wisdom was, at its roots, a shared resource, because the more people who can feel and express awe at the majesty of nature, the better it is for all of us.\n\nIt is as though Einstein had an innate wisdom that he wished to share with others, and as though he felt compelled to do so. Einstein's quest for wisdom was not an abstract exercise in which he wished to understand nature or the meaning of life. Rather, Einstein was driven by a need to share his insights. As the physicist Stephen Hawking has pointed out, the very nature of the scientific enterprise is a social activity, and this is as true of Einstein as it is of Hawking himself.\n\nLike Hawking, Einstein had the good fortune of being born into a social context that could support his quest for wisdom. He lived in an environment in which he was exposed to an intellectual culture that had been nourished by many philosophers who were also his contemporaries. He could, therefore, both draw from the wisdom of his predecessors and challenge them by articulating the insights that he had achieved.\n\nIn addition, the new physics that he helped to develop has spawned many technologies that have radically transformed our understanding of the world and has introduced new scientific disciplines, such as quantum physics, that have enriched our understanding of nature. Our scientific knowledge has become a shared resource that can be used as a basis for developing a new kind of wisdom, one that does not exist in the history of human thought before the twentieth century.\n\nAs we can see, the search for wisdom and the sharing of wisdom are based on a wide array of factors. To create a context that will allow for the growth of a new kind of wisdom, one that can benefit the common good of humanity, it is necessary to invest in science and in a new philosophical perspective.\n\nIn other words, a new kind of wisdom can only arise as the result of a new synthesis, one that links scientific knowledge with a philosophical perspective. It is this new synthesis that will be explored in the final chapter of this book.]" time="0.433"><properties><property name="score" value="0.3897342" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.3897342 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.3897342
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Onze melkveehouderij\n\nIn 1990, wij waren de oprichters van Lijst Harkema en verhuisden in 2004 naar Aagtekerke, waar de melkveehouderij in het verleden ook zat. Met de komst van de nieuwe melkveehouderij kwamen de melkveehouders van het dorp ook in de gemeenteraad. In 2011 ging het dorp verder met \xe9\xe9n kandidaat, die meteen werd gekozen.\n\nDe voorbije vier jaar, sinds het vertrek van Gert Mulder, heeft Lijst Harkema vier gemeenteraadsleden gehad: Eenmaal Dorine Schrier, daarna Ad van Haren, Peter Nieuwenhuis en uiteindelijk verkozen wij twee van de twee\xebnhalve tonne melkveehouders: Gerrit van der Poel en Marco Beutels. In onze partij Lijst Harkema mogen alle beslissingen eerst goed worden doorgerekend en beoordeeld door deskundigen voordat er ook maar \xe9\xe9n stap wordt gezet. Bij onze melkveehouderij in Aagtekerke is altijd aandacht voor natuurbeheer en het landelijk gebied.\n\nWe werken vanaf een bepaald aantal dieren ook samen met FrieslandCampina. Dit omdat we geen einde hebben aan het gebied waar we melkvee houden, ook al zijn wij de grootste houderij van heel West-Friesland. Het houden van meer dan 600 melkkoeien vraagt bijna dagelijks toezicht. Onze stalen zijn zorgvuldig afgestemd op de huidige voer- en veevo]" time="0.325"><properties><property name="score" value="0.03357078" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Jonathan Chait at New York Magazine says we should start ignoring Donald Trump.\n\nTrump gets endless media coverage, which he then uses to insist he should be treated fairly by the media.\n\nThe fact that Trump is now president makes his demand for fair coverage a valid concern. So Chait\u2019s right that ignoring Trump isn\u2019t the solution.\n\nBut Chait is also wrong that Trump doesn\u2019t deserve any media coverage. He\u2019s just like any other president.\n\nJust not as good at it.\n\nChait notes that Trump uses the press to get out his message:\n\nThe president of the United States is an extremely powerful figure. Even if the entire country agrees that the president of the United States is, in fact, a buffoon who speaks only in unintelligible gibberish, the president of the United States is still very powerful.\n\nChait is correct. Trump may have been a complete loser in the private sector. But in politics, Trump\u2019s clearly been a winner.\n\nThere are many reasons Trump has been a success in politics. Some of these reasons have to do with his political positions. But most of the reasons have to do with his personality.\n\nTrump is the ultimate salesman. He is a chameleon, able to change his tone and style to appeal to his audience. He\u2019s also the consummate bullshit artist, able to make false promises sound plausible.\n\nAnd Trump\u2019s made one of his signature moves since he began his political career. He completely ignores his Democratic opponents and talks directly to his voters. He\u2019s smart enough to understand that his opponents aren\u2019t really interested in actually talking to him.\n\nTrump has always understood how to get his message out, even if the message isn\u2019t all that important. It\u2019s why he never had a detailed health care plan. He wanted to talk to people who agreed with him about how terrible Obamacare was.\n\nHe\u2019s never really been interested in a detailed plan. He\u2019s interested in getting media coverage, because he knows the media will talk about what he says.\n\nTrump is constantly in search of free media coverage. The media gave him endless coverage during the campaign, and he won. And they\u2019re giving him endless coverage now, and he\u2019s still president.\n\nThe problem is that Trump is terrible at getting his message out in an organized and coherent way. He\u2019s also terrible at actually getting anything done.\n\nTrump\u2019s behavior is extremely damaging. But the damage doesn\u2019t come from the fact that he\u2019s in the news. It comes from the fact that he\u2019s so terrible at what he does.\n\nPeople who work for him never know what\u2019s going to come out of his mouth. And they\u2019re never really sure what he\u2019s going to do.\n\nBut his supporters always know where Trump stands. He\u2019s going to get rid of illegal immigrants. He\u2019s going to bring back jobs from overseas. He\u2019s going to put coal miners back to work.\n\nThat\u2019s the message he has for his supporters. And they know that even if his administration doesn\u2019t do what he says, Trump is still fighting for them.\n\nAll presidents have to use the media to get their message out. The difference with Trump is that his message is essentially nonexistent.\n\nTrump isn\u2019t president because he has an interesting policy agenda. He\u2019s president because he knows how to use the media to his advantage.\n\nThat means that we have to talk about him, whether we want to or not.]" time="0.400"><properties><property name="score" value="0.03414018" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03414018 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03414018
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[On the evening of October 23, 2017, the celebrated actor Will Smith hosted an invitation-only event in Las Vegas, hosted by UNICEF to support vulnerable children around the world. During his remarks, Smith reflected on his recent trip to Madagascar, where he met a family who lost their three children to diarrhea. \u201cWhen I say my faith was tested, it was tested. You understand? It was like I was in the Bible.\u201d\n\nSmith is a committed Christian. In 2007, when he was named the most bankable star in Hollywood, Smith made the bold claim that he\u2019s the only top-grossing actor who is a professed Christian. At the time, a study by the Pew Forum on Religion and Public Life found that just 18 percent of Americans consider Hollywood stars to be good role models, and just 10 percent said the same for politicians. \u201cIf the group that you are the leader of is viewed that way, you have to examine what you\u2019re doing.\u201d Smith said.\n\nOn this day, Smith was concerned about children around the world who are not receiving the care they need to survive. As he read about the dire need for vaccines, Smith thought about his own two kids, and how helpless he would feel if they were sick and dying. \u201cI can\u2019t imagine what that must be like. So for me, the easiest thing to do is to support UNICEF. Because when my children get sick, it\u2019s my job to get them help, and if they die, they die. I\u2019m not gonna stop that. I\u2019m not God. But when children around the world get sick and die, it\u2019s God\u2019s responsibility. And I have to believe that God will ask him, \u2018Are you there?\u2019 And when He says, \u2018Yes, I\u2019m there,\u2019 he\u2019ll say, \u2018Are you there?\u2019 And he\u2019ll say, \u2018I\u2019m there,\u2019 and God will say, \u2018Well, why didn\u2019t you help these children?'\u201d\n\nIn one year, UNICEF vaccinates 46 million children against preventable diseases. Every dollar invested in immunization results in $44 saved in treatment. UNICEF reaches children in 190 countries and territories. Each year, with the help of its many partners, UNICEF supplies more than 50 million children under the age of five with immunizations against the six life-threatening diseases: pneumonia, tuberculosis, diarrhea, polio, measles, and tetanus. UNICEF also supports the vaccination of pregnant women in countries where the practice has been shown to prevent transmission of vaccine-preventable diseases to newborns. In addition, UNICEF is the largest distributor of antiretroviral medicines for children and pregnant women with HIV in the developing world.\n\nUNICEF also provides thousands of training opportunities for community health workers to deliver health services to children in their own communities. UNICEF, through its extensive network of child protection partners, also provides psychological support and counselling for children and adolescents affected by violence, abuse and exploitation. For millions of children who would otherwise die, it is UNICEF that saves lives.\n\nIn response to the global refugee crisis, UNICEF is at the forefront of emergency response efforts to help children and families who are fleeing conflict and violence. The agency has distributed more than 1 million emergency packages in Syria, Iraq, Lebanon and Jordan, and has provided over 1.5 million people with emergency supplies including tents, kitchen sets, heaters and sleeping mats. UNICEF has established 41 child-friendly spaces for traumatized children in the region and continues to provide medical and psychosocial support, protection and assistance for refugees.\n\nIn 2016, UNICEF\u2019s commitment to the protection of children in conflict was formally recognized with the Nobel Peace Prize. The Nobel Prize was awarded to UNICEF \u201cfor its work for children in developing countries, and for long-standing advocacy in favor of children\u2019s rights.\u201d\n\nThe U.S. and UNICEF first partnered in 1953, to help children devastated by the Korean War. From that time, their relationship has strengthened. In fiscal year 2015, the U.S. government provided UNICEF with more than $77 million to support its humanitarian efforts. UNICEF also works with the U.S. government on a number of global health initiatives. These include ensuring that every child is fully immunized and preventing HIV transmission from mother to child. UNICEF also works with the U.S. government on the President\u2019s Emergency Plan for AIDS Relief (PEPFAR).\n\nThrough PEPFAR, the U.S. government has invested more than $80 billion to combat global HIV/AIDS since 2003. PEPFAR is a cornerstone of U.S. global health efforts, and it is the largest commitment by any nation to combat a single disease. The program provides 11 million people in over 50 countries with lifesaving antiretroviral treatment, and has contributed to a 40 percent decline in AIDS-related deaths since 2004. In fiscal year 2017, the U.S. contributed $4.2 billion to PEPFAR.\n\nChildren born with HIV and AIDS in Africa, including those living in remote rural areas, can now receive treatment. PEPFAR is working to ensure that every child is tested, identified, and started on treatment. New initiatives are also helping to treat HIV-positive mothers and prevent them from passing the virus on to their unborn children.\n\nIn the five years since the Global Health Security Agenda (GHSA) was launched, more than 40 countries have invested in the development of a National Emergency and Medical Preparedness and Response Plan. To date, more than 15 countries have published plans. In 2016, the GHSA received a boost when the U.S. committed to invest $1.3 billion through 2020. This funding will support the purchase of 50 million doses of vaccines to help save lives from infectious diseases like]" time="0.861"><properties><property name="score" value="0.0074883269999999995" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00748833 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00748833
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[2017.01.15. Szerz\u0151: Kir\xe1ly Zolt\xe1n\n\nAz elm\xfalt id\u0151szakban t\xf6bbsz\xf6r is m\xe1r t\xe9m\xe1t tett\xfcnk a honlapra, amelyekben a kiv\xe1ndorl\xe1s \xe9s a bev\xe1ndorl\xe1s probl\xe9m\xe1j\xe1r\xf3l, valamint a bev\xe1ndorl\xe1s befektet\xe9si lehet\u0151s\xe9geir\u0151l besz\xe9lt\xfcnk. Az itt szerepl\u0151 \xedr\xe1sokat mindenkit arra k\xe9rj\xfck, hogy ismertesse aj\xe1nl\xe1sainkat, s\u0151t: k\xf6zrem\u0171k\xf6dj\xf6n vel\xfck, ha \xe9s amennyiben kedve tartja. Hogy v\xe9g\xfcl ez az egy kicsit kev\xe9sb\xe9 szeml\xe9letes le\xedr\xe1s is az id\u0151szakon \xe1ttekinthet\u0151 legyen, t\xe9m\xe1nk megoszt\xe1s\xe1val, szeretn\xe9nk sz\xednesebb\xe9 tenni azt.\n\nBev\xe1ndorl\xe1s k\xfclf\xf6ld\xf6n: jelentkez\xe9s az online k\xe9pz\xe9sekre!\n\nEz a k\xf6zel-keleti sz\xe1rmaz\xe1s\xfa konzul bejelent\xe9se, hogy magyar diplom\xe1val is lehet amerikai \xe1llampolg\xe1r. Persze ez csak amolyan k\xf6lts\xe9ges tan\xfas\xedtv\xe1ny, amivel t\xf6bbek k\xf6z\xf6tt az amerikaiakn\xe1l \xe9s a sk\xf3t f\xfcggetlens\xe9gi referendumn\xe9l is seg\xedtette ezt az orsz\xe1got. Nem akarunk err\u0151l semmit el\xe1rulni, mert igen sokan csak ezzel a k\xfcl\xf6nleges diplom\xe1val mentek t\xf6megesen az USA-ba. Szerint\xfcnk ezt a t\xe9m\xe1t egy kicsit megk\xf6nnyebb\xfclj\xfck, ha leiratjuk a \u201eRe: \xc9rdekl\u0151d\xe9s angol nyelv\u0171 m\u0171szaki k\xe9pz\xe9s\xe9re\u201d \xe9s \u201eRe: F\xf3kuszt\xe1bor aul\xe1s k\xe9pz\xe9s, IAS vagy EC\u201d feliratokat is. Ugyanis a bev\xe1ndorl\xe1s nyitott k\xe9rd\xe9s, nyilv\xe1n nem tudni, hogy megmaradhat-e a hazai di\xe1kvizsga, vagy azt is el kell-e engedni, amihez a hatalom t\xf6bb k\xf6zt k\xe9pes \xe9s akar is. \xdagy t\u0171nik teh\xe1t, hogy az elm\xfalt id\u0151szakban nem ez a t\xe9ma kapta el a f\u0151sodor f\xf6l\xe9ny\xe9t, hanem ink\xe1bb az, hogy a diplom\xe1kat haszn\xe1lva bev\xe1ndorl\xe1sra k\xe9sz\xfclnek, mert szeretn\xe9k k\xfclf\xf6ld\xf6n folytatni tanulm\xe1nyaikat.\n\nDe mi\xe9rt is t\xf6rt\xe9nne ennyire sz\xe9lesk\xf6r\u0171 bev\xe1ndorl\xe1s, ami a diplom\xe1t kap\xf3k sz\xe1m\xe1t is mag\xe1ba foglalja? Mert a diplom\xe1val rendelkez\u0151k ugyan egyre kevesebben vannak, m\xe9gis akad b\u0151ven olyan, aki tud \xe9s ak\xe1r \xf6r\xf6m is a tanul\xe1s, a munka, de legal\xe1bbis a k\xfclf\xf6ldi \xfat. Ugyanis nemcsak a magyar fels\u0151oktat\xe1s gondot szenvedett, hogy az elm\xfalt h\xfasz \xe9vben az egyre k\xe9pzettebb munkaer\u0151 l\xe9tsz\xe1m egyre cs\xf6kkent, hanem m\xe9g a diplom\xe1val is rendelkez\u0151k sz\xe1ma is egyre kisebb. Az emberek sz\xe1m\xe1ra a k\xfclf\xf6ldi p\xe1ly\xe1zatokat is n\xe9zve, igazolni tudom, hogy nincs egy\xe1ltal\xe1n olyan k\xe9pz\xe9s, amelynek ne lenne r\xe9szben- vagy teljesen online k\xe9pz\xe9se is. Ugyanis a mai informatika, oktat\xe1s \xe9s kult\xfara nagyon nagy szerepet kap a dolgokban, ez\xe9rt \xe9rdemes elgondolkodni azon, hogy nem kell k\xe9nytelen vagy b\xe1rmi okb\xf3l kiszolg\xe1ltatott \xe1llapotban v\xe9gezni az oktat\xe1st.\n\nAz online k\xe9pz\xe9sek jelentik az \xfajat, amit ma a diplom\xe1val rendelkez\u0151k a legnagyobb ar\xe1nyban vesznek ig\xe9nybe, \xe9s szerintem nem is egy rossz d\xf6nt\xe9s, ha valaki le is teszi az online k\xe9pz\xe9st. Ami m\xe9g \xe9rdekesebb az eg\xe9szben, az az, hogy nem csak a bev\xe1ndorl\xe1sra k\xe9sz\xfclnek az online k\xe9pz\xe9sek seg\xedts\xe9g\xe9vel. Val\xf3j\xe1ban m\xe9g a saj\xe1t orsz\xe1gunkban is egyre t\xf6bb jelentkez\u0151 van olyan online k\xe9pz\xe9sekre, amelyekkel m\xe1s orsz\xe1gokban t\xf6megesen jelentkeznek. Ez teh\xe1t el\u0151ny \xe9s h\xe1tr\xe1ny is egyben, de szerint\xfcnk a legt\xf6bben ink\xe1bb a jelentkez\xe9s k\xf6vetkezt\xe9ben a szerencs\xe9j\xfckre vannak. De hogy mi a jelentkez\xe9s eredm\xe9nye? Kiv\xe1ndorl\xe1s vagy bev\xe1ndorl\xe1s, de a legt\xf6bb helyen egyel\u0151re m\xe9g azt sem lehet tudni, hogy van-e lehet\u0151s\xe9g a bev\xe1ndorl\xe1sra, vagy sem. De a fenti c\xedmen \xe9rdemes bejelentkezni, \xe9s ut\xe1naj\xe1rni, hogy van-e itt online k\xe9pz\xe9s. K\xe9rj\xfck, hogy t\xf6bbsz\xf6r is ut\xe1naj\xe1rjon, mert a keres\xe9s egy m\xe1sik c\xedmre is el\xe9rhet\u0151, \xe9s egy j\xf3 okos program lehet\u0151v\xe9 teszi azt, hogy az eredm\xe9nyek szeml\xe9ltet\xe9se legyen a lehet\u0151 legjobb.\n\nA magyar diplom\xe1val is lehet amerikai \xe1llampolg\xe1r?\n\nA t\xe9m\xe1t komolyan vegy]" time="0.468"><properties><property name="score" value="2.709273" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.709273 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.709273
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Twitter is the perfect platform to get the word out there about anything you are trying to promote. I am a huge fan of using Twitter as a marketing tool, even more than Facebook. It\u2019s a great way to network and reach out to people who are interested in what you have to offer. Here is my list of 10 tips to help you promote anything you are selling on Twitter:\n\n1. Use Hashtags\n\nI love using hashtags on Twitter. They help to promote the things you are interested in and create a sense of community within a group. I will admit that it can be hard to remember hashtags to use for all the things you promote. One way I suggest to overcome this is to put your hashtags in a Twitter search to make sure they are not already being used. This will save you some time and help you avoid any issues down the road.\n\n2. Retweet\n\nIf you like a tweet, retweet it! I\u2019m sure most people are familiar with the concept of retweeting, but I just wanted to put it out there to make sure it was stated. Retweeting is a great way to share the things you like, and can be a great way to show your audience that you are involved in the social media community and help them feel more comfortable doing business with you.\n\n3. Mention\n\nMentioning someone on Twitter is a great way to show your audience that you are engaged and want to interact with them. It is important to mention other people within your field of interest in order to show your audience that you are well connected. I always make sure to mention people who have liked or retweeted my stuff as well. It makes me feel good when I get a mention and it shows that the people I engage with are interested in what I have to say.\n\n4. Post About Your Daily Life\n\nThere is nothing wrong with posting about your daily life and about other stuff you like. I\u2019m sure you all know about the Twitter feeds that are all business. I don\u2019t like following people like that because I feel like it takes away from the idea of the social aspect of Twitter. By being a person and talking about your life, you can show your audience that you are a real person and are interested in other people\u2019s lives as well. I\u2019m sure you have seen some tweets about people\u2019s lives that you thought were really cool, and the people that posted those tweets have engaged you because of it.\n\n5. Be Social\n\nDon\u2019t forget to be social. I\u2019m sure that when you first started out you didn\u2019t know what to do on Twitter. My suggestion to you is to find some people who are interested in the things you are and start a conversation. You will see that the conversations that start on Twitter are real and can be interesting. One of my favorite things to do on Twitter is to start conversations with people. It gives me the chance to learn from other people and also helps them learn about me.\n\n6. Use Pictures\n\nI love using pictures on Twitter. I know a lot of people like to include pictures when they post about things, and I would like to suggest that you do so as well. Including a picture with your tweet can get you more retweets and likes, and can really help to boost the effectiveness of your post. I like to use pictures from Instagram with my tweets, but you can really use any picture. If you want to make a picture of yourself that has an impact on your audience, I would suggest using a tool like Socialbakers.\n\n7. Use Hashtags That Make Sense\n\nI\u2019ve touched on this before, but I want to emphasize it again. It is important to make sure that you are using hashtags that make sense. You don\u2019t want to hashtag your tweets with irrelevant hashtags just to get a retweet or a like. You also don\u2019t want to make hashtags that are too long. I would suggest keeping your hashtags short and relevant.\n\n8. Direct Message\n\nThere are times when a DM is more appropriate than a tweet. You will be surprised at how many people DM you. I think a lot of people just use it to ask questions, but you can also use it to network. I think a lot of people don\u2019t use DMs because they don\u2019t think their audience will see it. If you are going to send a DM, make sure it is personal. Send it to someone who is following you. It\u2019s a lot less likely that they will check the people they follow to see who is sending them a DM, so if you DM a person that is following you, they are much more likely to respond.\n\n9. Use Images\n\nI want to encourage you to use images with your tweets. Images are the first thing people look at, so you want to make sure that you are using good images. One thing I like to do is to include images with my tweets. I\u2019m sure you have seen a lot of Twitter profiles that do this. It helps to keep your tweets interesting and make your tweets more unique.\n\n10. Be You\n\nThis last one is really important. You want to be yourself on Twitter. The more genuine you are, the better. People can see through a fake personality. You want to engage with your audience and show them who you are. When they see you as a real person, it will help to build a more trusting relationship between you and your audience.\n\nThere you have it! I hope these tips help you to improve your Twitter account and that your business gets better because of it. I always love getting comments from you all, so if you have any more suggestions or questions, feel free to drop me a comment below.]" time="2.002"><properties><property name="score" value="1.6062725555000001" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.60627256 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.60627256
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Check out the info below for future tour dates, and track them to receive alerts when they tour near you\n\n"The one and only" as his legions of fans call him, John Lydon is the only original member of the world's most celebrated punk band, PiL.\n\n\n\n'All the very best, Johnny Rotten!' The Independent\n\n\n\n'It was awesome!' The Guardian\n\n\n\n'He's got some music to make, let him do his job' Mojo\n\n\n\n'The People's Punk. Still Rotten after all these years' Sunday Times\n\nJohn Lydon John Joseph Lydon (born 31 January 1956), also known by his former stage name Johnny Rotten, is an English singer, songwriter, and musician. He is best known as the lead singer of the punk rock band the Sex Pistols, which lasted from 1975 to 1978, and again for various revivals during the 1990s and 2000s. He is also the lead singer of post-punk band Public Image Ltd, which he founded and fronted from 1978 until 1993, and again since 2009.\n\n\n\nLydon's musical career has spanned over four decades. As a musician, he has also been a member of several bands: PiL (1978\u20131992, 2009\u2013present), the Flowers of Romance (1978), the Joneses (1979), and the Nightingales (1979\u20131980). Since 2013, he has put his PiL bandmates on hiatus to focus on his new band, the Public Image Ltd band. He has also hosted a weekly radio show on BBC Radio 6 Music, Rotten Radio.\n\nJohn Lydon tour dates]" time="0.625"><properties><property name="score" value="1.2849895" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Ultimate One Night Stand in the Square\n\nChapter 1: Proposal\n\nAs a bridesmaid, you're required to do a number of things that I'd never consider doing voluntarily. First of all, you're expected to wear a hideous dress that you've never worn before. Second, you're required to spend your evening catering to everyone else, acting as the host of the event. Most importantly, however, you're required to smile a lot and appear happy.\n\nAt the wedding I attended, everyone was happy, especially the bride and groom. I was happy for them, but I wasn't the happiest bridesmaid in the crowd. In fact, I was the exact opposite.\n\nWhy was I so unhappy? I wasn't the one getting married; I was the maid of honor. I was so annoyed that I was even standing up for my ex. We'd broken up last month because I thought he was cheating on me with a blonde bimbo named Summer. I was at the wedding because my best friend Alicia insisted that I go, but if she knew how much I hated the groom, she would have probably asked me not to go at all.\n\nAnyway, this was the part of the wedding that was pissing me off: the proposal. I was trying my hardest to hold back my tears, but I was failing. I didn't love him anymore, and I never would again.\n\nI glanced over at my ex-boyfriend, Blake. He was really handsome, but that's not what was important right now. He was going down on one knee and was about to propose to the most beautiful girl I'd ever seen.\n\n"Andi, will you marry me?"\n\nI cringed. He'd asked me the same question about ten times, but I was too busy being angry at him to remember. This time was different, however, because he was now asking the blonde bimbo he was sleeping with.\n\n"Yes," she said, finally accepting the proposal.\n\nAs soon as he slid the ring on her finger, everyone in the room erupted into cheers. I just stood there, my mouth wide open, in complete shock.\n\n"Yes, that's my girl," said Blake, "And now she's my fianc\xe9e!"\n\nAs they walked out of the church and into the limo, Blake leaned over and kissed her cheek. A couple seconds later, I lost it.\n\n"Bastard," I muttered. "Bastard."\n\n"Andrea?" said Alicia.\n\n"He just asked that whore to marry him," I said. "It was my turn. I was the one who should have been there. I'm the one who was supposed to marry him!"\n\n"Yeah, well I know that," she said, rolling her eyes. "But it's over now. You just have to be a big girl and accept it."\n\n"He doesn't love her," I said, "I know it. He was with her while he was with me, remember?"\n\n"Andi, I hate to say this, but it's too late now," she said. "He's getting married. You can't do anything about it."\n\n"I could show up at the wedding," I said, "and say that I'm his girlfriend and I'm pregnant."\n\n"Andi, that's insane," she said. "You know it's not your baby. You're going to destroy his wedding day if you pull something like that."\n\n"That's the point," I said. "I want him to feel the way I feel. I want him to feel miserable for a change."\n\n"Look," she said, "I'll go with you, but you can't tell Blake anything. If you do, you're going to be the biggest loser in the room, and you're going to lose your best friend."\n\nI hesitated. I knew she was right. If I ruined the wedding, I'd be in a lot of trouble.\n\n"Fine," I said. "I won't tell him anything."\n\nA few days later, I arrived at the church. The doors were open, so I wandered in. The church was completely empty, which made it look a lot bigger. I could hear some talking coming from the altar, so I walked in that direction. The first person I saw was Blake, wearing a brand new suit and looking like the happiest man on the planet.\n\n"You look so beautiful," he said to the blonde bimbo who stood next to him.\n\nI thought I would be furious when I saw her, but I wasn't. I was heartbroken and sad, but I didn't hate her. In fact, I didn't feel anything towards her. I was just jealous, and the sight of her made me remember how much I'd wanted to marry Blake myself.\n\nI walked up the aisle, ignoring the fact that I was completely alone. I sat down in the front row, and began to think about what had happened.\n\n"How did it happen?" I said to myself. "Why did we break up?"\n\nI knew that I loved him, but I was certain he didn't love me. My best friend Alicia and I had discussed it, and she agreed with me. She was convinced that Blake was cheating on me with a blonde bimbo named Summer, but I wasn't convinced.\n\n"It can't be her," I said. "How did he meet her? Where did they meet?"\n\nJust then, a woman walked up to the front of the church. She was dressed in a black robe, and she had short, black hair.\n\n"Are you Andrea?" she asked.\n\n"Yes," I said.\n\n"I'm sorry," she said, "but the wedding has been cancelled."\n\n"What do you mean?" I asked.\n\n"Blake is getting married in Las Vegas," she said.\n\n"But I'm his fianc\xe9e," I said, "And I'm supposed to be here."\n\n"You were never his fianc\xe9e," she said. "The bimbo, Summer, is the one he's getting married to."\n\n"I'm sorry," I said. "I don't understand."\n\n"Neither do I," she said, "but I was supposed to tell you the wedding was cancelled. So, that's what I'm doing. Sorry for ruining your night."\n\n"It's okay," I said. "It's not your fault."\n\nI knew I had to get out of there. I could barely stand being there as it was, so I hurried out the door. I walked down the sidewalk, not knowing where I was going. I had no idea what to do next.\n\n"Hey," said a voice behind me.\n\nI turned around and saw Blake running towards me.\n\n"You were supposed to be at the wedding," he said. "Where have you been?"\n\n"I'm not going to lie to you," I said. "I'm really hurt, and I don't want to be in your wedding. I'm just here because your father paid for the wedding."\n\n"You don't understand," he said. "We're getting married in Las Vegas tonight."\n\n"Really?" I said.\n\n"Andi, we've got to go," he said, "it's going to start any second."\n\nI took one look at his face, and I knew that he was telling the truth. I felt the tears well up in my eyes.\n\n"So, this is it?" I said. "You're really getting married?"\n\n"Andi, I'm sorry," he said. "I didn't know how to tell you. My father forced me into this, and I couldn't say no. If I had it my way, you'd be my wife right now. But this is the way it has to be."\n\nI felt a tear escape my eye, and I quickly wiped it away.\n\n"You look beautiful," he said.\n\n"I'm not going," I]" time="0.966"><properties><property name="score" value="0.041695569" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[4.25 stars - Review by Trisha\n\n\n\nIn my experience, most male-on-male romance books are really hot and steamy but the storyline is lacking, but this one definitely surpassed my expectations. This book wasn't hot and steamy. Not even a little bit. There was one sexy scene between Jay and Davey but that was about it. But it was such a great story. The storyline kept me interested the whole time and I was really rooting for them to have their happily ever after.\n\n\n\nDavey just recently moved from Ireland to get away from his family and the drama that comes with them. He loves working at a video game store and is really happy there. He has a steady boyfriend but that doesn't mean that Davey is 100% out of the closet. Jay is his friend from work but Davey doesn't know that Jay is in love with him.\n\n\n\nJay is totally in love with his best friend Davey. He thinks that Davey is perfect but he can tell that Davey is hiding something. Davey has a hard time trusting people and Jay doesn't know why. But Jay can tell that Davey is hiding something so he just decides to wait it out until Davey is ready to tell him. He's hoping that one day, Davey will realize that Jay is in love with him and he will finally be able to be with the man he loves.\n\n\n\nI really liked the characters. I felt really bad for Davey and how his family was treating him. I also really liked Jay. He was such a great guy. He was just really honest about his feelings for Davey. And I loved that about him.\n\n\n\nIt was a really great story. I loved the characters, I loved the storyline, and I was really rooting for these two to be together.]" time="0.392"><properties><property name="score" value="0.021897893" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[La ministre f\xe9d\xe9rale de la Sant\xe9, Maggie De Block (Open VLD), n'entend pas se mettre \xe0 genoux devant les r\xe9clamations de ceux qui r\xe9clament un d\xe9remboursement du soin m\xe9dical de base. "J'entends les gens, mais je pense qu'il faut se tourner vers d'autres solutions", explique-t-elle au soir de l'anniversaire de la prise du pouvoir par le nouveau gouvernement de coalition f\xe9d\xe9ral. "Je vais en d\xe9battre avec les partenaires sociaux, dans la soci\xe9t\xe9 civile, avec les \xe9lus r\xe9gionaux et les \xe9lus locaux", ajoute-t-elle.\n\nLes chiffres sont l\xe0. Selon les calculs de la Drees, le co\xfbt du maintien du syst\xe8me de soin de base en Belgique est de 2,8 milliards d'euros par an. Une somme qui n'est pas forc\xe9ment optimale dans un contexte budg\xe9taire tendu. En 2014, par exemple, des remboursements aussi massifs ont provoqu\xe9 un manque \xe0 gagner de 1,1 milliard d'euros pour le gouvernement f\xe9d\xe9ral. Un d\xe9ficit qui s'ajoute au budget annuel d'environ 21,5 milliards d'euros de la sant\xe9 publique.\n\nLa ministre se montre prudente, parce qu'il ne faut pas se tromper de combat. Il ne s'agit pas de r\xe9former le syst\xe8me de soins de base pour une raison financi\xe8re, mais pour l'am\xe9liorer, pr\xe9cise-t-elle. "Je ne suis pas pour le d\xe9remboursement de la m\xe9decine de base, mais je veux prendre un nouveau d\xe9part, et que tout le monde y trouve son compte", ajoute-t-elle.\n\nMaggie De Block a d'ailleurs entam\xe9 une s\xe9rie de consultations, avant de rendre son rapport final. A ses yeux, le "temps de l'improvisation est pass\xe9", car les gens attendent des r\xe9sultats concrets. Le gouvernement lib\xe9ral flamand et le PS, ainsi que des institutions nationales, mais aussi internationales, auront leur mot \xe0 dire dans ce d\xe9bat.]" time="0.488"><properties><property name="score" value="0.047618587" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Top Rank Inc. has signed welterweight contender Rod Salka to an exclusive promotional agreement, Top Rank president Todd duBoef told ESPN.com on Tuesday.\n\nSalka, 29, will fight on the undercard of the Timothy Bradley-Juan Manuel Marquez pay-per-view main event on Oct. 12 at the Thomas & Mack Center in Las Vegas.\n\nSalka, a former featherweight and super featherweight, will face Jorge Pimentel (23-4, 18 KOs), 32, of the Dominican Republic, in a scheduled 10-round welterweight fight. The card will be televised by HBO.\n\n"I've signed with Top Rank and will be fighting in Las Vegas on Oct. 12," Salka said. "I'm very excited about this opportunity. This is a great chance for me to go against one of the biggest names in boxing. I'm so thankful for the support that I've received from my family, friends and fans."\n\nSalka, who lives in Pittsburgh, is 23-3 with 13 knockouts and has not fought since July 31, 2011, when he lost a 12-round unanimous decision to Danny Garcia on the undercard of the Amir Khan-Zab Judah card at Mandalay Bay in Las Vegas.]" time="0.418"><properties><property name="score" value="1.4081304" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Adrian School District is dedicated to providing the best possible learning environment for all students. This school district is composed of approximately 5,000 students in grades K-12 and 125 full-time and part-time teachers.\n\nAdrian is a town of approximately 16,000 people, located in southwest Michigan. Adrian is best known for its variety of community events, from festivals and parades to musical concerts. A new football stadium opened in 2015, and other athletic facilities are planned for the future.\n\nSince 1873, the Adrian School District has been dedicated to providing students with the best education possible.\n\nAdrian Schools is one of the three districts within the Jackson-Adrian Area Schools, which includes Jackson and Adrian. This collaboration allows our students to take advantage of an excellent education and opportunities for athletic competition in a small, personal community.\n\nWe are very proud of our students and staff and are very excited about the future of our district.\n\n- Chris Hettinger\n\nSuperintendent]" time="0.342"><properties><property name="score" value="0.13460664" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[fot. J\u0119drzej Skiba\n\nWizualna uczta dla wielbicieli Harry\u2019ego Pottera. Ju\u017c niebawem w Olsztynie!\n\nZdj\u0119cia z filmu zrealizowane przez Alfonso Cuar\xf3na, do kt\xf3rego graj\u0105 gwiazdy jak Daniel Radcliffe czy Emma Watson, zapowiadaj\u0105 si\u0119 niezwykle okaza\u0142e. Zaanga\u017cowanie mieszka\u0144c\xf3w, \u015bwiat\u0142o, charakterystyczne elementy miasta b\u0119d\u0105 w tym filmie cz\u0119\u015bci\u0105 wizualnej uczty dla ka\u017cdego fanu Harry\u2019ego Pottera.\n\nPlanowana dat\u0105 startu projektu jest pa\u017adziernik 2019 roku. Projekt b\u0119dzie realizowany przez Filmowy Ob\xf3z Gier, Wsp\xf3\u0142pracuj\u0105cych ze Stacj\u0105 Filmoznawcz\u0105 im. Andrzeja Wajdy i Stowarzyszenie Pomocy Inicjatywom Kulturalnym Miasta Olsztyna.\n\n- Miejscem realizacji filmu b\u0119dzie miasto Olsztyn, zar\xf3wno star\xf3wka, jak i inne cz\u0119\u015bci miasta, a prawdopodobnie tak\u017ce same Podlasie. Trudno jednoznacznie wskaza\u0107 przeznaczone obszary, gdy\u017c pozyskamy najlepsze miejsca do filmowania. W pobli\u017cu rzek, na szlakach turystycznych, w zabytkowych okoliczno\u015bciach, w obiektach, kt\xf3re by\u0142yby dost\u0119pne dla produkcji, przy budynkach kulturalnych, w wojskowych obiektach - m\xf3wi Mariusz \u0141azicki, prezes Filmowego Obozu Gier.\n\nTymczasem pocz\u0105tek pracy tw\xf3rc\xf3w zaplanowany jest na 21 wrze\u015bnia w Centrum Kultury w Olsztynie. Wej\u015bcie na teren projektu jest bezp\u0142atne, a pierwsze pr\xf3by rozpocznie si\u0119 w pa\u017adzierniku, r\xf3wnolegle z realizacj\u0105 obiektu.\n\nPodczas wyprawy filmowc\xf3w po Europie, prac\u0119 tw\xf3rc\xf3w poprowadzi ameryka\u0144ski re\u017cyser.\n\nW\u015br\xf3d uczestnik\xf3w b\u0119dzie mia\u0142a r\xf3wnie\u017c swoje miejsce Olszty\u0144ska Fabryka Form Filmowych - eksperymentalna scenografia - najwi\u0119kszy tego typu obiekt w Europie.\n\n- Ten nowy obszar pracy filmowej przejdzie gruntown\u0105 renowacj\u0119, w tym nowa przepustowo\u015b\u0107 dla t\u0142umu widz\xf3w. Olsztyn i teren przy Fabryce Form Filmowych wyr\xf3\u017cniaj\u0105 si\u0119 na tle innych miast w Polsce, ale i w Europie. Dzisiaj ju\u017c niebawem mo\u017cemy wystawi\u0107 szyld w kraju i na \u015bwiecie - m\xf3wi \u0141azicki.\n\nOd 2008 roku, czyli od czasu pojawienia si\u0119 pierwszych prac re\u017cyserskich w tym miejscu, powstaje kilkana\u015bcie prac, dzi\u0119ki czemu ma miejsce w Europie, wykorzystywane na potrzeby filmowe i komercyjne.\n\nObecnie w przysz\u0142ym roku zaplanowana jest realizacja kolejnego filmu o losach czarodziejki, gdzie Olsztyn b\u0119dzie g\u0142\xf3wnym miejscem akcji.\n\n- Jedna z produkcji ma za zadanie pokaza\u0107 mieszka\u0144com miasta, a za po\u015brednictwem filmu z ca\u0142ego \u015bwiata, jak Olsztyn zosta\u0142 wybrany do filmowania. W przysz\u0142o\u015bci obiekt wykorzystany jest do realizacji dalszych produkcji z unikalnym potencja\u0142em. Takie miejsce ma szans\u0119 powsta\u0107 tylko raz na kontynencie - podsumowuje prezes.\n\nW przysz\u0142o\u015bci, w obiekcie b\u0119d\u0105 realizowane kolejne filmy, nie tylko te komercyjne.\n\n- Konsekwencj\u0105 pojawienia si\u0119 Fabryki Form Filmowych, jest potrzeba dalszej rozbudowy obiektu. Tw\xf3rcy nie zapomn\u0105 o Olsztynie. Chc\u0105, aby fabryka sta\u0142a si\u0119 pr\u0119\u017cnie dzia\u0142aj\u0105c\u0105 wydarzeniem kulturalnym i edukacyjnym, daj\u0105cym prac\u0119 tysi\u0105com ludzi w Polsce. Jak i te\u017c nie zapominaj\u0105, \u017ce fabryka powsta\u0142a dzi\u0119ki Polakom, kt\xf3rzy dzia\u0142ali w tym miejscu pod nazw\u0105 Fabryka Filmowa "Kolor" - m\xf3wi prezes.]" time="0.467"><properties><property name="score" value="0.018147314" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Share Tweet Email Copy Link Copied\n\nTimeless creator Eric Kripke wants a season 4 to resolve the show's cliffhanger ending.\n\nThe time-travel series, starring Abigail Spencer, Matt Lanter, Malcolm Barrett and Goran Visnjic, was canceled after two seasons on NBC. However, after a last-minute bid from Sony Pictures Television, it was ordered to a special two-part finale. The shows were meant to resolve the cliffhanger, and answer why Rufus was shot and where Lucy and Wyatt ended up. However, when the episode aired, nothing was resolved.\n\nRelated: Timeless Fits Perfectly Into The Revival TV Movement\n\nIn an interview with Syfy Wire, Kripke revealed he's hoping for a season 4 so that the show can get a proper ending.\n\n"We always conceived of [the finale] as a potential series finale, because we couldn\u2019t get canceled! So that\u2019s just what it ended up being. It\u2019s like, \u201cOK, we can\u2019t end the show, so let\u2019s end the arc.\u201d It felt really appropriate and full circle, and everybody at NBC, Sony and Warner Bros. was like, \u201cThat\u2019s a perfect place to end this.\u201d We\u2019re not ruling out a future for the show. Who knows? We still feel passionately about it. Maybe there will be a season 4. I think everyone at the studio and the network felt really good about where it ended.\u201d\n\nIf]" time="0.384"><properties><property name="score" value="0.0068742163" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00687422 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00687422
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Arnold R\xfc\xfctel\n\nArnold R\xfc\xfctel (born 3 April 1937) is an Estonian politician who was the third President of Estonia from 2001 to 2006. He was born in Rakvere, L\xe4\xe4ne-Viru County. He served as the Mayor of Tallinn from 1992 to 2001 and was the Speaker of the National Assembly from 1999 to 2001.\n\nR\xfc\xfctel served as a Colonel in the Soviet Air Defence Forces from 1967 to 1992. He joined the pro-independence party "Vaba Eesti" (Free Estonia) in 1988.\n\nIn the last Soviet-era election of the Supreme Soviet of the Estonian SSR, held on 17 March 1990, R\xfc\xfctel was elected to the parliament, representing the Tallinn constituency. On 20 August 1991, he was one of the speakers at the Congress of Estonia, which proclaimed independence. He was elected to the new Riigikogu (Parliament) on 18 September 1991, and became Minister of Foreign Affairs in the government of Mart Laar.\n\nR\xfc\xfctel joined the conservative Pro Patria Union party in 1993 and was elected chairman in 1996. He ran for president in 1999 and came in second to Arnold R\xfc\xfctel. He became a member of the Riigikogu again in 2003, this time for the Reform Party. R\xfc\xfctel is considered to be a pro-Western politician and a leading proponent of Estonia's membership of NATO. In February 2004, he was the first person to publicly endorse IRL politician Ene Ergma as the Reform Party's candidate for president in the scheduled elections. On 12 September 2004, he announced that he was joining the Union of Pro Patria and Res Publica party, whose candidate for president he had been in 1999.\n\nOn 23 September 2004, the Riigikogu elected R\xfc\xfctel to the office of President of Estonia. R\xfc\xfctel was sworn into office on 9 October 2004, and was re-elected in 2006.\n\nR\xfc\xfctel has held a number of positions in the Estonian government since 1991, including as Minister of Foreign Affairs, Minister of Education and Research, Speaker of the Riigikogu, and a two-year term as the Mayor of Tallinn (from 1992 to 1994).\n\nHe has also served as the Chairman of the National Defense Committee and was the leader of the European Movement in Estonia from 1996 to 2004.\n\nOn 20 February 2007, R\xfc\xfctel announced his intention not to run for re-election in the scheduled presidential election of 2007.\n\nHis first wife Tiina Urm (1942\u20132011) died on 9 May 2011, aged 69, from undisclosed causes. R\xfc\xfctel has one son, Peeter, born in 1968, from his first marriage.\n\nHis second wife is Kadri M\xe4lk, with whom he has a daughter, Triin, born in 1989.\n\n]" time="0.394"><properties><property name="score" value="0.50066555" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Crescent-chested whitestart\n\nThe crescent-chested whitestart ("Myioborus luteoventris") is a species of bird in the Parulidae family. It is found in the humid lowland forests of tropical South America. Its range extends from southeastern Colombia, eastern Ecuador, and northeastern Peru to northern Bolivia, southeastern Venezuela, and northern Brazil. It is a fairly common species within its small range, and the IUCN has rated it as a species of "least concern".\n\nThe crescent-chested whitestart is a medium-sized songbird. The adult has a fairly long tail and a thin bill. It is mainly yellow-olive, with a white belly and vent, a yellow breast, and a yellow eyebrow. It has a black stripe over the eye and a whitish crescent on the breast. It is similar to the yellow-bellied white-start and the turquoise-fronted whitestart.\n\nThe crescent-chested whitestart is native to eastern South America, its range extending from southeastern Colombia, eastern Ecuador, and northeastern Peru to northern Bolivia, southeastern Venezuela, and northern Brazil. It inhabits humid tropical forest between sea level and about above sea level. It can be found at altitudes of , but generally below .\n\nThe crescent-chested whitestart is a fairly common species. No particular threats have been identified, and the International Union for Conservation of Nature has rated its conservation status as being of "least concern".\n]" time="0.353"><properties><property name="score" value="0.044981226" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Friedrich Hofmeister\n\nFriedrich Hofmeister was a German piano and music publisher in Leipzig. His company, Friedrich Hofmeister Musikverlag, is the oldest music publishing company in Germany and one of the oldest in the world. It was founded in 1798. His catalogue contained more than 25,000 works, many published as composers' copies, without printed music.\n\nHofmeister was a friend and patron of Robert Schumann, a composer whose music was frequently published by Hofmeister, and a generous supporter of Felix Mendelssohn Bartholdy. A close friendship developed between Mendelssohn and Schumann, who lived at the same time.\n\nOne of the most important works of Schumann, his Piano Quintet in E-flat major, op. 44, is dedicated to Friedrich Hofmeister, as is Schumann's Piano Concerto in A minor, op. 54.\n\nIn his will, Schumann left his house to Mendelssohn.\n\nIn 2011, a new edition of the full catalogue was launched. The company today is a subsidiary of the German publisher B\xe4renreiter, founded in 1525.\n]" time="0.526"><properties><property name="score" value="0.30535167" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Transport and Communications Workers Union\n\nThe Transport and Communications Workers Union (T&CWU) is a trade union in Trinidad and Tobago, with the bulk of its membership employed by the state-owned National Petroleum Company (Petrotrin).\n\nThe union was founded in 1952 as the Oilfield Workers Trade Union, and in 1974 it became the Petroleum Workers Trade Union. In 1977, the union renamed itself as the National Oilfield Workers Trade Union, and then in 1987, the name was changed again to the National Oilfield Workers Union.\n\nThe union changed its name again in 1997 to its current form. In 2005, it merged with the Civil Service and Allied Workers Union, forming the Petroleum and Allied Workers Trade Union. The union re-split in 2007.\n\nFor many years, the union was led by Ancel Roget, and in 1997 he was convicted for soliciting a $40,000 bribe from an executive at the Shell Oil Company. In 2000, Roget was forced to retire from his position at Petrotrin due to a management investigation.\n\nIn 2006, the union was involved in a strike over the state of Petrotrin. In 2010, the union was accused of illegally striking.\n\nIn 2008, a branch of the T&CWU was reported to have hired gang members to threaten striking Petrotrin workers.\n\n\n]" time="0.691"><properties><property name="score" value="0.059499625" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A/N: Before I start, I must confess. I lied. In an interview with Josh Radnor from earlier this year, he claimed he would only do a spin-off if it was centered around Ted and Barney, with the two of them going off to some far off place (New Zealand? Australia?) where they lived in a beach house and watched sports. I laughed. A lot. And now that I have come up with a sequel for The Only Person Who Didn't Run from Ted Mosby, I don't really have a plot for it...\n\n(Disclaimer: This is a work of fan fiction. Any resemblance to any other work of fiction is entirely coincidental. Not to mention a little insulting)\n\nI sat on my bed, looking down at my phone. There was only one person who could help me write this...\n\nI knew it was kind of a lame excuse. I mean, my sister works at a museum, for Pete's sake. She can't help me with a stupid paper. What was I thinking? And I had a really good excuse to tell my girlfriend when I get home. We had a date. But, in order to give me that good excuse, I have to write this stupid paper and get it done. I have to talk to my sister.\n\nI dialed the number to my sister's work, and it started ringing. My sister, Gloria, picked up.\n\n"What's up, D?"\n\n"Glor, do you think you can help me with a paper? I really need some help."\n\n"Sure. What is it about?"\n\n"It's a paper about JFK."\n\n"Oh. Cool. Yeah, sure. What do you need?"\n\n"I need some help finding some good sources for this. I need to know how to start a paper."\n\n"I'm glad you asked."\n\nAnd I was off to a good start. I sat at my desk, making notes. The paper was going to be really easy to write. It would probably only take a couple hours. I knew it. And I would be home before Lily.\n\nThe paper was starting to look really good. I had a bibliography in place, a couple of good paragraphs, and a nice introduction. Everything was great.\n\nI had a paper ready to turn in the next morning. It was almost done, and I was free to go home. But I had a date to get to.\n\n"Bartender!" I called. "One more, please!"\n\n"You sure, man? You're not gonna make it home tonight."\n\n"Nah, man. It's all good. I'll just be getting home, like, ten minutes later than I would."\n\n"Okay, man. Whatever you say."\n\nI started walking out the door, but I took the bar stool with me. I had to carry it around to make it look like I was in a drunken stupor. If my girlfriend saw that I was drunk when I got home, I would never be able to keep my secret.\n\nAs I made my way through the train station, I heard a strange beeping sound. I turned my head to the side, trying to find the source of the noise. It was coming from my phone. There was a text message. I opened my phone, and read it.\n\nI was starting to feel a little tipsy. It was a good thing I was carrying a bar stool around. It made me look like I had a reason for not walking right.\n\nThe message was from Lily. I read it.\n\nThe good thing about living in New York was the night life. I was lucky enough to be able to spend an evening at a nightclub, so I would be home in no time.\n\n"Yeah, man," I said. "I don't know why I even did this, dude."\n\nI walked out of the nightclub and back into the train station. I knew it was late, but the train wasn't too crowded. I sat down in a seat, trying to get some sleep. I would be home soon enough.\n\nI woke up as the train pulled into the station. I was close to home now. It was getting a little crowded on the train, but I managed to squeeze myself into the seat. I was a little more aware of the fact that I was still carrying my bar stool, but I decided to go on anyway.\n\nI stumbled out of the train station, still carrying the bar stool. I made my way through the crowd, out into the parking lot, and across the street to my car. I put the bar stool in the trunk, and got in the car. I turned on the engine, and drove off.\n\n"Hey, Lily. Yeah, I'm on my way home. I'm sorry, but I ran into some trouble. It shouldn't take me long to get home."\n\n"You said that you were just going to be a few minutes late. You said you were on your way home, and then you don't show up for three hours. You call me and say you're sorry? That doesn't even make sense!"\n\n"I know, I know. It's just that it took me a little longer to get home than I thought."\n\n"You lied to me! You said you were going to be home at 8:30! I waited until midnight! You were just trying to get out of our date!"\n\n"It wasn't like that, Lily. I had some trouble with a paper, and then I was at a nightclub. I had a lot of stuff on my mind."\n\n"So, you didn't want to come home. You just didn't want to spend time with me. And now you're calling me after it's all over and trying to explain yourself. And I don't want to hear it! Goodbye!"\n\nI was standing at the door to my apartment, keys in my hand, when I heard my phone ring. It was Lily. I stood there for a moment, trying to decide whether or not I should answer. I looked down at the floor, and then back at my phone. I answered.\n\n"Lily, I-"\n\n"I don't want to hear it, Ted. I told you that I don't want to hear it."\n\n"No, no, it's just that I really have to tell you something. I can't wait until tomorrow. I really need to tell you right now."\n\n"Well, fine. What do you need to tell me? Spit it out."\n\n"It's just that...I think that..."\n\n"Ted, you're babbling. What is it?"\n\n"I...I...well..."\n\n"Ted? Ted! You're breaking up. I think the connection is getting worse. What was it?"\n\n"I think we should break up."\n\n"What?"\n\n"I think we should break up."\n\n"What?"\n\n"I...I...you were right."\n\n"What?"\n\n"I didn't want to spend the night with you. I didn't want to be around you anymore. I wanted to get out of the date. I know it's not fair. I know I was a jerk. I know I lied to you. I just...I don't think we should be together anymore."\n\n"What? Why?"\n\n"I don't know. I just don't."\n\n"Ted, I love you. You can't just say that we should break up like this."\n\n"You were right. You shouldn't have to date me."\n\n"Ted..."\n\n"I'm sorry. I really am. I didn't mean to hurt you. You're a wonderful girl. I just...I don't know. I'm sorry."\n\n"Ted..."\n\n"Goodbye, Lily."\n\nI hung up the phone, and dropped it to the floor. I was standing there for a moment, trying to get my emotions in check.\n\nI had done it. I broke up with my girlfriend of three years. I had broken up with the girl I loved. I had no idea why I did it, but I was doing it.\n\nI opened my door, and made my way to my bedroom. I dropped my keys on the dresser, and sat down on my bed. I leaned against the wall, and closed my eyes.\n\n"Hey, Ted. What are you doing home so early?"\n\n"Lily, I..."\n\n"Ted, I know I was mad at you before, but I've calmed down a lot. You know I love you. I can't live without you."\n\n"Lily, I..."\n\n"Ted, you just scared me, is all. I thought I lost you. I thought you didn't want to be with me anymore."\n\n"Lily, I..."\n\n"I know it was wrong for me to keep pushing you to make up your mind about me, but you couldn't see that."\n\n"Lily..."\n\n"And I know that I can be a little difficult to get along with sometimes, but I know you'll come around."\n\n"Lily, I..."\n\n"We're supposed to be together, Ted. We always knew that. You and me, we're meant to be. You can't just do something like this, Ted."\n\n"Lily..."\n\n"I love you, Ted. You can't just throw that away. I can't just throw that away. I can't..."\n\nI opened my eyes, and saw Lily]" time="1.101"><properties><property name="score" value="0.045210597" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Former Arizona Sen. John McCain died after a yearlong battle with brain cancer.\n\nMy fellow Republicans, John McCain was a true American hero. https://t.co/YlNEJ2KRAS \u2014 Jake Tapper (@jaketapper) August 26, 2018\n\nArizona Sen. John McCain, the maverick Republican whose war record and outspokenness against abuses of power made him an American icon, died on Saturday. He was 81.In a statement, McCain\u2019s office said he died at 4:28 pm local time at the family\u2019s home in Arizona surrounded by family members. The cause of death was not immediately known.The former Navy pilot, who was imprisoned and tortured during the Vietnam War, rose to the top of American politics after emerging as a prominent critic of President Donald Trump.An upstart presidential bid in 2000 did not succeed but after he won the Republican nomination in 2008, he lost to Democrat Barack Obama.Despite the loss, his image soared and he emerged as one of the most influential members of the Senate, willing to work with Democrats on issues like campaign finance reform.By the time he ran for president again in 2016, he seemed like a throwback to a bygone era of civility and bipartisanship. McCain ran against Obama again in 2008.He continued to play a pivotal role in American politics, becoming chairman of the powerful Senate Armed Services Committee after the Republicans regained control of the Senate in 2015.McCain in the past had been a thorn in the side of Republican presidents \u2014 George W. Bush and Trump.He was also well known for reaching across the aisle.He took a secret trip to visit Syrian dictator Bashar al-Assad during the early years of the country\u2019s civil war, and was one of the final Republicans to speak with the president before his firing last year.He was a long-time critic of the U.S. use of torture against detainees.He held out against Republicans\u2019 efforts to dismantle Obama\u2019s signature healthcare legislation and refused to support the Graham-Cassidy bill last year.He was a harsh critic of Russia, and one of the earliest supporters of sanctions against Russian officials. He played a role in seeking to keep the United States from launching a pre-emptive attack against North Korea in the face of its nuclear provocations.McCain was one of the first Republicans to support Trump\u2019s presidential campaign in 2016. But when the \u201cAccess Hollywood\u201d tape emerged, he withdrew his support, and famously said in his 2017 memoir \u201cThe Restless Wave,\u201d \u201cI do not know how I could have spoken so disrespectfully about the commander in chief of the Armed Forces.\u201dHe also repeatedly denounced what he called Trump\u2019s \u201ccheap rhetoric and insults\u201d against U.S. allies, and after Trump\u2019s summit with Russian President Vladimir Putin in July 2018, called it a \u201ctragic mistake.\u201d He was one of the loudest Republican voices criticizing the president for his performance at a summit with Putin in Helsinki.Trump mocked him as \u201ca clown,\u201d and even at the end of his life, he was still a target for the president, who reportedly resisted hosting a state funeral.On Saturday, Trump said he sent his \u201cdeepest sympathies and respect\u201d to McCain\u2019s family.\u201cThe nation mourns the loss of a great American patriot, a statesman who put his country first and enriched this nation every day he served.\u201dFormer President Barack Obama called him a \u201cgiant of American politics,\u201d and his one-time opponent in the 2008 presidential race said he was \u201ca man of deep conviction and a patriot of the highest order.\u201dPresidential candidate Sen. Bernie Sanders, I-Vermont, called McCain \u201can American hero\u201d on Twitter.McCain\u2019s funeral service will be held at the Washington National Cathedral and the ceremony will include eulogies from former President George W. Bush, former President Barack Obama, former Secretary of State Henry Kissinger and former Sen. Joe Lieberman, the former vice-presidential candidate who was a close friend.After the service, he will be buried in Annapolis, Md., at the U.S. Naval Academy.McCain was born at a naval station in the Panama Canal Zone, where his father was stationed. After his father\u2019s career in the Navy, the family settled in the Arizona desert, where he attended high school.McCain studied at the Naval Academy and became a pilot in the Navy, serving on a ship that was shot down in Vietnam. He spent five-and-a-half years in captivity, which included torture, before he was released in 1973.McCain returned to the U.S. and was assigned to the Senate as a liaison to the Navy. He became a member of the House of Representatives in 1983 and eventually the chairman of the Senate Committee on Commerce.During his 2008 presidential bid, he secured the GOP nomination in the face of much skepticism. At a dinner in 2008, then-Sen. Barack Obama joked that after losing to Obama, McCain would be on a beach sipping a drink with \u201can umbrella in it.\u201dThe Republican-led Senate, which was much closer to McCain than to the president, overwhelmingly passed a resolution earlier this year that censured Trump for his \u201cbigoted and racist\u201d remarks about four members of Congress.In his memoir, McCain said that he regretted that his choice of Sarah Palin as a running mate did not propel him to the White House. He said he made the choice based on who he thought could become president, but that was wrong.\n\nJoin Jerusalem Post Premium Plus now for just $5 and upgrade your experience with an ads-free website and exclusive content. Click here>>\n\n\n\n]" time="0.745"><properties><property name="score" value="0.008506340000000001" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00850634 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00850634
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Avolites V-Color 2\n\nV-Color is an all-in-one visualisation system for lighting professionals which empowers operators with unprecedented control and flexibility, while also offering total ease-of-use. A complete visualisation solution for the modern production environment.\n\n\n\nNew V-Color 2 Software\n\n\n\nUsing the same hardware, V-Color 2 offers full compatibility with existing shows, but with brand new software including some great new features and exciting innovations.\n\n\n\nMore Detailed, Better Feedback\n\nThe addition of 3D colour bars gives a better representation of colour than before. The inclusion of warm/cool & complementary information makes diagnosing colour temperature easier than ever. An inbuilt screen lock function and scene copy capability further streamlines the user experience.\n\n\n\nEasier Control of Everything\n\nWith a large, backlit LCD screen, V-Color 2 gives the operator total control of the system from a distance. The touchscreen interface makes everything intuitive and gives instant access to show information and control options.\n\n\n\nSeamless Integration into Live Production Workflow\n\nPowered by ProfilerX (firmware version 2.3 and above), V-Color 2 gives the operator seamless and continuous control over their show using the same industry standard protocol as their other devices. This means that they can operate their visualisation system in parallel with their lighting console, creating the ideal platform for shows involving complex automated and DMX control.\n\n\n\nBigger, Better, More Powerful\n\nThe increased size of V-Color 2 gives it the space to fit a larger screen with a better resolution. The dual menu and page system makes navigation easier than ever and the addition of a USB port and SD card slot allows the operator to save and play back their show in a simple and fast manner.\n\n\n\nFeatures:\n\n\u2022 Upgradeable for full ProfilerX support.\n\n\u2022 Highly responsive and intuitive touchscreen interface.\n\n\u2022 Fits into any lighting desk.\n\n\u2022 Dual menu system.\n\n\u2022 USB & SD card slot for show playback.\n\n\u2022 Upgraded 3D colour bars.\n\n\u2022 Larger display for better visibility.\n\n\u2022 ProfilerX compatible.\n\n\u2022 Industry standard OSD protocol.\n\n\u2022 Relay channel output for all screens.\n\n\u2022 Separate input and output cables.\n\n\u2022 Quick calibration system.\n\n\u2022 Assignable RS232 port.\n\n\n\nSpecifications:\n\n\u2022 VGA & HDMI Input.\n\n\u2022 TFT screen.\n\n\u2022 WVGA screen resolution.\n\n\u2022 USB & SD card slot.\n\n\u2022 Can be fitted to V-Pad stand.\n\n\u2022 Size: 10.1" x 5.9" x 1.7".\n\n\u2022 Weight: 1.2kg.]" time="0.448"><properties><property name="score" value="1.8513297" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Power Consumption\n\nIdle: Windows Vista Aero sitting at the desktop (1280x1024 32-bit) all windows closed, drivers installed. Card left to warm up in idle mode until power draw was stable.\n\nMulti-monitor: Two monitors connected to the tested card, both using different display timings. Windows Vista Aero sitting at the desktop (1280x1024 32-bit) all windows closed, drivers installed. Card left to warm up in idle mode until power draw was stable.\n\nAverage: Crysis 2 at 1920x1200, Extreme profile, representing a typical gaming power draw. Average of all readings (12 per second) while the benchmark was rendering (no title/loading screen).\n\nPeak: Crysis 2 at 1920x1200, Extreme profile, representing a typical gaming power draw. Highest single reading during the test.\n\nMaximum: Furmark Stability Test at 1280x1024, 0xAA. This results in a very high non-game power-consumption that can typically be reached only with stress-testing applications. Card left running stress-test until power draw converged to a stable value.\n\nBlu-ray Playback: Power DVD 9 Ultra was used at a resolution of 1920x1200 to play back the Batman: The Dark Knight disc with GPU acceleration turned on. Playback started around timecode 1:19, which has the highest data rates on the BD with up to 40 Mb/s. Playback was left running until power draw converged to a stable value.\n\nCooling modern video cards is becoming more and more difficult, especially when users are asking for quiet cooling solutions. That's why the engineers are now paying much more attention to power consumption of new video-card designs.For this test, we measured the power consumption of the graphics card only via the PCI-Express power connector(s) and PCI-Express bus slot. A Keithley Integra 2700 digital multimeter with 6.5-digit resolution was used for all measurements. Again, the values here reflect only the power consumption of the card measured at DC VGA card inputs, not of the whole system.We choseas a standard test representing typical 3D gaming usage because it offers the following: very high power draw; high repeatability; is a current game that is supported on all cards because of its DirectX 9 roots; drivers are actively tested and optimized for it; supports all multi-GPU configurations; test runs in a relatively short time and renders a non-static scene with variable complexity.To measure the power consumption of our testbed we used a digital power meter (Keithley Integra 2700) connected before the power supply. The power consumption measurement of the system is based on the power consumption of the drives, not of the graphics cards. All cards were tested with a total of four SSDs: one in the system, one used as a primary test drive in a slot without a powered connector, and two additional drives in the system (not used for testing). The SSDs are Western Digital WD360GD (362GB), WD1500HLHX (150GB), Samsung SSD 830 (128GB) and OCZ Agility 3 (240GB).Idle power consumption of the whole test system (at the desktop) is measured after sitting idle at the desktop for 30 minutes. The cards are not closed. The result is presented as the average value of all four cards.Please note that after extensive testing, we found that measuring idle power consumption only, as seen in many other reviews, can be misleading. Due to different testing methodology and environments, this number can be significantly lower than the real power consumption. Also, in many cases, the card does not reach the desired idle temperature, so it will draw more power. In our test setup, the cards reach their idle temperature very quickly (in a few minutes) and in a climate controlled room (22\xb0C).Therefore, we use this only as a rough indication of the cards' power consumption.Please note we are using different adjustements to test the performance of our graphics cards. Our testing methodology is detailed here . It's worth mentioning that our method allows us to perform a more thorough test that's free from GPU bottlenecks. It's also free from variations caused by dual-gpu/hybrid configurations.The following two values are the peak power consumption and the maximum power consumption of our testbed (without speakers/headphones) measured after long periods of use (at least 15 minutes) with Windows Aero enabled. The peak power consumption is the maximum power draw of the graphics card only, measured in the most stressful situation (generally, when it's overclocked). The maximum power consumption is the maximum power draw of the complete testbed, including the monitor, speakers, hard-disk, SSD, etc.The results are impressive. Idle power consumption is a tiny bit higher than that of the GTX 580. All cards operate at fairly low power levels in idle. NVIDIA has done a good job reducing idle power consumption of its GTX 680. Under full load, the GTX 680 is only slightly more power hungry than the GTX 580. Compared to AMD, the GTX 680 fares even better as it uses slightly less power than the HD 7970.All graphics cards tested consume quite a lot of power during Blu-ray playback. Interestingly, this is one area where NVIDIA can't keep up with AMD.]" time="0.913"><properties><property name="score" value="0.136673628" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.13667363 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.13667363
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A bi-partisan bill that would give states the option to spend welfare funding on faith-based charities is making its way through the U.S. Senate.\n\nThe legislation is called the Combating and Preventing Crimes of Violence Act, and it would give states the ability to use federal funds on programs that promote "the traditional values of marriage, family, religion, and morality." The bill would also authorize $5 million annually to states to promote chastity and healthy marriage.\n\nState governments would be permitted to use federal welfare funding to teach young people "the social, psychological, and health gains to be realized by abstaining from sexual activity," according to the text of the bill, which was introduced by Sen. Orrin Hatch (R-Utah) and 23 other co-sponsors.\n\nSen. Hatch said the legislation would reinforce "state efforts to strengthen families and communities by increasing opportunities for the social and economic advancement of young people."\n\nSen. Hatch's home state of Utah passed a similar law in 2013, and it was successfully implemented, according to a statement from the senator's office.\n\n"This is not an effort to allow taxpayer funding for religious groups, but to give states the option to partner with groups to promote healthy relationships," the senator's statement said.\n\nHowever, the American Civil Liberties Union (ACLU) criticized the legislation as "misguided" and "misinformed," saying that it would restrict the freedom of organizations that provide critical services to women and children.\n\n"We have grave concerns about this bill because it's divisive, discriminatory, and fiscally irresponsible," Laura Murphy, director of ACLU's Washington Legislative Office, said in a statement. "It would allow states to use federal funds to provide child welfare services in a way that would exclude those who are not religious or who don't subscribe to traditional family values. This means that women and children who need assistance would be turned away, and those who provide critical services would be fired or not hired."\n\nThe bill, which was approved by the Senate Committee on Finance on Wednesday, now heads to the Senate floor.]" time="0.435"><properties><property name="score" value="0.14271405" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.14271405 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.14271405
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[HUNDREDS OF people are expected to attend a public meeting in Clonmel this evening which will focus on the recent developments in the Irish Water saga.\n\nClonmel Borough Council has granted permission for the meeting to be held in the Tower Hotel at 7pm.\n\nGarda\xed have also been notified of the meeting but a spokesperson said they are not expecting any trouble.\n\nThe meeting comes in the wake of a massive turnout at a public meeting on Sunday last where thousands of people flocked to a hall in Carrick-on-Suir, Co Tipperary to hear speakers on the Irish Water issue.\n\nThe Tipperary Star reported today that a Fine Gael representative has complained to the party\u2019s headquarters about a leaflet produced by the Carrick on Suir branch of the party.\n\nThe leaflet called on people to attend the meeting on Sunday last in order to oppose Irish Water and the installation of water meters.\n\nSpeaking to the Star, Fine Gael TD for Tipperary South Noel Coonan said the leaflet had damaged the image of Fine Gael in the area.\n\nHe also described it as a \u201cdistortion of facts\u201d.\n\n\u201cIf this is being done in the name of Fine Gael, it is very serious,\u201d he said.\n\n\u201cI was very disappointed to see this leaflet which was distorting the facts. I\u2019m very annoyed about this and I will be taking it further.\u201d\n\nCouncillor Coonan also questioned the language used in the leaflet and the manner in which the information was presented.\n\nFine Gael councillor in Carrick on Suir, Councillor Martin Browne defended the leaflet, saying that it was a statement from the party\u2019s national executive and was a totally legitimate use of the party\u2019s logo.\n\n\u201cIt was used to promote a public meeting which was organised by a totally independent group,\u201d he said.\n\nThe group was not aligned to the party in any way and was not part]" time="0.409"><properties><property name="score" value="0.024202975" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02420298 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02420298
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[John Astley (diplomat)\n\nJohn Francis Melhuish Astley, CMG (born 2 January 1950) is a former British diplomat.\n\nAstley was educated at St Paul's School, London, and the University of Cambridge, where he was a member of St John's College.\n\nAstley joined the Foreign and Commonwealth Office (FCO) in 1973. He served as Consul in Santa Cruz, Bolivia, 1973\u20131975, Deputy Consul General in San Francisco, California, 1981\u20131984, Deputy Head of the Middle East Department, FCO, 1985\u20131987, Private Secretary to the Secretary of State for Foreign and Commonwealth Affairs, 1987\u20131989, and Ambassador to Bahrain, 1990\u20131993.\n\nIn 1993 Astley became the first Permanent Under-Secretary of State at the FCO since the Second World War. He was appointed Companion of the Order of St Michael and St George (CMG) in the 1995 New Year Honours. From 1996 he was Ambassador to the Netherlands.\n\nIn 1999, during his tenure as Ambassador to the Netherlands, he was informed that his name appeared on a list of paedophiles. He had no connection to the accusations, but he resigned anyway, rather than face public humiliation.\n\nFrom 2000 to 2006 Astley was Chair of the Northern Ireland Audit Committee, an all-party group of the Northern Ireland Assembly, reporting to the Assembly and the Northern Ireland Audit Office.\n\nAstley was a director of Intraco Management Services Ltd, a recruitment firm.\n\nIn 2006 he was appointed a non-executive director of the Ministry of Defence's Defence Business Services organisation, where he remained until 2010.\n\nAstley is a member of the Athenaeum Club.\n]" time="0.327"><properties><property name="score" value="1.1302276" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.1302276 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.1302276
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Stephen W. Kearney\n\nStephen Watts Kearney (June 17, 1794 \u2013 October 31, 1848) was an officer in the United States Army who is best known for his leadership in the Mexican\u2013American War, in particular the Battle of Monterrey and the Battle of Buena Vista.\n\nKearney was born in Newark, New Jersey. He was a descendant of John Kearney (1635\u20131701), a native of Ireland who was the first of the family to settle in what became the United States. John's son Richard (1668\u20131734) was born in Bristol, England, but became a fur trader in what was then the English colonies and later became New Jersey. Richard was commissioned as an ensign by British colonial governor Jonathan Belcher in 1709.\n\nRichard's son James (1703\u20131785) was a general in the New Jersey colonial militia during the French and Indian War. James's son Stephen Watts Kearny, the namesake of the general, was a captain in the War of Independence and was at the surrender of General John Burgoyne. His home, the Kearney Mansion, has since been preserved in Newark.\n\nIn 1794 he moved with his parents to Louisville, Kentucky. His father, Alexander Morris Kearney, a native of South Carolina, was a captain in the American Revolutionary War. In the War of 1812, Kearney participated in the Battle of Lundy's Lane, where he was wounded and captured by the British. After being released, he joined the Missouri Rangers and, in 1813, married Mary Radcliffe Matthews. In 1814 he joined the 5th United States Infantry as its sixth lieutenant and served in the war against the Creek nation. In 1819 he was promoted to captain and assigned to the 1st U.S. Infantry. Kearney resigned from the Army in 1822 and became superintendent of Indian affairs at St. Louis, Missouri.\n\nIn 1832 Kearney was appointed as governor of the New Mexico Territory, where he was active in promoting settlement and negotiating treaties with the Native Americans. Kearney participated in the Gila Expedition of 1837 and then commanded the Army's Third Dragoon Regiment in Florida in 1837 and 1838.\n\nDuring the Mexican\u2013American War, Kearney was appointed colonel of the 1st New York Dragoons on June 30, 1846. Kearney's new regiment was sent to Santa Fe, New Mexico, to reinforce the Army of New Mexico under Col. Stephen Watts Kearny (no relation). There they joined the march on the capital of Mexico City. On the way, Kearney's regiment carried out several successful raids, including the Battle of La Mesa, where he captured a large amount of ammunition and supplies. He took the Puebla de Los Angeles without opposition on December 7, 1846. There he received word that his promotion to brigadier general had been approved.\n\nKearny, reinforced by the 3rd Infantry and Mormon Battalion, took the city of Monterrey on September 25, 1846. During the battle, a cannonball tore away part of Kearny's jaw and neck.\n\nFollowing the battle, Kearney was carried to Saltillo for medical treatment. While he was recovering, Lt. Colonel John Garland was given command of the 1st Dragoons. In February 1847, Kearney returned to the army and resumed command of the dragoons. Kearney served in the Battle of Buena Vista, and later he fought in the Taos Revolt. He returned to the United States in October 1847 and was assigned to Fort Leavenworth in the Kansas Territory.\n\nKearney, a bachelor, died of cholera at Fort Leavenworth at the age of 54. He was buried in the Fort Leavenworth National Cemetery.\n\nSeveral U.S. Army installations are named in honor of Kearney, including Kearney Barracks in Wilhelmshaven, Germany, the Kearney Building at Fort Leavenworth, and Fort Kearny, Nebraska, which is now a state historic site.\n\n\n]" time="0.327"><properties><property name="score" value="0.37364724" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.37364724 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.37364724
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Los R\xedos Province, Chile\n\nLos R\xedos (Spanish for "The Rivers") is one of four provinces in the southern Chilean region of Los R\xedos (IV). The capital is Valdivia.\n\nAs a province, Los R\xedos is a second-level administrative division of Chile, governed by a provincial governor who is appointed by the president.\n\nThe province comprises eleven communes (Spanish: "comunas"), each governed by a municipality consisting of an alcalde and municipal council:\n\nThe province spans an area of , the second largest in the region. According to the 2002 census, Los R\xedos Province had a population of 253,331 inhabitants (133,315 men and 120,016 women), giving it a population density of . Of these, 119,262 (46.4%) lived in urban areas and 134,069 (53.6%) in rural areas. Between the 1992 and 2002 censuses, the population grew by 1.9% (4,243 persons).\n\nAs a province, Los R\xedos is a second-level administrative division of Chile, which is further divided into eleven communes.\n\nWithin this province are the most important archaeological ruins in all of southern Chile. The ancient city of "Puquios", capital of the "Lentas" nation, is located in the commune of Valdivia. Other ruins include those at Chep\xe9n, Chichihualco and the ancient fortifications of Valdivia. Also of interest is the "Cueva del Milod\xf3n", which features the remains of an extinct species of giant sloth.\n\nThe native tree "Fitzroya cupressoides", locally called "lauca" or "lauco", is a common tree in the forests of the coastal mountains.\n\nThe Rupanco and Quinchao Islands in the Chonos Archipelago are part of Los R\xedos.\n\nLike other southern regions of Chile, Los R\xedos experiences a moderate climate. Its weather is affected by the cold Humboldt Current which flows along the west coast of South America from Antarctica. During the summer months, temperatures can reach , while in the winter temperatures hover around .\n\nThe province is one of the most forested ones in Chile. Its economy is based on timber, salmon and tourism.\n\nRupanco and Quinchao Islands are part of the commune of Quinchao. The latter, together with a few minor islands, forms the "Ciudad Insular" (Inhabited Island) of Quinchao, with approximately 3,500 inhabitants, and is administered as part of the "Comuna" of Quinchao, in the province of "Llanquihue".\n\n]" time="0.356"><properties><property name="score" value="0.12446896" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In many places there are no longer any young men at all. According to the World Health Organization, "in countries with very low fertility, the proportion of young people may halve in the next 40 years". At this rate, by 2100 a majority of the world's population will be over 50. We will then have to find a way to accommodate the needs and aspirations of an unprecedented number of very old people in a society that has been moulded for decades around the needs of youth.\n\nNowhere is this more true than in Japan, the world's fastest-ageing country. The greying of Japan \u2013 "silver tsunami" or "grey goo" as it is known \u2013 is by now well known. There are a number of reasons for this. Japanese have one of the longest life expectancies in the world, with women expected to live to 87 and men to 80. Meanwhile, a long-standing national emphasis on having small families and long working hours \u2013 for both men and women \u2013 have kept the birth rate below replacement levels. And Japan's postwar economic miracle has not been kind to the young. The country's population is shrinking, partly because of a low birth rate and partly because of a high level of immigration.\n\nBut what is less well known is that this graying of Japan \u2013 and other nations such as Germany, China, South Korea and Thailand \u2013 is not just due to longer life expectancy and lower birth rates. There is another factor in play, and one that could have dramatic implications: very low fertility rates, particularly among younger women. It's estimated that around a quarter of the population will be aged over 65 by 2050.\n\nIn Japan, the "total fertility rate" (the number of children a woman is likely to have in her lifetime) is just 1.4 \u2013 and has been for the past 20 years. Among women aged between 15 and 24, the rate is even lower at 0.8, lower even than the famously low rate in Germany (which is 1.38). And in Tokyo, that rate is even lower at 0.7. By contrast, in 2010, the average rate in Europe was 1.6. The fertility rate in England and Wales in 2010 was 1.9.\n\nThe world's media are full of breathless stories about Japan's crisis of depopulation. Last year, an article in the International Business Times said that "Japanese women are rejecting marriage and motherhood at a staggering rate". In the New York Times, another piece claimed that Japan is "exporting its young women" and is now "facing a demographic crisis of epic proportions". More soberly, the BBC's business editor Robert Peston has written: "Without a dramatic increase in its birth rate, Japan will face economic and social ruin."\n\nThe sense of panic is understandable. "The number of young people will go down by two-thirds by 2035," says demographer Toshio Kanazawa. "That means not only a decline in the size of the workforce but a dramatic increase in the number of retirees. Who will pay for them?"\n\nThe answer is "women" \u2013 or more specifically, their wombs. And in this, there is something not quite right.\n\nIn Tokyo, I meet Nana, a 29-year-old who is employed in the financial sector. She is smartly dressed in a suit and speaks good English. She tells me she has a boyfriend and they are very happy. She is, she says, the typical "She Economy" \u2013 a young woman working in the city and her parents are very pleased. "They want me to settle down," she says, "and have children." But she's not so sure.\n\n"It's too late," she says. "I've got to think of my future. And I just don't know if I could afford it \u2013 having children. I'd need a bigger flat, and pay for childcare, and a new car."\n\nFor Nana, and for many Japanese women like her, the economic reality of having children is daunting. "I have two brothers," she says, "and they have wives and children. The wives don't work, and they have one or two children. One of my sisters-in-law doesn't even work outside the house. They don't have much money, but my parents love them. They are very happy. So I know what my parents want for me. But it's impossible. I can't do it."\n\nThis is a scenario that is playing out in homes across the country. The situation is, in many respects, rather unique. As Peston points out, Japanese women who stay in employment tend to have children later. As a result, while there is a generation of Japanese in their early 30s who have given up on having children, there is a generation of younger women who are still trying to get pregnant.\n\n"I think it's pretty much impossible to have two or three children in Tokyo," says Seiko, a 35-year-old marketing executive. "I don't think I could afford it. You have to pay so much for childcare. And then, you've got to give up work. I just couldn't do it.\n\n"But, still, my mother is pressuring me to have children. If you have a boyfriend, you can't get married. It's impossible. You have to marry first, then have children. So, if you are a working woman, you have to get married, have children, and then stay at home with your children. That's it. And that's what everyone wants. That's the ideal."\n\nAt the root of this ideal is Japan's traditional gender-role society \u2013 one that has stayed remarkably the same since the end of the second world war. It is not, perhaps, surprising that such a rigid society is under strain. And not only for women. It is also under strain for men.\n\n"Women in Japan are not treated well," says Toshio Kanazawa. "They don't earn a lot of money. They are discriminated against in many ways. That's why there aren't enough babies."\n\nNot everyone agrees. "I don't think it's true," says Nana, who, I've noticed, has referred to herself as "boku" (which means "I") all evening, rather than the more feminine "watashi" (which means "I"). "Women in Japan are strong. They do well at work and they earn a lot of money. They can do everything. So why should they have children?"\n\nIn some respects, Nana has a point. Japan is a country in which young women are breaking glass ceilings. The number of women in senior management in Japan's 3,000 largest companies is at a record high. And in 2013, the World Economic Forum rated Japan the fourth most "gender-equal" nation in the world.\n\nThe Japanese government has encouraged this development. Ever since the Second World War, successive prime ministers have tried to get more women into the workplace and have even gone so far as to tell men to "say goodbye to their bonuses if they refuse to let their wives and daughters work outside the home".\n\nBut while some Japanese women are finding their way into senior positions, many are also facing a harsh reality: most large Japanese corporations have an unofficial "marriage bar" that prohibits the promotion of women who are married and have children. This is particularly true of men. According to a study by the Japanese government, 61.5 per cent of male managers are married. By contrast, only 42.2 per cent of female managers are married. This means that women with children can be in a very difficult position, because \u2013 as Shihoko Goto of the Wilson Center points out \u2013 they face a choice between marriage and career. And that is not a choice that men face.\n\n"If you look at people in their 30s," says Seiko, "I think many of them are not getting married and having children. If you don't have children, you have more time and money to enjoy your life. So why not?\n\n"I don't think that women are rejecting marriage and family," she says. "It's just that if you want children and you are a career woman, it's impossible. There is no way. You can't do both. And so you have to make a choice. Either you go for your career or you go for marriage and family. That's what I think is happening."\n\n"In Japan," says Goto, "it's very difficult for men and women to be able to balance work and family. So, if you are a career woman, you will have to sacrifice family. That's the problem. That's why so many women don't have children. Because they want to focus on their career."\n\nThis is a view echoed by Ai Kato, a 29-year-old tax accountant. "It's true that if you work in a large Japanese company, you cannot get married or have children if you want to keep your job," she says. "That's the reality. It's a matter of the company culture. It's difficult to balance both. And so people are having fewer children."\n\nJapan has never really known anything else. "Since the Meiji era [from 1868 to 1912] Japan's population has been very stable," says Kanazawa. "So they think that is normal. But it's not. If you look at Germany, their population is falling too, but they are getting immigrants. And in the US and the UK, the population is stable, but people are having more children. So there are many different types of demographic change, and Japan is one of the most extreme."\n\nWhat is less clear is why this is happening. The popular explanation is that Japan is a victim of the phenomenon known as the "demographic time bomb" or "]" time="0.657"><properties><property name="score" value="0.056043313333333344" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Australian Computer Emergency Response Team\n\nThe Australian Computer Emergency Response Team (AusCERT) is the recognised national computer security incident response team of the Australian Government. AusCERT works closely with the Australian Communications and Media Authority (ACMA), the Australian Federal Police (AFP), the Department of Defence (Defence), the Australian Taxation Office (ATO), and other government departments and agencies to deal with computer security incidents on an operational level. The organisation also provides specialist security incident response advice and services to the private sector.\n\nAusCERT was established in 1987 under the auspices of the Australian Computer Society (ACS) and is funded by the Australian Government through the Department of Communications and the Australian Government Information Management Office (AGIMO).\n\nAusCERT provides services to the public and private sectors in the following areas:\n\nThe headquarters for AusCERT are in the inner-city Melbourne suburb of Fitzroy, and are situated at the ACS Victoria. Other AusCERT team members are located around the country, including in Sydney, Brisbane, Adelaide and Perth.\n\nIn the early 1980s, the Australian federal government recognised the need for a computer emergency response capability and developed the Computer Emergency Response Team (CERT) concept. The first CERT team was established in December 1987 as the Computer Incident Advisory Capability (CIAC) under the auspices of the Australian Computer Society (ACS) at the University of Melbourne. In the mid-1990s, CIAC changed its name to AusCERT and moved its headquarters to the Department of Communications in Canberra. Since then, it has moved to the AGIMO building in Belconnen, ACT. In January 2013, AusCERT relocated to the City of Melbourne.\n\nAusCERT is a specialist organisation that provides advice and assistance in computer security incidents to its constituent members. As an operational unit, AusCERT:\n\n\nAusCERT's incident management process incorporates the Australian Signals Directorate's Incident Handling Working Model, an approved Australian Standard, AS 4801-2005.\n\nAusCERT is the designated lead agency for computer security incidents within Australia's Critical Infrastructure community, as defined by the Communications and the Arts portfolio of the Commonwealth Government.\n\nSince 2001, AusCERT has been responsible for issuing national warnings and alerts on a number of security issues, as directed by the Australian Communications and Media Authority (ACMA).\n\n\nAusCERT is active in a number of national and international computer security forums. AusCERT regularly participates in the Cyber Storm exercises conducted by the US Department of Homeland Security, as well as the Cyber Storm exercises hosted by the Singapore Infocomm Development Authority. AusCERT has also participated in the Cyber Security Exercise Series (CSES) developed by the Government of New Zealand. In 2003, AusCERT attended the UK's National Infrastructure Security Coordination Centre (NISCC) / British Computer Emergency Response Team (BCERT) course, and was the first international agency to receive the NISCC's Advanced Incident Handling course.\n\nOn 8 September 2005, AusCERT signed a Memorandum of Understanding with the US Department of Homeland Security's United States Computer Emergency Readiness Team (US-CERT) to formalise cooperation in the areas of:\n\n\n]" time="0.305"><properties><property name="score" value="0.22993536" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.22993536 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.22993536
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Ahmed Harkat\n\nAhmed Harkat (, ; born April 27, 1971 in Ottawa, Ontario, Canada) is a Pakistani Canadian and Muslim who was detained as a threat to national security and imprisoned for two years in Canada.\n\nOn May 1, 2005, a Canada-wide arrest warrant was issued for Harkat by the Federal Bureau of Investigation (FBI) of the United States. On July 18, 2005, Ahmed Harkat was arrested under a Security Certificate by the Government of Canada, at his home in Ottawa, on the grounds that he was involved in terrorist activities, in particular in association with the al-Qaeda organization. On November 23, 2005, Ahmed Harkat was detained indefinitely by the Federal Court. He was released on strict house arrest conditions on February 1, 2006, after the Supreme Court of Canada ruled that his detention was unconstitutional. On December 13, 2007, the Court of Appeal for Ontario found that Harkat was detained lawfully. However, the Court ordered a new detention review hearing to be held before the end of June 2008. The Supreme Court of Canada refused to hear his appeal on February 15, 2008.\n\nHarkat applied for a judicial review of the decision of the Minister of Public Safety to order his detention. The Federal Court of Canada dismissed his application on December 14, 2006. Harkat has appealed to the Supreme Court of Canada.\n\nThe Federal Court decision came a week after the United States Senate rejected a bill to close the Guantanamo Bay detention camp.\n\nIn August 2008, Harkat was living under 24-hour house arrest, with some restrictions.\n\nOn June 17, 2009, the Supreme Court of Canada ruled that the security certificate under which Harkat was detained was valid and that he must be deported.\n\nOn July 29, 2015, the Federal Court of Appeal upheld a lower court decision and ruled that Harkat could stay in Canada. The ruling meant that Harkat could not be removed from Canada and remained under a strict form of house arrest.\n\nOn January 12, 2017, the Supreme Court of Canada refused to hear his appeal.\n\nAhmed Harkat was born in Pakistan in 1971, and he came to Canada in 1995. He speaks some English and has a wife and three daughters. He is a pizza delivery driver in Ottawa, Ontario, Canada.\n\nHarkat worked in Peshawar, Pakistan as a relief coordinator for Care International Pakistan, an international humanitarian organization, until 1999. He then went on to work as an accountant and cashier at Afghan Relief in Peshawar, a project of the National Council for Voluntary Social Services (NCVSS).\n\nHarkat came to the attention of Canadian intelligence officials after being deported from Dubai in April 2000, after he failed to obtain a visa for the United States. He has never visited Afghanistan, a key requirement of a security certificate. Harkat also states that he was not involved in any terrorist activity, and has never supported or associated with a terrorist organization.\n\nHarkat was arrested on December 10, 2002. He was charged with knowingly facilitating a terrorist activity and knowingly participating in the activities of a terrorist group.\n\nOn January 23, 2003, a judge granted the Royal Canadian Mounted Police (RCMP) an order to monitor his activities and to search his home. On March 20, 2003, Harkat was released under a strict curfew. The surveillance and house arrest was lifted on September 11, 2003.\n\nOn February 10, 2004, the judge in the case ruled that Harkat would not be allowed to work as a relief coordinator in his community or to interact with a list of specified persons, including the media. On March 10, 2004, Harkat's curfew was changed from 11 p.m. to 6 a.m., and the list of people he was not allowed to contact was expanded to include more than 100 people, including several Members of Parliament.\n\nOn May 11, 2004, the judge in the case ruled that Harkat would not be allowed to attend community events, and that he would be required to meet regularly with RCMP officials.\n\nOn August 16, 2004, Harkat was accused of writing love letters to two married women, one of whom was an RCMP officer.\n\nOn September 15, 2004, the Attorney General of Canada, under Paul Martin, asked that Harkat be detained for an additional six months, which was approved by a judge on October 12.\n\nOn September 30, 2004, Harkat's wife, Sophie, appeared on a news show, the "National Magazine" on CBC.\n\nOn January 21, 2005, the Federal Court of Canada ordered Harkat to remain under a 24-hour surveillance and under house arrest. On January 23, 2005, he was required to surrender his passport.\n\nOn May 1, 2005, a Canada-wide arrest warrant was issued by the FBI for Hark]" time="0.297"><properties><property name="score" value="0.016722675" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[By DontHassleDaHoff\n\nWe're heating things up with PROJECT: Overcharge in the upcoming Patch 7.24b!\n\nPROJECT: Overcharge\n\nAssault up, minions! Project: Overcharge replaces Stormrazor and Stormguard Banner, empowering your entire team with 10% increased attack speed and 8% increased movement speed for 15 seconds. In addition, you'll gain Overcharge stacks while attacking enemy champions and playing as Summoner's Rift objectives. The more you participate, the faster you charge!\n\nWith the PROJECT pre-season approaching, we're giving Overcharge a test run on the PBE!\n\nHow do I get Overcharge?\n\nYour team starts with a fixed number of Overcharge tokens that reset when you recall. You earn more Overcharge by killing enemy champions and playing as objectives.\n\nObjective Total tokens Rift Herald 2 Scuttle Crab 2.5 Dragon 4\n\nKilling an enemy champion generates 1 stack, but if you earn more than 5 stacks, you'll go into "overdrive" and get a short burst of additional movement speed and attack speed!\n\n1-5 stacks: +8% AS / 10% MS\n\n6-10 stacks: +16% AS / 20% MS\n\n11+ stacks: +24% AS / 30% MS\n\nOverdrive lasts 1.5 seconds and grants up to +120% bonus AS and +180% bonus MS!\n\nOverdrive ends immediately if you're dealt damage greater than 4% of your maximum health or if you activate Stormguard Banner.\n\nPROJECT: Hunters\n\nPROJECT: Hunters rewards map objectives and creating map pressure for your team. If you slay a jungle monster or help your allies take down an enemy Rift Herald, Dragon, or Baron, you'll earn a stack of PROJECT: Hunters.\n\n1 stack for Rift Herald\n\n2 stacks for Dragon\n\n4 stacks for Baron\n\n3 stacks for a secured Baron kill\n\nWhen you earn a stack of PROJECT: Hunters, you and your teammates are empowered for 15 seconds with +10% bonus movement speed and +10% bonus attack speed.\n\nPlay the objective and rack up those stacks to hunt for the enemy team!\n\nExhaust changes\n\nWe're making some changes to Exhaust that are designed to let it work better with aggressive crowd control effects.\n\nWe want to remove Exhaust's bonus AD ratio because it makes it really difficult to fight champions with both Exhaust and high attack speed. However, Exhaust should feel more effective against high attack speed targets because its slow should be more powerful.\n\nWe're doing this by reducing the duration of the slow by 10% but increasing the duration of the debuff that prevents the target from autoattacking by the same amount. Overall, this means that it'll be easier to reach the minimum Attack Speed slow but harder to reach the maximum Attack Speed slow.\n\nAlso, this means Exhaust won't affect attack speed-based champs as much because it'll take more time for the debuff to tick down.\n\nWe'll continue to assess Exhaust and other individual adjustments to hit our goals in the pre-season.]" time="0.367"><properties><property name="score" value="0.0029578016" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0029578 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0029578
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Unemployed people who refuse a job offer will have their benefits cut under Government plans.\n\nThe Government will tighten the conditions which allow unemployed people to refuse work offers.\n\nWork and Income (WINZ) has been told it must provide greater support for people to get into work.\n\nBeneficiaries who refuse a suitable job offer will have their benefits reduced under new measures announced by Social Development Minister Paula Bennett.\n\nREAD MORE:\n\n* Government plans crackdown on parents who won't work\n\n* PM takes aim at beneficiaries who refuse to work\n\n* Thousands of solo parents' benefit slashed under 'tough love' plan\n\n* More sanctions on beneficiaries as Government claims welfare reforms are working\n\n* Benefit sanctions have forced hundreds to quit job search\n\n* Beneficiaries told 'get a job' in get tough letter\n\n* Benefit sanctions 'designed to make you feel like you're doing something wrong'\n\n* No Job? No Benefit.\n\nThere will be exceptions for those who cannot work due to illness or disability, and those in serious financial hardship.\n\nThose who had been receiving a sickness or invalids benefit, such as the invalids benefit, the sickness benefit, or the severe disabilities benefit for at least six months in the past two years, will be exempt from the tougher requirements.\n\nHowever, all job seekers who had been on a sickness benefit for six months or more would be required to actively look for a job, even if they were on a sickness benefit.\n\nThe measures, contained in a Ministry of Social Development discussion paper, would apply to new and existing beneficiaries.\n\nThey would also apply to beneficiaries who are looking after a child under six months old, or a child who is in the "prescribed age range" of six to 12 months, or is aged under two years old.\n\nPeople with children over two years old would be expected to look for work once the youngest child turned two.\n\nBennett said jobseekers needed to be active and look for work, rather than wait to be told what to do.\n\n"We don't think the system is working very well at the moment. The policy is asking for more people to go into paid employment."\n\nThe Government is under pressure to get more people into work, particularly with a labour shortage.\n\nJob vacancies were at a 10-year high, but there were not enough skilled workers to fill them, Work and Income chief executive Glenys Coughlan said.\n\nThere were also not enough job offers to meet the needs of unemployed people, Bennett said.\n\n"We know there are around 28,000 job seekers who have been unemployed for a year or more, and nearly 30,000 unemployed who have been unemployed for at least two years," Bennett said.\n\n"We want to get these people into the workforce."\n\nThe Government's target is for 55 per cent of people aged between 18 and 64 to be in paid work by the end of this year.\n\n"This is a national problem. It's going to require a lot of hard work from all of us to solve it."\n\nThe discussion document is out for public consultation, and the measures are likely to be introduced in September.\n\nIf the measures are adopted, there will be increased reporting requirements, and consequences for not meeting work obligations.\n\nThere will be four levels of compliance measures.\n\n"Where a person is placed at the highest level of compliance with their obligations, it would mean that a person may be subject to reduced or no benefit payments if they are not meeting their obligations," the discussion paper said.\n\nPeople on a benefit would be expected to have regular interviews with a case manager, and have mandatory obligations to get training and development.\n\n"The expectation is that the person will be actively looking for work, and not sitting on the benefit," Bennett said.\n\n"They can say no to jobs, but they will still need to look."\n\nThose who refused a job offer three times would be placed on the work preparation programme. They would be expected to actively look for work, and attend job interviews, if they were suitable for the position.\n\nIf the person did not have a suitable job offer, they would be expected to participate in the work preparation programme.\n\nThose on a benefit who refused to participate in the programme would have their benefit reduced.\n\nWork and Income would also actively seek out job opportunities, and encourage beneficiaries to apply for the jobs.\n\nBennett said the work preparation programme would not be mandatory.\n\nBut "if you have two years of not being in work, you should probably have a little bit of pressure on you to do a little bit more".\n\n"I wouldn't want to see a situation where there was lots of sanctions. I think there will be exceptions."\n\nThe work programme already had a requirement for those who were work-ready to actively seek out work.\n\nThe changes were "very targeted", she said.\n\n"If you've been on a benefit for a long time, we want to make sure you are taking steps to get into work.\n\n"It's about saying to people 'get with it or we'll move you along'."\n\nThe tighter requirements for beneficiaries were part of a wider review of the welfare system.\n\nThe changes could see beneficiaries' obligations reduced if they were taking care of a seriously ill or dying family member.\n\nBut if the sickness was self-inflicted, such as drug and alcohol abuse, there could be tougher requirements.\n\nCoughlan said there was already a work-ready requirement for job seekers, but that it was flexible.\n\n"I think we're not as prescriptive as Australia. I think they're much more prescriptive."\n\nShe said it was important to keep the labour market up to date.\n\n"That's part of our focus, to make sure that we've got the market that matches up with the right skills."\n\nThere had already been a move towards a more results-based approach, she said.\n\n"We're already in the business of 'what are the outcomes for the people we serve'?"\n\nThe discussion document said the proposed measures would help reduce the number of beneficiaries, while supporting those who were genuinely unable to work.\n\n"It is proposed that these policy changes will provide a tighter fit between the requirements for beneficiaries to engage in paid work, and the exceptions to those requirements," it said.\n\nThe new measures are part of the Government's welfare reforms.\n\n"There is a real concern that people are falling out of the benefit system. We]" time="0.597"><properties><property name="score" value="0.625633125" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Filth was first made into a play for the BBC\u2019s series of television plays in 2003, featuring Ewan McGregor, as a detective called Bruce Robertson. I don\u2019t think it\u2019s too far fetched to say that Bruce is the Scottish version of Neil Buchanan in American Psycho. Not necessarily in terms of the content of the story, but in the sheer fact that he is a very messed up guy, one who people can\u2019t stand, but at the same time can\u2019t stop looking at him.\n\nThis character is played to perfection by Jonny Lee Miller in the new film adaptation of Filth. The novel follows Bruce Robertson (Miller) a detective who, after starting the story off as a drunken, bitter asshole, finds out that he has cancer and so takes leave to get himself checked out. This action in turn leads to Bruce discovering that he is actually a massive pervert. He becomes obsessed with performing the most unspeakable of actions in order to be like the perverts that he so despises. The film follows Bruce as he conducts an investigation to find the person responsible for him being a terrible person and while he is still struggling with his illness.\n\nWhat is great about this adaptation is that it keeps the nastiness and the gritty, unpleasant content that is in the book. That might be what stops this film from being a complete success because this film is a difficult watch. It\u2019s not so difficult because of the content but because you will be so incredibly frustrated by the main character. He is an unpleasant person who you don\u2019t want to spend time with.\n\nIt\u2019s a testament to Miller\u2019s performance that he makes you want to keep watching even though you can\u2019t stand him. It\u2019s this nastiness that he exudes that makes him so engaging to watch. You will want to know how his investigation turns out and what his next move is, because he is truly awful. It also helps that he looks incredibly creepy, like he would kill someone at the slightest provocation.\n\nBruce is helped by a fantastic supporting cast. Jon Skellern plays Bruce\u2019s best friend Simon. You can tell that Simon has his concerns for Bruce and that his concern for him will only continue to grow as Bruce\u2019s behaviour becomes worse. Simon acts as the voice of reason when it comes to Bruce and does his best to help him, only to be shut down by Bruce\u2019s barbs and by Bruce himself. Kelly Macdonald plays Bruce\u2019s wife Susan. While Bruce gets into scrapes with his fellow detectives, Susan is struggling to cope with him and his illness. It\u2019s obvious that Susan is struggling with her husband\u2019s condition, and you will feel for her throughout the film.\n\nThere are a lot of big names in this film that will be recognisable to most people. Jonny Lee Miller, so good as Sherlock Holmes, plays Bruce with a brilliant blend of ferocity and uncertainty. While he is fully committed to the disgusting nature of his character, he also seems like he could completely lose it at any minute. Stephen Fry is outstanding as Inspector Siobhan Clarke, who is one of the few people who is able to make Bruce think twice about the things he does. Everyone is perfectly cast and help to make this film feel incredibly authentic.\n\nThe film does do a good job of adapting the book. Although the source material is sometimes over the top, the film takes that feeling and amplifies it to the next level. What is great about this film is that you do believe that all the characters are real people. You get a real sense of the community that Bruce has around him and that is what helps to make the film so engaging. You want to know what is going to happen to Bruce and how he is going to get out of the situations that he has put himself into.\n\nFilth is a good adaptation of the novel by Irvine Welsh. It does have the same nastiness that is in the novel, which is great for those of you who enjoy watching people doing things that you shouldn\u2019t be watching. The acting is excellent, with a standout performance from Jonny Lee Miller, who takes the idea of a horrible person to a whole new level. It\u2019s not the most pleasant of films to watch, but it\u2019s certainly one of the most engaging.]" time="0.289"><properties><property name="score" value="0.03332567" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03332567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03332567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This board was created for the discussions of Nintendo's two major flagship gaming systems, the Nintendo DS and the Nintendo Wii. Some discussion about previous Nintendo systems is also welcome, but as always please try to keep the conversation in the current console's area.\n\n\n\nNext Display topics from previous: All Topics 1 day 7 days 2 weeks 1 month 3 months 6 months 1 year Sort by Author Post time Replies Subject Views Ascending Descending\n\nReturn to Board index\n\nJump to: Select a forum ------------------ Forums Info & Announcements Read me first! Hints & Tips Gaming Marketplace Recommended Source Books Role Playing - Tales of The Mind Forums Games & RPG Rules The Sinister Spire Promethean: The Created The Dreaming Stone Vampire: The Masquerade Werewolf: The Apocalypse Exalted: The Emerald Dawn Wraith: The Oblivion Promethean: The Created Wraith: The Oblivion Promethean: The Created 3rd Edition Promethean: The Created 2nd Edition Werewolf: The Apocalypse Vampire: The Masquerade Werewolf: The Apocalypse Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Promethean: The Created Wraith: The Oblivion Vampire: The Masquerade Wraith: The Oblivion Vampire: The Masquerade Werewolf: The Apocalypse Vampire: The Masquerade Exalted: The Emerald Dawn Werewolf: The Apocalypse Exalted: The Emerald Dawn Vampire: The Masquerade Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Promethean: The Created Vampire: The Masquerade Werewolf: The Apocalypse Exalted: The Emerald Dawn Vampire: The Masquerade Promethean: The Created Werewolf: The Apocalypse Promethean: The Created 2nd Edition Werewolf: The Apocalypse Exalted: The Emerald Dawn Wraith: The Oblivion Promethean: The Created 3rd Edition Werewolf: The Apocalypse Promethean: The Created Werewolf: The Apocalypse Exalted: The Emerald Dawn Vampire: The Masquerade Promethean: The Created 2nd Edition Vampire: The Masquerade Promethean: The Created 3rd Edition Vampire: The Masquerade Exalted: The Emerald Dawn Werewolf: The Apocalypse Exalted: The Emerald Dawn Werewolf: The Apocalypse Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Promethean: The Created Vampire: The Masquerade Promethean: The Created Werewolf: The Apocalypse Werewolf: The Apocalypse Promethean: The Created Exalted: The Emerald Dawn Wraith: The Oblivion Vampire: The Masquerade Promethean: The Created 3rd Edition Vampire: The Masquerade Vampire: The Masquerade Exalted: The Emerald Dawn Promethean: The Created 2nd Edition Werewolf: The Apocalypse Promethean: The Created Werewolf: The Apocalypse Exalted: The Emerald Dawn Vampire: The Masquerade Vampire: The Masquerade Exalted: The Emerald Dawn Promethean: The Created Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Promethean: The Created Exalted: The Emerald Dawn Werewolf: The Apocalypse Vampire: The Masquerade Vampire: The Masquerade Exalted: The Emerald Dawn Promethean: The Created 2nd Edition Werewolf: The Apocalypse Vampire: The Masquerade Wraith: The Oblivion Werewolf: The Apocalypse Vampire: The Masquerade Wraith: The Oblivion Promethean: The Created Exalted: The Emerald Dawn Werewolf: The Apocalypse Vampire: The Masquerade Promethean: The Created 3rd Edition Wraith: The Oblivion Werewolf: The Apocalypse Vampire: The Masquerade Promethean: The Created Wraith: The Oblivion Vampire: The Masquerade Exalted: The Emerald Dawn Vampire: The Masquerade Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Exalted: The Emerald Dawn Werewolf: The Apocalypse Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Promethean: The Created Exalted: The Emerald Dawn Werewolf: The Apocalypse Wraith: The Oblivion Promethean: The Created Werewolf: The Apocalypse Vampire: The Masquerade Vampire: The Masquerade Promethean: The Created 3rd Edition Werewolf: The Apocalypse Vampire: The Masquerade Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Promethean: The Created 2nd Edition Vampire: The Masquerade Promethean: The Created Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Promethean: The Created Wraith: The Oblivion Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Vampire: The Masquerade Exalted: The Emerald Dawn Werewolf: The Apocalypse Werewolf: The Apocalypse Vampire: The Masquerade Exalted: The Emerald Dawn Promethean: The Created 2nd Edition Vampire: The Masquerade Promethean: The Created Vampire: The Masquerade Exalted: The Emerald Dawn Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Promethean: The Created 3rd Edition Werewolf: The Apocalypse Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Vampire: The Masquerade Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Vampire: The Masquerade Vampire: The Masquerade Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Wraith: The Oblivion Vampire]" time="0.597"><properties><property name="score" value="0.001503788" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Each year, the Duluth News Tribune names a Great Duluthian. This year's Great Duluthian is Bernie Betz, founder and president of Betz Equipment.\n\nBetz, an avid hunter and fisherman, is not only a successful business man, he is a giver. His Betz Family Foundation has donated over $5 million to various organizations and projects, including Duluth's Discovery Center and the Betz Sportsman's Club, which has operated since 1948.\n\n"It has been a real honor to know Bernie, work with him, and to benefit from his support," says John Stowe, president and CEO of the Duluth Entertainment Convention Center (DECC).\n\nIn his acceptance speech, Betz shared a quote from Henry Ford: "If you think you can do a thing, or if you think you can't do a thing, you're right." Betz says he tries to follow this philosophy in all aspects of his life.\n\nBetz said that there are too many good people in Duluth to name one "Great Duluthian," but he humbly accepted the award. "This is just a thank you," Betz said. "I thank you for this."]" time="0.308"><properties><property name="score" value="0.47871405" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.47871405 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.47871405
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Le lancement de Canon EOS M5 est imminent et pour ce faire, la soci\xe9t\xe9 nippone lance sur les r\xe9seaux sociaux une campagne marketing ax\xe9e autour de la qualit\xe9 des vid\xe9os. Un teaser se prom\xe8ne donc sur la toile d\u2019apr\xe8s laquelle le bo\xeetier serait capable de filmer dans une r\xe9solution 4K (passe de 2,7K).\n\nLes qualit\xe9s vid\xe9o d\u2019un bo\xeetier d\xe9termin\xe9es par la r\xe9solution de l\u2019enregistrement de la vid\xe9o. La baisse de la r\xe9solution ne signifie pas pour autant que la qualit\xe9 diminue : on peut avoir une r\xe9solution 4K pour une vid\xe9o en HD, ou inversement.\n\nEt de toute \xe9vidence, la r\xe9solution 4K de la vid\xe9o de Canon EOS M5 semble plus qu\u2019une simple rumeur. Et c\u2019est un scoop ? Pas vraiment puisque le constructeur avait annonc\xe9 que son prochain compact avait la capacit\xe9 de filmer en 4K il y a un an. Et pour une raison qui n\u2019est pas claire, la marque nippone a tout simplement gard\xe9 ce secret.\n\nUne r\xe9solution 4K a de quoi attirer les foules, et surtout les utilisateurs d\u2019appareils photo. En effet, la 4K constitue aujourd\u2019hui un format de r\xe9f\xe9rence, \xe0 l\u2019instar de la r\xe9solution Full HD. Cela dit, la 4K n\u2019est pas forc\xe9ment un avantage pour un bo\xeetier de ce type, mais plut\xf4t pour les bo\xeetiers d\u2019entr\xe9e de gamme ou de milieu de gamme.\n\nCanon EOS M5 : plusieurs versions ?\n\nLa r\xe9solution 4K, comme l\u2019explique Dpreview, est un atout dans le cas des fabricants de bo\xeetiers car ceux-ci peuvent d\xe8s lors proposer des machines \xe0 un prix bas et vendre ensuite des objectifs (propres \xe0 l\u2019appareil ou non) \xe0 prix plus \xe9lev\xe9.\n\nCanon EOS M5 a beau \xeatre attendu au tournant, il ne faudra toutefois pas s\u2019attendre \xe0 ce que l\u2019appareil soit dot\xe9 d\u2019une stabilisation des images. Le bo\xeetier ne semble en effet pas disposer d\u2019une stabilisation optique d\u2019image, alors que la concurrence (compacts compris) poss\xe8de d\xe9sormais un syst\xe8me de stabilisation optique.]" time="0.306"><properties><property name="score" value="1.7256624" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.7256624 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.7256624
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[// Use of this source code is governed by a BSD-style license that can be\n\n// Check if the field is initialized or not\n\n// Determine the kind of path to use\n\n// Generate the path from the module name, directory and field name.\n\n// Module name comes first, to keep a consistant ordering between native\n\n// native method code and java/native method code, to allow for more readable\n\n// Remove 'this' parameter from the function declaration\n\n// If the arguments are references (ie. the passed in argument is a local\n\n// variable), mark the parameter as read only.\n\n// If there is a non-factory constructor, use it\n\n// Always use the default constructor\n\n// A non-null `type` value, or `value` with a type annotation,\n\n// means that we are constructing a type.\n\n// Use the native constructor if it exists, otherwise fall back to\n\n// Use the name of the class as the default constructor name.\n\n// Check if a constructor exists on the type\n\n// If the value is a reference, use the name of the field.\n\n// Use the default constructor name for a value.\n\n// If the value is a reference, use the name of the field.\n\n// If a type is specified (name or value), it takes precedence.\n\n// If we have a type annotation on the parameter, it must match the type\n\n// If we have a name annotation on the parameter, it must match the name\n\n// Use the name of the class as the constructor name\n\n// If we have a type annotation on the parameter, it must match the type\n\n// If we have a name annotation on the parameter, it must match the name\n\n// Don't check for annotation matches in constructors.\n\n// Try to use the field name as a constructor name\n\n// If there is a non-factory method, use it\n\n// Always use the default constructor\n\n// A non-null `type` value, or `value` with a type annotation,\n\n// means that we are constructing a type.\n\n// Use the native constructor if it exists, otherwise fall back to\n\n// Use the name of the class as the default constructor name.\n\n// Check if a constructor exists on the type\n\n// If the value is a reference, use the name of the field.\n\n// Use the default constructor name for a value.\n\n// If the value is a reference, use the name of the field.\n\n// If a type is specified (name or value), it takes precedence.\n\n// If we have a type annotation on the parameter, it must match the type\n\n// If we have a name annotation on the parameter, it must match the name\n\n// Use the name of the class as the constructor name\n\n// If we have a type annotation on the parameter, it must match the type\n\n// If we have a name annotation on the parameter, it must match the name\n\n// Don't check for annotation matches in constructors.\n\n// Try to use the field name as a constructor name\n\n// If there is a non-factory method, use it\n\n// Always use the default constructor\n\n// A non-null `type` value, or `value` with a type annotation,\n\n// means that we are constructing a type.\n\n// Use the native constructor if it exists, otherwise fall back to\n\n// Use the name of the class as the default constructor name.\n\n// Check if a constructor exists on the type\n\n// If the value is a reference, use the name of the field.\n\n// Use the default constructor name for a value.\n\n// If the value is a reference, use the name of the field.\n\n// If a type is specified (name or value), it takes precedence.\n\n// If we have a type annotation on the parameter, it must match the type\n\n// If we have a name annotation on the parameter, it must match the name\n\n// Use the name of the class as the constructor name\n\n// If we have a type annotation on the]" time="0.337"><properties><property name="score" value="0.00063005235" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Why won't anyone on the Senate Banking Committee acknowledge that debt restructuring is needed for the Puerto Rico debt crisis to be solved? I just spent about two hours on CSPAN watching the Committee's hearings about Puerto Rico. Not once was the possibility of debt restructuring, which would mean debt reduction, mentioned. All that was mentioned was higher taxes, pension cuts, and deep government spending cuts, on top of what Puerto Rico is already doing. A complete deadlock. Puerto Rico has been austerity-impaired for a long time now, and has experienced a 12% drop in GDP as a result. No one can grow their way out of debt. Yet, even with this depression-like economy, Puerto Rico is still paying a huge amount of its income to its creditors. A lot of that debt comes from bonds that the government of Puerto Rico sold to investors to get the money to cover the huge losses that its electricity monopoly incurred because of oil price spikes. The government still has no way to fix that, since electricity is now being generated by private companies, due to a privatization law passed in 2013. The government of Puerto Rico could offer a debt exchange to investors, swapping the current bonds for ones with a longer maturity date and a lower interest rate, and then reinvest the proceeds into infrastructure projects, where it has a big deficit. But that possibility is completely ruled out. On the other side, the creditors are as intransigent as ever. They claim they can sue the US government if it tries to change their contracts, which is not true. They also claim that Puerto Rico is defaulting on its debt already, which is also not true. The government of Puerto Rico has been paying its creditors 100 cents on the dollar. There is simply no default risk. This is all a huge waste of time. All that the Puerto Rico hearings did was show that the US Congress is not capable of doing what it should have done long ago: allow Puerto Rico to restructure its debts. That would have given Puerto Rico a fresh start, and the creditors would have ended up with their money back. And we would have avoided all this useless talking. Now, we are just wasting time and making the situation worse. Puerto Rico's economy continues to decline. Puerto Rico's economy is expected to contract again by at least 1% in 2016, and another 2% in 2017. Most of the business owners I interviewed in Puerto Rico last month said they expect business to get worse in 2017. So the longer the creditors keep Puerto Rico in this situation, the worse it will get. In the hearings today, several senators brought up a resolution that the House of Representatives passed yesterday in a partisan vote, saying that Puerto Rico is already in default. That resolution is just to make a political point. The Supreme Court has already ruled that Puerto Rico cannot declare bankruptcy like a US municipality can, and cannot restructure its debt in a court. This was because of a law that was passed in 1984. The US Congress could have changed this law a long time ago, but they did not. The Republicans in the House of Representatives, however, do not want to restructure Puerto Rico's debts. Instead, they are trying to force the government of Puerto Rico to do all the reforms it already is doing, without giving it the opportunity to do the debt restructuring that will put its economy back on track. This was not really mentioned in the Senate hearings, but I found out from reporters that the Democrats on the Senate Banking Committee are not going to move forward with the House resolution. They understand that it is not going to pass. We need Congress to pass the resolution anyway, just to show that it has bipartisan support. In the House hearings, Representative Sean Duffy of Wisconsin said, "This is not an emergency." This is a statement that no one in Puerto Rico agrees with. By delaying the debt restructuring, the economy of Puerto Rico is getting worse. More people are moving to the US mainland, which will further reduce the income that Puerto Rico is able to collect in taxes. More people are being forced to do cash jobs in the underground economy, because they cannot find other jobs. And those jobs do not get reported to the government. The longer this process is delayed, the worse it will get. But the creditors and some members of Congress do not seem to understand that Puerto Rico needs a fresh start. So they will continue to waste time, talking about things that are already being done, without any hope of any positive outcome. Puerto Rico's creditors just don't want to take a loss. But we are not doing Puerto Rico any favors by letting this situation continue for so long.]" time="0.344"><properties><property name="score" value="0.00902413" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00902413 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00902413
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[President Trump got into a heated exchange with CNN White House correspondent Jim Acosta at his press conference on Thursday, calling the reporter \u201cfake news\u201d and challenging his network\u2019s reporting.\n\nBut Trump\u2019s son, Eric Trump, says the president will always be fair and give all reporters the time of day.\n\nIn an appearance on Fox News\u2019 \u201cMedia Buzz,\u201d Eric said Trump may attack CNN but always makes time for the network\u2019s reporters.\n\n\u201c[T]hey can still come in. The reporter that he did call on [at the press conference], we always give them an opportunity at every press conference. He\u2019s always going to be fair,\u201d he said.\n\nADVERTISEMENT\n\n\u201cHe\u2019s always going to give them an opportunity, but we\u2019re not going to let them take potshots at our president and our administration,\u201d Eric Trump added.\n\nEric Trump also predicted that eventually the president will win the fight against \u201cfake news\u201d in the mainstream media.\n\n\u201cMy father is a fighter, and he\u2019s an unbelievable person. I mean, he\u2019s built an unbelievable business, and he\u2019s built an unbelievable life. He\u2019s a person that\u2019s been elected to lead this country, and he\u2019s going to do it with or without the media. He\u2019s going to do it with or without certain networks. And it\u2019s sad because he\u2019s such a good man, and he\u2019s such a good father,\u201d Eric Trump said.\n\n\u201cBut at the same time, if they\u2019re going to put themselves in a position where they\u2019re going to be speaking so much, they\u2019re going to continue to make mistakes,\u201d he added.]" time="0.332"><properties><property name="score" value="0.011110187" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01111019 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01111019
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This is not a bug or something that is wrong. The game is not detecting your Shield as something that it can block. The animation itself looks fine. I don't know how you can replicate it yourself to get a screenshot, but what you are seeing is the default Shieldblock animation without your Shield in your inventory.\n\n\n\nIf you are referring to the broken animation for Normal and Magic Shieldblock, the bug with that is fixed on 0.11.4. I'm not sure when we'll be able to patch that for Ascendancy. Last edited by Mark_GGG on Nov 11, 2015, 8:54:36 AM Posted by Mark_GGG\n\non Grinding Gear Games on Quote this Post\n\nI mean my shield is in my inventory and the character can block while using the skill.\n\n\n\nThat's what I mean about not being a bug.\n\n\n\nIf it's a game mechanic that can be prevented somehow that would be really helpful to know. Posted by Greendogo\n\non on Quote this Post\n\n" Greendogo\n\n\n\nThat's what I mean about not being a bug.\n\n\n\nIf it's a game mechanic that can be prevented somehow that would be really helpful to know. I mean my shield is in my inventory and the character can block while using the skill.That's what I mean about not being a bug.If it's a game mechanic that can be prevented somehow that would be really helpful to know.\n\nThe game can't detect your shield. When you block, the shield is on your back. When you use your shield in the skill, it isn't. The game can't detect your shield. When you block, the shield is on your back. When you use your shield in the skill, it isn't. Posted by Mark_GGG\n\non Grinding Gear Games on Quote this Post\n\n" Mark_GGG " Greendogo\n\n\n\nThat's what I mean about not being a bug.\n\n\n\nIf it's a game mechanic that can be prevented somehow that would be really helpful to know. I mean my shield is in my inventory and the character can block while using the skill.That's what I mean about not being a bug.If it's a game mechanic that can be prevented somehow that would be really helpful to know.\n]" time="0.353"><properties><property name="score" value="0.0016678318" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Uninstall all Office add-ins in Office 365\n\nIn this article\n\nWhen you install an Office add-in, you will be able to see the add-in in the Add-ins page in Word, Excel, or PowerPoint. However, it is not the case that you can only install add-ins from this location. In fact, you can add any website to the browser toolbar, and install a specific add-in from there.\n\nThis article describes the steps to completely uninstall all add-ins from all Office applications that you have in your tenant. This will allow you to completely remove all Office add-ins from your Office 365 tenant. This can be useful in a tenant cleanup or a company migration.\n\nImportant Before following the instructions in this article, please verify that your Office 365 subscription has the add-in licensing model and that the Tenant admin has permissions to run PowerShell scripts.\n\nIf you have any questions or feedback, please let us know in the Q&A section on this page.\n\nManual process\n\nUse the following steps to completely uninstall all Office add-ins from all Office applications that you have in your tenant.\n\nImportant Before following the instructions in this article, please verify that your Office 365 subscription has the add-in licensing model and that the Tenant admin has permissions to run PowerShell scripts.\n\nOpen the SharePoint Online Management Shell. Run the following command: Get-PnPUtilization | Remove-PnPUtilization To remove the add-ins from Word, Excel, and PowerPoint, run the following commands: Get-PnPUtilization | ? {$_.Product -like "*Word*"} | Remove-PnPUtilization Get-PnPUtilization | ? {$_.Product -like "*Excel*"} | Remove-PnPUtilization Get-PnPUtilization | ? {$_.Product -like "*PowerPoint*"} | Remove-PnPUtilization To remove the add-ins from Outlook, run the following commands: Get-PnPUtilization | ? {$_.Product -like "*Outlook*"} | Remove-PnPUtilization\n\nPowerShell script\n\nThe following PowerShell script will completely uninstall all Office add-ins from all Office applications that you have in your tenant.\n\nImportant Before following the instructions in this article, please verify that your Office 365 subscription has the add-in licensing model and that the Tenant admin has permissions to run PowerShell scripts.\n\n# run as SharePoint Administrator $spAdmin = [Microsoft.SharePoint.Administration.SPAdminService]::GetAdmin # Connect to the SharePoint Online Management Shell $webApp = Get-SPWebApplication "https://<your_tenant_name>.sharepoint.com" $w = $webApp.LoginPage $w.ReturnUrl = $w.Url.AbsoluteUri + "/_layouts/15/ PowerShell -ApplicationPage.aspx" $cred = Get-Credential $credential = $spAdmin.Credentials.GetNetworkCredential($cred.UserName, $cred.Password) $session = New-PSSession -ConfigurationName Microsoft.Exchange -ConnectionUri https://ps.outlook.com/powershell/ -Credential $cred -Authentication Basic -AllowRedirection Import-PSSession $session -CommandName "Remove-PnPUtilization" -AllowClobber $excel = Get-PnPUtilization | ? {$_.Product -like "*Excel*"} | Remove-PnPUtilization $word = Get-PnPUtilization | ? {$_.Product -like "*Word*"} | Remove-PnPUtilization $powerpoint = Get-PnPUtilization | ? {$_.Product -like "*PowerPoint*"} | Remove-PnPUtilization $outlook = Get-PnPUtilization | ? {$_.Product -like "*Outlook*"} | Remove-PnPUtilization Remove-PSSession $session\n\nNote In the PowerShell script, you can run the commands individually to remove a specific add-in for a specific Office application, or you can remove all Office add-ins by running the Remove-PnPUtilization cmdlet without any parameters.\n\nAdditional information\n\nLearn more about how to remove a specific add-in for a specific Office application\n\nLearn more about how to add or remove an Office add-in in Office 365\n\nLearn more about the SharePoint Online Management Shell]" time="0.365"><properties><property name="score" value="0.00899187" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Shepard and his team have done it again. I've been a fan of "American Chopper" since day one. I used to get angry with Paul Sr. for the way he treated the guys but I guess that was part of the show's draw. I have never seen a father and son fight like that on TV before. I still hope he comes back someday to work with his son, and they can rebuild the relationship they had before. I can't say enough good things about this season of American Chopper, with all the good work the team did for cancer patients, this is one of the most memorable seasons of the series.\n\nThe creativity of the builds is incredible. I'm so glad that they were able to get the Ford back on the road after the fire. They did an amazing job on the bike itself and the amount of work they put into making sure everything was functional on the bike, even the brakes, was inspiring. The customization they did on the ambulance was pretty impressive as well, especially how they made sure all the hydraulic and electrical components worked correctly. I also loved the idea of doing a bike with a hunting theme and the amount of work they put into making the motorcycles look like they belonged to an entire hunting party was great. They did an amazing job on the bike that played homage to the military and even the Great American motorcycle show was awesome! The barber shop bike and "Appalachian Outlaw" motorcycle were just as awesome. The personal touches that were put on these bikes really made them so much better.\n\nI know a lot of people criticize the shows for not showing the whole building process, but in my opinion, I like to see the creativity that the builders put into the bikes. The shows are a lot more enjoyable when I see what goes on in their heads when they come up with their ideas.]" time="0.400"><properties><property name="score" value="0.054878455" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The drama of the week is all about the inability of a local physician to get paid by insurance companies. It is not an uncommon story in that many physicians cannot get paid by insurance companies for a variety of reasons. The difference in this story is that this physician not only tried to get paid, but took the insurance company to court to try to get paid.\n\nIt started when a physician sent an invoice to an insurance company for services rendered. The physician was told that the insurance company did not have the funds to pay the invoice and that they would pay the bill at a later date. The physician sent the insurance company a bill every month for about a year until the insurance company stopped communicating. The physician was then advised by a collection agency that if he wanted to be paid, he would have to take the insurance company to court.\n\nThe physician then did just that. He filed a claim with the District Court seeking the unpaid bill plus interest and costs. The insurance company tried to have the case dismissed by claiming the physician did not have standing to sue. The insurance company argued that the physician only had a contractual right to be paid, but that right had not been breached. They also argued that he could not have been damaged by their failure to pay since it was their money.\n\nThe physician won the case. He was awarded the $10,600 plus interest and costs. The judge agreed that the insurance company breached the contract when it failed to pay the bill. The judge also found that the insurance company's withholding of payment did cause the physician to suffer damages in the form of legal fees to pursue payment.\n\nAs for the insurance company, it is probably a good idea that they got caught. Since their contract was breached and they caused damages, they may be liable for punitive damages which could double the amount of the doctor's claim.]" time="0.341"><properties><property name="score" value="0.028620651" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Google+ on pakotettu entist\xe4 tiukempaan sis\xe4ll\xf6ntuotantoon, kertoo TechCrunch. My\xf6s yhti\xf6n taloudelliset resurssit k\xe4rsiv\xe4t j\xe4\xe4dytyksist\xe4.\n\nLue my\xf6s Google jatkaa keskittymist\xe4 Androidiin\n\nYhti\xf6 aikoo t\xe4sment\xe4\xe4, ett\xe4 j\xe4rjestelm\xe4 ei ole en\xe4\xe4 pelkk\xe4 verkkopalvelu, vaan tiettyyn sis\xe4ll\xf6ntuotantoa vaativaan verkkopakettiin. Verkkopalvelua varten tarvittavat julkaisuprofiilit, lis\xe4\xe4ntyneet palvelut ja Google Play -sovelluskaupan julkaisut ovat poistumassa.\n\nMy\xf6s Googlen lis\xe4\xe4ntyv\xe4t kulut verkkosivujen uudistamisesta kertoivat sis\xe4ll\xf6ntuotannon lis\xe4\xe4ntymisest\xe4. Tuotanto lis\xe4\xe4ntyi Googlen julkistaman ensimm\xe4isen raportin mukaan vuoden 2011 ensimm\xe4isest\xe4 nelj\xe4nneksest\xe4 vuoden 2013 ensimm\xe4iseen nelj\xe4nnekseen verrattuna 10 prosentilla, ja sis\xe4ll\xf6ntuotannon kustannukset kasvoivat samana aikana 48 prosenttia.\n\nGooglen taloudellisen kirjanpidon lukujen perusteella Google+ sai my\xf6s viime vuonna entist\xe4 korkeammat resurssit, mutta kulujen kasvattaminen vaikutti j\xe4\xe4dytykseen.\n\nGoogle on jo aiemmin keskitt\xe4nyt ty\xf6voimansa Android-k\xe4ytt\xf6j\xe4rjestelm\xe4\xe4n, ja samankaltainen kehitys voi my\xf6s Google+:n osalta olla tulossa.]" time="0.349"><properties><property name="score" value="0.0673588" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[the belief or doctrine that the universe is eternal and has no beginning or end.\n\nthe belief or doctrine that the universe is eternal and has no beginning or end.\n\na worldview, esp. in ancient India, that denies all distinctions between spirit and matter.\n\nthe doctrine that the universe is infinite and without beginning or end.\n\nthe doctrine that the universe is infinite and without beginning or end.\n\na form of pantheism that assumes the presence of god as a force or energy pervading the universe.\n\nthe belief that the universe is eternal and has always existed.\n\nthe belief that the universe is eternal and has always existed.\n\nthe doctrine that there is only one god.\n\na philosophy that stresses the unity and continuity of existence.\n\na philosophy that stresses the unity and continuity of existence.\n\nthe philosophical doctrine that there are no immaterial or transcendent entities, such as God or the soul, but that all phenomena of reality may be accounted for by material means.\n\na philosophy holding that truth is apprehended by intuition and not by reason.\n\nthe doctrine that God is not a person but an impersonal principle that accounts for the universe.\n\nthe doctrine that the universe is not a personal, creative agent but a blind, orderly, insensible machine.\n\nthe philosophical doctrine that the universe is not a personal, creative agent but a blind, orderly, insensible machine.\n\nthe doctrine that natural phenomena have no supernatural explanation.\n\na doctrine that is similar to pantheism but is regarded as more fundamental, asserting the essential unity of the universe.\n\nthe doctrine that God, nature, and humanity are not distinct entities but are one.\n\nthe belief that the universe is an organic unity, with every person and event affecting every other.\n\nthe belief that the universe is an organic unity, with every person and event affecting every other.\n\na worldview positing that all life and existence is inseparable from the interdependent parts of the whole.\n\nthe belief that there is an undying and immaterial part of man, esp. the soul.\n\nthe belief that there is an undying and immaterial part of man, esp. the soul.\n\nthe belief that there is a common and universal religious or moral experience in every person.\n\nthe belief that there is a common and universal religious or moral experience in every person.\n\nthe theory that all existing things in the world are formed from and constitute a unity with one fundamental substance, esp. matter or spirit.\n\nthe theory that all existing things in the world are formed from and constitute a unity with one fundamental substance, esp. matter or spirit.\n\nthe theory that only material things and properties exist.\n\nthe theory that only material things and properties exist.\n\nthe doctrine that the world and all its phenomena are merely the product of chance and necessity.\n\nthe doctrine that the world and all its phenomena are merely the product of chance and necessity.\n\nthe doctrine that man is no more than a natural product of evolution, with no spiritual aspect.\n\nthe doctrine that man is no more than a natural product of evolution, with no spiritual aspect.\n\na system of principles and practices based on the teachings of a spiritual leader.\n\nthe worship of idols or icons.\n\nthe worship of idols or icons.\n\na religious practice consisting of the use of some object as a focus of worship.\n\na religious practice consisting of the use of some object as a focus of worship.\n\nthe belief that ultimate reality cannot be expressed in ordinary language.\n\nthe belief that ultimate reality cannot be expressed in ordinary language.\n\nthe doctrine that all human beings possess a dual nature and can achieve a transcendent existence.\n\nthe doctrine that all human beings possess a dual nature and can achieve a transcendent existence.\n\nthe doctrine that only moral and spiritual values are real.\n\nthe doctrine that only moral and spiritual values are real.\n\na belief in the existence of a soul as an immaterial entity distinct from the body.\n\na belief in the existence of a soul as an immaterial entity distinct from the body.\n\nthe doctrine that knowledge is impossible.\n\nthe doctrine that knowledge is impossible.\n\nthe belief that everything is the result of chance.\n\nthe belief that everything is the result of chance.\n\nthe doctrine that all matter is intrinsically evil and that human existence is a burden imposed upon men by evil spirits.\n\nthe doctrine that all matter is intrinsically evil and that human existence is a burden imposed upon men by evil spirits.\n\nthe doctrine that knowledge is merely a by-product of learning and not a result of the processes of the mind.\n\nthe doctrine that knowledge is merely a by-product of learning and not a result of the processes of the mind.\n\nthe doctrine that God is unknowable and that religious truth can be attained only through intuition and inner experience.\n\nthe doctrine that God is unknowable and that religious truth can be attained only through intuition and inner experience.\n\nthe doctrine that life is an illusion and death is the reality.\n\nthe doctrine that life is an illusion and death is the reality.\n\nthe doctrine that the universe is composed of a single substance, such as matter or spirit, and that all things are modifications of this basic substance.\n\nthe doctrine that the universe is composed of a single substance, such as matter or spirit, and that all things are modifications of this basic substance.\n\nthe belief that all phenomena and events in the world are determined by necessary laws and have their causes in previous events.\n\nthe belief that all phenomena and events in the world are determined by necessary laws and have their causes in previous events.\n\nthe doctrine that matter and its motions are eternal and that God, if he exists, is wholly immanent in the world.\n\nthe doctrine that matter and its motions are eternal and that God, if he exists, is wholly immanent in the world.\n\na group of people sharing religious convictions.\n\na group of people sharing religious convictions.\n\nthe doctrine that the world is an aggregate of self-existent individuals.\n\nthe doctrine that the world is an aggregate of self-existent individuals.\n\na philosophy that identifies religion with a specific moral system.\n\nthe belief that knowledge of an eternal reality is gained through intuition.\n\nthe belief that knowledge of an eternal reality is gained through intuition.\n\nthe belief that a divine or other transcendent power has sovereignty over the universe.\n\nthe belief that a divine or other transcendent power has sovereignty over the universe.\n\na comprehensive system of political, economic, and social organization.\n\nthe practice of worshiping with songs, prayers, and other gestures in addition to rites and ceremonies.\n\nthe practice of worshiping with songs, prayers, and other gestures in addition to rites and ceremonies.\n\nthe doctrine that truth is gained through study and contemplation.\n\nthe doctrine that truth is gained through study and contemplation.\n\nthe theory that all qualities in the human mind are relative to the situation in which they are encountered.\n\nthe theory that all qualities in the human mind are relative to the situation in which they are encountered.\n\nthe belief that the divine spark of reason is in all human beings.\n\nthe belief that the divine spark of reason is in all human beings.\n\n]" time="0.686"><properties><property name="score" value="0.012441223000000001" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In my world it's important to be organized. Especially when you live with more than two people, which I do. Most of the time, everything is on a schedule. No one is allowed to eat at 11pm unless they're hungry. Everyone is not allowed to leave dirty dishes in the sink unless they're at work. If you're working out at a certain time, you have to shower. No one can go outside unless it's to throw out the garbage. And so on and so forth.\n\nFor some reason, though, the whole "organization" idea flies right out the window when I'm trying to schedule a trip. I tend to plan things to the day and then get annoyed if something goes wrong or someone else wants to do something that may interfere. I hate it when someone wants to do something at a time that I've already booked for another thing. I feel like I should have priority, especially since I've planned this whole thing and if it were cancelled, I would have to pay for everything anyway.\n\nBut, guess what? I've realized I'm wrong. I've realized that while I may have planned the whole thing, other people need to be included too. And that they deserve a say in what goes on too. Maybe that means they have to drive back a different route to get home or they need to leave an hour earlier to get to their house. Maybe they need to stay later than they would have planned. Or maybe they don't want to leave. And that's ok. It doesn't have to ruin anything.\n\nAs long as everyone is included and has a say, it's all good. It doesn't mean that there won't be stress involved. There will be. I'm not going to lie. We may end up fighting about some things. Or they might leave early, which makes us upset. But at the end of the day, we're still family. We still love each other. We still get to have fun.\n\nI guess what I'm saying is that sometimes, I need to let other people in. To let them have a say in what happens. Otherwise, it will just be me against them. And I'd rather be the bigger person. I'd rather be the one who says "Fine, I'll do it this way" instead of the one who gets in an argument. I don't want to be the one who stays up late crying over something that went wrong and couldn't be avoided.\n\nSo, to sum up my whole blog:]" time="0.361"><properties><property name="score" value="0.014821661" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["Would You Accept A Ridiculously Generous Gift?\n\nThe book, Cults Inside Out, claims to reveal everything you ever wanted to know about cults, from recruiting and controlling techniques to the manipulation of the children of cult members. The book is written by Jeremy Spencer, who claims that his grandfather was a cult leader and that his father was in a cult. It is hoped that by publishing this book that Jeremy Spencer can stop this cycle and prevent any other children from being hurt in this way.\n\nA spokesperson for Jeremy Spencer has confirmed that he is desperately in need of some cash to fund the marketing and promotion of the book. The cost is simply too great to risk doing it alone. He hopes that if he can raise enough money to pay for advertising, then he will be able to share his story and help people.\n\nIf Jeremy Spencer can raise enough money for the book, then he will gift it to the person who donates the most money. The donation can be made via the crowdfunding site Kickstarter.com.\n\nDonating to this crowdfunding campaign is likely to have more benefits than simply receiving a copy of the book. You can be part of the book and even get a speaking part in it. This is a great opportunity to help someone with a great story."\n\nKickstarter is a crowdfunding website that allows you to donate money to people who are trying to raise money for something. In return for your donations, you can receive gifts from the person you are donating to.\n\nWould You Accept A Ridiculously Generous Gift?\n\nA friend of mine contacted me a few months ago to ask if I would consider reviewing a book for them. The book was called Cults Inside Out and the author is called Jeremy Spencer. He has offered to donate the book to the highest bidder.\n\nCults Inside Out is the first of a trilogy and Jeremy Spencer is trying to raise money to self-publish the second book. As part of his plan, Jeremy is offering to donate the book to the highest bidder. The highest bidder is whoever donates the most money to Jeremy's GoFundMe account.\n\nWould you accept a ridiculously generous gift? I decided that I would.\n\nJeremy Spencer is an interesting character. I had never heard of him before and I was sceptical about some of the things that he had to say. Jeremy is a bit of a controversial character and he is no stranger to the press. He is very controversial and he has a history of being sued for libel, but you can find out more about that on his GoFundMe page.\n\nThe book is about cults and how they use manipulation techniques to recruit people into their organisations. The book also talks about the psychology of the cult members and how they get manipulated. There is some fascinating stuff in there and it is an easy read.\n\nThe book starts with the stories of two children who were born into cults. One child was the son of a cult leader and the other child was the daughter of another cult leader. Both children were exposed to extreme forms of cult abuse and you can really feel the pain that they went through.\n\nI didn't really enjoy reading the stories of the two children because it was so sad. You could really feel their pain. I am glad that Jeremy was able to escape the cult, but I don't think that it is an easy thing to do. There are always going to be repercussions, no matter how many years later.\n\nAfter the stories of the two children, Jeremy goes on to talk about the psychology of the cult members. I didn't realise that there were so many different reasons why people join cults. There are a number of factors that can influence the decision to join a cult.\n\nThere are a number of strategies that cults use to recruit new members and Jeremy goes on to discuss the techniques that they use. He talks about how they use manipulation and persuasion techniques to encourage people to join them. Jeremy is not the first person to talk about these strategies, but he does explain them in a very clear way.\n\nJeremy also talks about the different kinds of cults and what they are like. There are religious cults and political cults and there are even business cults. There are all kinds of cults and it is fascinating to read about how they are structured and what they are all about.\n\nJeremy Spencer has also included information about his family and his time in the cult. I have never been in a cult, so I don't know what it is like, but I was impressed with how well Jeremy handled the subject. He didn't talk about the cult in a negative way and he didn't try to make it sound worse than it was.\n\nThere is a lot of information about cults in this book and Jeremy doesn't try to overstate any of the facts. He doesn't try to talk in hyperbole and he gives very factual descriptions of what it is like to be in a cult.\n\nIf you are a fan of cults, then this book is going to be right up your street. If you are just interested in psychology, then this book is also going to be right up your street. There are a lot of interesting theories and a lot of fascinating facts.\n\nThere are a number of interesting stories and you can really feel the emotion in this book. I am glad that I have read it, but I don't think that I will read the rest of the trilogy.\n\nWhat you will get if you make the highest bid\n\nIf you make the highest bid on Jeremy's GoFundMe page, then he will send you a copy of Cults Inside Out. The money that you donate will be used to help with the marketing and promotion of the book.\n\nI have seen people donate large amounts of money to crowdfunding projects, so it is definitely possible. Jeremy is even offering to sign your copy of the book, if you make the highest bid.\n\nThe book is available in paperback and as an e-book. You will also be able to get it in various different languages. It is likely to be available in a number of different countries.\n\nYou can get a signed copy of the book for just $30 and Jeremy has been very generous with his offers. There are some very generous rewards if you can make the highest bid. Jeremy is determined to get this book out and he will give you the opportunity to help him.\n\nIf you are interested in making the highest bid, then click here. If you are interested in reading more about the book, then click here.\n\nWhat are your thoughts about Jeremy Spencer's generosity? Please leave a comment below.\n\nSave\n\nSave\n\nSave\n\nSave]" time="0.716"><properties><property name="score" value="0.033319776" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl['I'd only ever been with two girls'\n\nMany guys worry about their first time having sex \u2013 especially when it comes to having sex for the first time with a girl. How can you be sure she's comfortable? And what should you do if she says no?\n\nHere's how to handle your first time.\n\nGetting ready for the first time\n\nEven though your first time might be really exciting, you need to remember that having sex for the first time can be really awkward.\n\nThis is especially true if you're nervous, so to make it easier for both of you, try to relax, and make sure you're both feeling comfortable and happy to do it. You don't want to be worrying about whether your partner's enjoying it.\n\nThe best way to do this is to talk about it before you get started. Find out what she expects, and what she doesn't. Try to find out how much she knows about sex. It might seem strange to talk about this, but it will make it easier for you both when you get down to it.\n\nYou can talk about contraception too. Both of you should know how you're going to stop pregnancy happening and what to do if it does.\n\nA lot of guys worry about getting their first time over with, but in fact, the longer you take, the more you'll enjoy it. Most girls feel more comfortable the longer it takes. If you try to rush things, you're more likely to make her feel uncomfortable and she might not enjoy it.\n\nWhat if you're with someone new?\n\nIf you're having sex with someone for the first time, you may be nervous. You're not sure what to expect.\n\nYou're likely to be worried that you won't know how to do it properly or that you'll be rubbish in bed. But the fact is, it doesn't matter how good you are. All that matters is that you both enjoy it and that you're safe.\n\nYour worries might make you want to rush things and this might make you less sensitive and not as gentle as you should be. This is especially true if you're with a virgin. She'll be more nervous than you, so make sure you take your time and that you both enjoy it.\n\nYou'll know if she's enjoying it if she shows signs of pleasure, like:\n\nmoaning\n\ngetting very wet (this is the most obvious one!)\n\nshe may make noises or say things to let you know she's enjoying it\n\nremember to look for these signs!\n\nFirst time with a girl: the sex\n\nSex for the first time can be really exciting.\n\nWhat if she says no?\n\nIf your first time involves having sex with a girl, there's a chance she might say no. That's normal. It's important to make sure she's happy to do it. It's your responsibility to make sure she's okay with it and you don't want to do anything that might hurt her or make her feel uncomfortable.\n\nEven if she says yes, she might change her mind when the time comes. This can be a little awkward, especially if you've been going out with her for a while and you've had sex before.\n\nIf this happens, try to deal with it like a man. If you want to take it further, tell her you really want to, but you won't if she's not up for it.\n\nIf she wants to stop, you should respect that. It can happen, even if she's wanted to have sex for a while. If you think she might be pregnant, make sure you take care of that too.\n\nThe actual sex\n\nIt's important that you know how to please a girl, but this is especially important the first time. It will help you build your confidence, and it will also help her enjoy sex more.\n\nHow do you please a girl?\n\nWhat most people think about when it comes to pleasing a girl is what feels good for her. But in fact, what feels good for you is important too. It's the only way you can both enjoy yourselves and have a great time.\n\nBe careful to go slowly. If you go too fast, you might scare her or make her uncomfortable.\n\nWhat if you're not having sex with a virgin?\n\nIf you're not having sex with a virgin, it's unlikely that you'll have to worry about losing your virginity. It's more likely that she will lose hers!\n\nWhen you have sex for the first time, it's still important that you take it slow. It might be even more important because you'll need to show her that you can be gentle and caring. This will make sure she feels comfortable with you. It will also make sure that you have a great time too.\n\nIs she ready for sex?\n\nYou need to know when she's ready to have sex. If you rush it, you could end up doing something that she's not ready for. This could make her feel embarrassed or uncomfortable, which could make you feel embarrassed too.\n\nIf you don't think she's ready, you shouldn't go ahead. That's because it might make her feel like she's not good enough.\n\nJust be patient and make sure you're both happy and comfortable.\n\nYou can help her decide when she's ready for sex by asking her. Ask her what she thinks about having sex. If she says no, respect that, and don't push it.\n\nIf she says yes, talk about what you both think. Ask her if she's ready for it and talk about what you both expect. You'll both feel more relaxed if you know what's going to happen and you're both ready for it.\n\nDon't forget, it's important that you're both ready, not just her!\n\nWhat if you're with a virgin?\n\nSex for the first time can be really scary. But remember, you're both in the same boat and you can help each other through it.\n\nIf you're with a virgin, you need to remember that she's not an expert. It will take her a while to get used to sex and you need to give her time. It will help if you make sure you go slowly.\n\nAs you know, she'll be nervous, so you need to make sure she feels comfortable.\n\nSome girls are really confident and they're great at giving directions. But other girls aren't, so if she needs help, you should be there to help her.\n\nHow do you make sure she's ready?\n\nYou might have to talk about it. You might feel like she's pushing you into having sex, but she might not actually be ready for it.\n\nIf you don't feel comfortable talking to her, you can find out by looking at her. Does she seem relaxed? Is she making the right noises? Is she happy? If she seems happy, you're probably okay.\n\nMake sure you ask her about contraception too. It's important to keep yourself safe, so make sure you both know how you're going to prevent pregnancy.\n\nWhat if you have problems?\n\nSex for the first time can be really scary for some guys. But the good news is that it doesn't have to be.\n\nWhat if you're having trouble getting an erection?\n\nIf you're having trouble getting an erection, it could be that you're nervous. It could also be that you don't feel ready for sex.\n\nIf it's nerves, you should try to relax. Try to take it slowly. You don't want to scare your partner. If you're not ready for sex, then you need to tell her.\n\nIt might help to talk to her about it first. If you think you're ready, but she isn't, you should respect that. You don't want to make her feel bad or make her regret having sex with you.\n\nIt's important that you're both ready for it and that you both feel comfortable. If you're not ready, don't go through with it.\n\nWhat if it doesn't feel right?\n\nSome guys worry about whether they're doing it right. It can be a bit scary if you don't know what to do.\n\nIt's really important that you talk about it. If you think it's not right, you should ask her.\n\nAnd don't worry too much. There's no right way to have sex. The important thing is that both of you are enjoying it and that you're both safe.\n\nIt's really important that you both make sure you're ready for sex. You don't want to go through with it if she's not ready.\n\nIf you're having sex with a virgin, then you need to be more careful. She might not know what she's doing, so it's important that you tell her what you want. You should also tell her if it doesn't feel right.\n\nWhat if it hurts?\n\nIf you're having sex for the first time, there's a chance that it could hurt. But the good news is that this should only happen the first time. If it happens again, you should get help as soon as possible.\n\nYour partner should tell you if it hurts, so you need to listen to her. You should also be able to tell if it hurts. If you can't, then it's not right.\n\nIf it hurts her, then you need to stop and think about what you're doing. It's important that you both know what feels good and what doesn't.\n\nIf you're not sure what to do, then it might be best to practice with a toy. You can use it to find out what she likes and what she doesn't.\n\n]" time="0.858"><properties><property name="score" value="0.00021400572" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Don't miss the return of the Vancouver Stars to the Coast Soccer League. Vancouver Stars. Score-by-Score. W: L. Goal Differential. Offside. Soccer positions (association football) The outfield players are divided into four main categories: forwards, midfielders, defenders, and goalkeepers. A team is composed of eleven players of which.Vancouver Stars - CSL Senior Division - 20.09.2017 - Whitecaps U-23 vs. StarsAway matches Away Score Home Result Date. The players involved with the Whitecaps' Whitecaps have appeared in an international youth match. Vancouver. In , the Whitecaps qualified for the semifinals of the CONCACAF Champions League for the first time after defeating Puerto Rico Islanders in the quarterfinals with a aggregate score of 4\u20143 and Club Tijuana in the semifinals with a aggregate score of 4\u20142. The following season, the Vancouver Whitecaps won their first CSL Championship. TSR: 0.69. MLS Reserves league records: Attendance.\n\nVancouver Whitecaps FC 2. Regular Season Stats. Soccer - BC Soccer Premier League. Soccer Statistics. Each match will be given a score at the end of the match based on the following scoring system: 3 points for a win, 1 point for a tie, and 0 points for a loss. Statistics - College Soccer - Pro/College. From Wikipedia, the free encyclopedia. The number of teams varies in each season. Check out Vancouver vs Ottawa Fury FC live score, video stream and H2H results. Vancouver Whitecaps F.C. (Vancouver Whitecaps or Whitecaps) is a Canadian professional soccer team based in Vancouver, British Columbia, that competes in Major League Soccer. Soccer Statistics - College Soccer - Pro/College. It was created as a reserve team of the MLS side Vancouver Whitecaps FC, in the United Soccer Leagues Premier Development League , the fourth tier of the American Soccer Pyramid, the Canadian Soccer Pyramid. In , the Vancouver Whitecaps won their first CSL Championship. Vancouver Whitecaps FC 2. The following season, the Vancouver Whitecaps won their first CSL Championship. MLS Reserves league records: Attendance. Vancouver Whitecaps FC. Vancouver Whitecaps FC 2.\n\nCoeur dalene hookup:]" time="0.355"><properties><property name="score" value="0.63696665" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.63696665 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.63696665
|
||
assert 'Human' == 'AI'
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||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\xa9 2018 Ontario Real Estate Association. All rights reserved. IDX information is provided exclusively for consumers' personal, non-commercial use and may not be used for any purpose other than to identify prospective properties consumers may be interested in purchasing. Information is deemed reliable but is not guaranteed accurate by the MLS or The Natalie Gabriele Real Estate Team. The data relating to real estate for sale on this website comes in part from the participating Associations/MLS's in the Regional IDX Program of the Toronto Real Estate Board. The properties displayed may not be all the properties available through the MLSR or the TRREB, or may include properties with unavailable data. Notice: The seller/owner of this property expressly disclaims any responsibility for any typographical errors, misinformation, or misprints and will be deemed to have made reasonable efforts to provide accurate information regarding the properties, including costs, terms, dimensions, locations, and amenities. This data is updated daily. Some properties that appear for sale on this website may subsequently have sold and may no longer be available. Information last updated on May 25, 2018 2:48 PM]" time="0.327"><properties><property name="score" value="0.20125224" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.20125224 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.20125224
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assert 'Human' == 'AI'
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- AI
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||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Anjaane\n\nAnjaane () is a 2003 Bollywood film, directed by Vikram Bhatt. It stars Ajay Devgn and Ayesha Takia in lead roles and Kunal Khemu, Nafisa Ali and Rajpal Yadav in supporting roles. The film is a remake of the American movie "Unfaithful".\n\nThis movie was an average grosser at the box office.\n\nA middle class girl, Meghna (Ayesha Takia) lives with her divorced mother, Dr. Kamla Tiwari (Reema Lagoo), a well known psychiatrist, and her younger sister in the suburbs of Mumbai. Her parents had divorced when she was just two years old, and she has hardly seen her father, Colonel Rameshwar Prasad (Deepak Shirke), ever since.\n\nRajeev Mathur (Ajay Devgn), a renowned architect, is married to Sheetal (Ayesha Julka), who is the love of Meghna's life. Meghna falls in love with Rajeev, and they become involved in an illicit relationship. One day, while trying to evade Rajeev, Meghna witnesses an incident where her father, whom she had not met for more than twelve years, is found dead at a friend's farmhouse.\n\nShe goes to his funeral and is completely shocked to see Rajeev there. On confronting him, she is told that he and her father were old friends and colleagues. She accepts this, but not before starting to suspect that Rajeev has been trying to get her out of the way in order to take over her father's position. She confronts Rajeev on this, but he insists that this is not the case.\n\nMeghna, unable to bear the thought that her father was killed, decides to investigate on her own. She tracks down one of the servants at the farmhouse, who reveals that her father was shot, and that Rajeev was there, drunk, when it happened. She confronts Rajeev, who admits that he and her father were involved in a fraud, in which they stole money from one of their clients, and faked his death to escape justice. However, Rajeev swears that he has nothing to do with her father's death.\n\nShe believes him, and accepts that she was wrong in suspecting him. While trying to console her, he kisses her. They decide to meet the next day. However, on the way to her meeting with Rajeev, she finds him being confronted by her mother and sister, who saw him leaving their house. Rajeev confesses to them that he and Meghna have been involved in a relationship, but insists that they didn't do anything wrong.\n\nAfter much debate, her family decides to agree to the relationship. Rajeev insists that Meghna move in with them, but she is shocked to learn that she is pregnant with his child. She insists that Rajeev take a DNA test to prove that the child is his, and he does so.\n\nHe confesses to her that he was never married to his wife, and had no children. He had always been in love with Meghna, but had not told anyone about it, not even her father. Sheetal had left him for another man, who later divorced her, and Rajeev's father was killed by one of his clients, who then blackmailed him. He promises that they will run away together, but Meghna doesn't believe him.\n\nLater that night, Rajeev is killed, and Meghna is accused of the murder. Dr. Tiwari believes her daughter, and begins to suspect that Sheetal might be the murderer. The police refuse to believe Dr. Tiwari's story, and the family falls apart. Meghna is released, but her mother refuses to see her, and she is forced to live with her uncle and his family.\n\nWhen the child is born, the family is forced to admit that the child does bear a close resemblance to Rajeev. They forgive Meghna and re-accept her. She goes to Rajeev's mother (Nafisa Ali), and tells her that the child is Rajeev's. His mother is grief-stricken, but eventually decides to accept Meghna, and asks her to name the child, since Rajeev was also hers. Meghna decides to name the child after her father.\n\n\n\nAll songs were composed by Sandeep Chowta, written by Sameer, and performed by Udit Narayan and Kumar Sanu.\n\n]" time="0.381"><properties><property name="score" value="0.7713669" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Khudadat Rafibeyli\n\nKhudadat Rafibeyli (; 1842\u20131889) was an Azerbaijani novelist, playwright, translator, editor, teacher and publisher.\n\nRafibeyli was born in 1842 in Shamakhy. From 1853 to 1860 he attended the Shamakhy religious school, and then later at the Shamakhi Muslim Boarding School. In 1862, he studied at the Nizamiyya Madrasah in Ganja. At first, he worked as a teacher, but then he moved to Tiflis where he studied at the Caucasian Muslim Gymnasium from 1864 to 1870. Then he returned to Shamakhi and taught at his old school until 1876, when he left for Tiflis again. In 1877, he moved to Baku and worked as a deputy editor and later as an editor at the "Hayat" newspaper. He lived in Tiflis for a third time from 1878 to 1884, and then returned to Baku, where he established a publishing house named "Abdulgaffar", which published the first Azerbaijani newspaper "Bakinskiy Listok". He died in 1889.\n\nRafibeyli is considered the founder of the Azerbaijani novel. He is also the author of numerous plays. His best-known plays include "Mumtaz Khan" (1882), "Seyid Huseyn" (1886), "Arshin Mal Alan" (1884), "Khanlar Bahadur" (1886), and "Shirin" (1887). His plays mainly revolve around the heroic deeds of people in the history of Azerbaijan, but his historical plays do not have a profound philosophical content. As well as plays, he also wrote novels and short stories such as "Koroghlu" (1872), "Xirayi" (1872), "Jabal" (1872), "Dashtadem" (1873), "Shah Abbas and Kamaleddin Efendi" (1879), "Bahadur Khan Shaku" (1880), "Shah Mansur" (1882), "Shirin" (1886), "Sulthan Mahmud" (1888), "Dervish Khudadat" (1886), "Agha Mammad Hasan" (1888), "Qataghani" (1889), "Khurshidbanu Natavan" (1889), "Nebiy" (1890), "Unsulli" (1890), and "Gulbakhor" (1890).\n\nHis two most famous works are "Seyid Huseyn" (1886) and "Arshin Mal Alan" (1884). "Seyid Huseyn" was written after the Karabakh liberation movement (1830-1835) and was first staged in 1873. It is a work of realism and it depicts the life of the Azerbaijani feudal landlord Seyid Huseyn. It was written in the tradition of oriental tales and was praised for its artistic value and the depiction of people. "Arshin Mal Alan" is a work of realist-idealistic nature. It tells about the greed of people and how this brings misfortune to them. This work was praised for the beauty of its language and for the pathos of its characters.\n\nIn addition to his plays and novels, Rafibeyli translated several plays by Russian playwrights into Azerbaijani.\n\nRaf]" time="0.374"><properties><property name="score" value="0.060292773" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[We the People of the United States, in Order to form a more perfect Union, establish Justice, insure domestic Tranquility, provide for the common defence, promote the general Welfare, and secure the Blessings of Liberty to ourselves and our Posterity, do ordain and establish this Constitution for the United States of America.\n\nIn looking at the definition of the word constitution, it becomes clear that the purpose of the Constitution was to establish a form of government for the United States of America. This was done to protect the people from the tyranny of the government, and also protect the government from the whims of the people. In this way the people would be ensured freedom to live their lives as they saw fit and the government would be ensured freedom to protect the people from foreign and domestic threats.\n\nIn order to be a free and sovereign people, it was necessary to have a proper government to guard those rights.\n\nHere is the full text of the Constitution:\n\nhttp://www.archives.gov/exhibits/charters/constitution.html\n\nThe text of the Constitution has been added to this blog. It may be found at the following address:\n\nhttp://www.debbieschlussel.com/2012/01/21/constitution-of-the-united-states/]" time="0.300"><properties><property name="score" value="0.14248976" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[You May Also Like\n\nFree quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template Free quote template]" time="0.948"><properties><property name="score" value="0.07443113333333333" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07443113 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07443113
|
||
assert 'Human' == 'AI'
|
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- AI
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+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Schon lange ist Kuba umweltfreundlich und wirtschaftspolitisch auf dem vorderen Rang anzusiedeln. Hier sind dementsprechend einige russische Technologien in den vergangenen Jahren installiert worden. Vor allem Stromerzeugung von Solarzellen hat sich f\xfcr Kuba als erfolgreich erwiesen. In den vergangenen f\xfcnf Jahren wurden 2.000 Solarzellen in Kuba eingesetzt.\n\nDer Nutzen von Solarzellen f\xfcr Kuba\n\nSolarenergie f\xf6rdert auf Kuba gesundheitlich viele Vorteile. Erstens erzeugt sie Strom, was f\xfcr einen Staat, der wie Kuba so viele wichtige Schritte in Sachen Energie f\xfcr eine modernisierte Gesellschaft geht, eine gro\xdfe Rolle spielt. Die Energiegewinnung wird damit auch in Kuba demographisch ausgeglichen.\n\nZweitens l\xf6st die Sonnenenergie den direkten Nutzen f\xfcr die medizinische Versorgung aus. Das bedeutet, dass Solarzellen auch f\xfcr die Versorgung von medizinischem Ger\xe4t eingesetzt werden k\xf6nnen, wodurch wiederum die Gesundheit der Menschen verbessert wird. So gesehen ist die Installation von Solarzellen eine entscheidende Sache, die f\xfcr eine langfristige Gesundheit von Menschen gesorgt hat.\n\nWie werden Solarzellen produziert?\n\nAuch wenn das Wetter auf Kuba eine gro\xdfe Rolle spielt, kann man aufgrund der Klima\xe4nderungen auf der Insel mit einem bedeutenden Einfluss auf die Anwendung von Solarenergie rechnen. Daher werden die Solarzellen auf Kuba in gro\xdfem Umfang eingesetzt. Wie genau das im Einzelnen geschieht, zeigt das Beispiel des Leuchtturms \u201eLa Revoluci\xf3n\u201c in der Provinz Las Tunas. Dieser wurde mit Solarzellen gebaut, weil die vorhandene Infrastruktur einige Herausforderungen mit sich bringt. Die Installation der Solarzellen hat dementsprechend unmittelbare Erfolge mit sich gebracht.\n\nDer Leuchtturm befindet sich auf einer Klippe, die einen Abstand von 1.250 Metern zum Festland hat. Es gibt keine M\xf6glichkeit, in den Turm ein Stromkabel einzuziehen. Das ist deshalb ein Problem, weil dieser Turm eine gewisse Gr\xf6\xdfe hat. Die M\xf6glichkeit, dass der Strom aus der Natur umweltfreundlich gewonnen werden kann, wird durch die Installation der Solarzellen genutzt. Wie es ebenfalls erw\xe4hnt wurde, befindet sich der Leuchtturm auf einer Klippe und somit auch einige Kilometer von der Siedlung entfernt. Deshalb ist es hier sehr lohnenswert, Solarzellen zu installieren.\n\nDie gro\xdfe Stromproduktion des Leuchtturms ist das Resultat des Einsatzes von Solarenergie. Der gesamte Energiebedarf wird damit gedeckt. Solarzellen haben sich dementsprechend als eine \xe4u\xdferst wertvolle Sache f\xfcr Kuba erwiesen. Dadurch wird eine stromproduzierende Stelle sichergestellt, die unabh\xe4ngig vom Regenwetter ist. Somit haben Solarzellen einen unglaublich hohen Nutzen f\xfcr Kuba.\n\nFazit\n\nDie Installation von Solarzellen auf Kuba stellt somit einen sehr wichtigen Baustein f\xfcr das Funktionieren der Gesellschaft dar. Die Produktion von Strom aus Sonnenenergie f\xf6rdert die Gesundheit, da sie dem Bev\xf6lkerungswachstum Rechnung tr\xe4gt. Solarzellen sind daher auch in Kuba eine wichtige Sache, um die Energieversorgung zu sichern.]" time="0.324"><properties><property name="score" value="0.010673079" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Cardiac intervention in men is a critical procedure performed with the best equipment available. Sometimes, however, there are complications that are difficult to solve. For example, the images provided by a coronary angiography may not be clear enough for the doctor to determine the problem. In this situation, it is necessary to perform an intervention for coronary angioplasty. This is a technique that was introduced in the 1970s and has been improved many times over the years.\n\nWhat is coronary angioplasty?\n\nCoronary angioplasty is a technique that allows the narrowing of a coronary artery to be dilated. This is done with the use of a catheter that has a flexible balloon at its end. This is inflated and deflated so that the artery is dilated. Once the dilation is achieved, a stent is implanted to keep the artery dilated and allow blood to flow properly. The stent is a small metal ring that is placed inside the lumen of the artery. It acts as a scaffold and prevents the vessel from closing. This is important because, if this happened, the part of the heart that receives blood from this artery would not receive any more.\n\nCoronary angioplasty is performed under general anesthesia. The patient is given nitroglycerin so that the pain caused by the dilation of the artery is less intense. Sometimes, if the patient has chest pain, an injection of painkillers may be needed.\n\nAfter the procedure is completed, the patient is observed to make sure he has not had any complications. If the patient develops a hematoma, the artery is usually clamped again and the hematoma is removed by inserting a small wire.\n\nThe risk of complications is low. They can develop in patients who have had angioplasty many times or who have had previous heart attacks.\n\nThe main advantage of angioplasty is that it provides immediate relief for the patient. If the stent works well, the patient may need to take medication for the rest of his life. This is an important advantage for those who have suffered a heart attack and are at risk of a second one.\n\nIn certain cases, it is necessary to repeat the intervention several times until the lumen of the artery becomes stable. Usually, the procedure is done after 4-6 weeks, depending on the patient\u2019s progress.]" time="0.296"><properties><property name="score" value="0.13301806" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Olympic Champion Jazmin Carlin had a successful return to racing on the World Cup circuit this weekend, winning a silver medal in the 50m backstroke and claiming two more top-3 finishes in the 200m individual medley and 50m freestyle.\n\nCarlin, a Manchester born-and-bred athlete who moved to Wales to train with the Welsh Academy, produced a stunning performance in the 50m backstroke, finishing just over a second behind American world-record holder Kathleen Baker.\n\nA week earlier she had set a new British record of 26.06 seconds at the British Championships, setting up a superb start to the 2018 season.\n\nEarlier in the week, Carlin also clocked a lifetime best in the 200m individual medley in Glasgow. Her swim of 2:14.50 is her fastest ever 200m medley in a year that she is targeting selection for the European Championships.\n\n\u201cI came into this season knowing that I am going to be racing in the 100m and 200m individual medley in the European Championships and this is the event that I am training for so this was a good start,\u201d said Carlin.\n\n\u201cI am not usually a 200m medley swimmer but my best event is the 100m backstroke and, when it came to a race choice, I am always going to take the backstroke so I was just pleased to go under 2:15, as it is my personal best.\u201d\n\nCarlin also set a new British 50m backstroke record of 26.21 seconds in the heats and the semifinals.\n\n\u201cI got a bit stuck with people in the first 50m of the race,\u201d she said.\n\n\u201cI couldn\u2019t get going but I knew I had to make a push in the last 25m.]" time="0.382"><properties><property name="score" value="0.031235263" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03123526 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03123526
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[John Gray Blaikie\n\nJohn Gray Blaikie (15 April 1838 \u2013 18 February 1915) was a Scottish journalist, author and miscellaneous writer. He was the author of the "Portrait-Gallery of Eminent Scotsmen".\n\nHe was born in Edinburgh, Scotland, in 1838, the son of the architect Robert Kerr Blaikie.\n\nHe studied at the Edinburgh Academy. At 15 he was apprenticed as a compositor to the publishers Oliver and Boyd, and studied during the intervals of his work. He then became a journalist, working on the "Glasgow Herald" and "Scottish Leader", and other papers. In 1862 he became sub-editor of the "Glasgow Citizen", and later editor, and continued in this post till 1868. He then became a reporter on the "Standard", and subsequently on the "Daily News". In 1874 he went to London and became parliamentary and general leader of the "Evening News". He continued to act as leader writer to this paper till 1885, when he returned to Edinburgh.\n\nBlaikie contributed to the "Dictionary of National Biography" (DNB) articles on John P. Manson, Thomas Guthrie and George Dempster. He also wrote the DNB's article on his father. He died at Penicuik, Midlothian, on 18 February 1915.\n\nBlaikie married Agnes Sinclair and had six children.\n\nHe was the author of:\n\nHe also compiled the "Portrait-Gallery of Eminent Scotsmen" (1884), the "Essay on Burns" in the "Men of Letters" series, and the "Land of Burns" in the "Penny Poets".\n\n]" time="0.315"><properties><property name="score" value="0.08824792" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Sri Lankan cricket team in Australia in 2014\u201315\n\nThe Sri Lanka national cricket team toured Australia from 10 December 2014 to 4 January 2015. The tour consisted of two Twenty20 International (T20I) matches, three One Day International (ODI) matches and two Test matches. The T20I matches were played in Hobart on 14 and 16 December 2014, the ODI matches were played at the Melbourne Cricket Ground (MCG) from 26 to 28 December 2014, and the Test matches were played at the Sydney Cricket Ground (SCG) from 2 to 6 January 2015.\n\nIn July 2014, Sri Lanka Cricket named a preliminary 26-man squad for the tour. This was later reduced to 23.\n\nOn the first T20I of the series, Tillekaratne Dilshan scored the fastest fifty in T20I history off just 13 balls.\n\nThe first ODI of the series was the 400th ODI match to be held at the MCG.\n\nThe first Test of the series saw the return of Australian all-rounder Shane Watson after injury.\n\nSri Lanka won the Test series 2\u20130 and therefore won the Chappell\u2013Hadlee Trophy.\n\n]" time="1.364"><properties><property name="score" value="0.2547273" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Marocs\n\nMarocs was a slave from Ghana in West Africa who was brought to St. Augustine in Spanish Florida around 1740. His life there became the basis of a plantation diary written by Francis Le Jau in 1741. The diary and other documents were later published as "The Journal of Francis Le Jau, 1741\u20131743", by Richard Hakluyt (the pseudonym of a 19th-century English writer). In the document Marocs and his fellow slaves are described as being part of the possessions of Captain Francisco Menendez M\xe1rquez, who died and willed them to his nephew Captain Don Jose Men\xe9ndez M\xe1rquez. \n\nAt the time of Le Jau's journal, Marocs had become a trusted member of the household, handling business transactions on the plantation. On August 5, 1742, he signed a contract of manumission with Captain Don Jose Men\xe9ndez M\xe1rquez. He became a free man, and was set up with a farm and a lifetime income, in exchange for his work as a steward on the plantation.\n\nSome time later, he was accused of killing a slave of his neighbour, Charles de Sauvinet. Marocs was sent to St. Augustine for trial, but was acquitted due to a lack of evidence. The local Spanish governor and slave owners took Marocs' acquittal as an insult, and made him wear an iron collar to publicly declare his guilt. The collar was fastened with an iron chain and ring around his neck and he was locked to the wall of the courthouse. Marocs would stay in St. Augustine for the next 12 years until the colonial government collapsed during the American Revolution.\n\nMarocs became a symbol of African resistance and a rallying cry for slaves during the Stono Rebellion of September 9, 1739. The rebellion of slaves and African free men, planned and carried out by a slave named Jemmy, began with an armed group of about twenty men killing two British traders. They marched south to the St. Augustine Parish church, where they broke into the weapons store. They then broke into the house of the militia leader, Lieutenant Governor William Bull. After killing him, the rebels marched to the St. Johns River, where they seized boats and rowed to freedom across the Santee River into the interior of South Carolina. There were 60 or so participants in the revolt, with 40 of them escaping and the rest either killed or captured. The colonial militia and British Army killed many of the captured rebels.\n\nThe Stono rebellion started a series of revolts in the British colonies. The revolt started the movement to end the slave trade and slavery in the Thirteen Colonies and led to the declaration of independence by the Continental Congress on July 4, 1776.\n\n\n]" time="0.728"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[[Editor\u2019s note: We get a lot of submissions from industry organizations like RILA, NCPA, FMI, etc., and we love it when they are well-done. This piece was sent to us from FMI\u2019s public affairs director Mike Haftka and was so good that we asked if we could publish it here. It has just a couple edits from the original. As always, all opinions are his own.]\n\nIt is clear that the well-organized government-sector labor unions have been spending big time to demonize farmers, and the rest of the industry as well, in an effort to advance their own interests. It is time to push back.\n\nWhile the politicians involved in the passage of the 2013 farm bill have been lionized for their actions, it was actually the members of the grassroots, the vast majority of whom are not farm owners, that saved the farm bill.\n\nAlthough the House of Representatives only received a 5 percent score from the AFBF, according to the FMI\u2019s own scorecard, a significantly larger number of lawmakers voted with the FMI\u2019s policy recommendations when it came time to actually cast a vote on the 2013 farm bill. That is a big difference, one that makes the distinction between the union\u2019s demonization of farmers and the reality of farmers\u2019 lives crystal clear.\n\nSome of the most vocal advocates of farmers in the media are organizations and individuals that are largely funded by the food stamp program. The same groups pushing to expand food stamps are lobbying for higher farm prices. Their message is confusing, even contradictory, and it simply does not resonate with voters.\n\nThe farm bill was also a big winner for consumers. The American Farm Bureau\u2019s own report, which tracks consumer prices, found that the price of fresh fruits and vegetables fell by more than 9 percent in 2013. Americans may not like to think of farmers as price makers, but there is no question that low commodity prices resulted in lower prices for consumers.\n\nAs the current farm bill continues through the process, and in anticipation of the 2014 midterm elections, we need to make sure that the politicians we elect are being held accountable for the actual impacts of the farm bill.\n\nNo amount of lobbying is going to influence the farm bill debate if it is going to be followed by groups that are financed by the food stamp program. If these groups are going to lobby on behalf of farmers, then they need to learn how to talk like farmers.]" time="0.285"><properties><property name="score" value="0.0045496207" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00454962 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00454962
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Nous avons test\xe9 l\u2019ultra haut de gamme: les PC du gaming MSI Prestige et du Ryzen Threadripper 1950X avec ses 16 coeurs de 3.4 GHz. Nous les avons utilis\xe9s pendant un mois. Avec ce test et une r\xe9flexion de la part des partenaires, nous avons pu vous proposer les meilleurs configurations disponibles en magasin et sur internet. Lequel choisir pour lancer des jeux 4K et faire tourner vos applications ? Ce test va vous aider \xe0 vous d\xe9cider.\n\nDans le monde du gaming, l\u2019excellente configuration de PC est souvent difficile \xe0 mettre en place. Les gros jeux utilisent de plus en plus de m\xe9moire vive et de processeurs pour produire des graphismes et des fonctionnalit\xe9s toujours plus complexes. Vous avez souvent besoin d\u2019un PC de jeu puissant avec un excellent mat\xe9riel pour pouvoir profiter du meilleur de ce que propose le march\xe9.\n\nNous vous proposons deux configurations PC gaming qui sont disponibles sur le march\xe9 actuellement.\n\nAvec un PC de jeu ultra haut de gamme, vous pouvez jouer dans des conditions exceptionnelles et profiter de graphismes sans faille.\n\nPour vous donner des id\xe9es, nous avons test\xe9 deux configurations diff\xe9rentes pour vous guider vers les meilleurs PC de jeu disponibles en magasin.\n\nS\xe9lection des meilleurs PC de jeu\n\nAvec ce comparatif, nous vous proposons des tests r\xe9alis\xe9s avec le meilleur mat\xe9riel actuellement disponible. Il est essentiel d\u2019utiliser un PC de jeu ultra haut de gamme pour profiter du contenu disponible sur les sites de jeux vid\xe9o.\n\nPour la configuration 4K\n\nNous vous proposons la configuration de test de d\xe9part, que vous pouvez utiliser pour lancer les nouveaux jeux 4K de haut niveau.\n\nLa configuration 4K propose la combinaison de composants suivante:\n\nIntel Core i7 7700K\n\nMSI B250 GAMING M5\n\nMSI GTX 1070 Ti 8 Go\n\nADATA XPG DDR4 4x4 Go\n\nMSI GTX 1070 Ti\n\n240 Go SSD\n\nCe PC de jeu a \xe9t\xe9 con\xe7u pour vous offrir un PC 4K complet. Avec une r\xe9solution de 4K, la configuration de test de d\xe9part offre une qualit\xe9 visuelle maximale avec des jeux r\xe9cents comme Far Cry 5, PUBG, Wolfenstein II et Shadow of War.\n\nLa configuration de test de d\xe9part vous permet de vous mettre en train de mani\xe8re s\xe9curis\xe9e. Avec cette configuration, vous pourrez commencer \xe0 jouer d\xe8s que vous l\u2019aurez command\xe9e. Vous pourrez profiter de votre nouveau PC de jeu ultra haut de gamme en HD et 4K avec la configuration de test de d\xe9part.\n\nAvec le PC de jeu 4K, vous disposez d\u2019un PC gaming qui vous permettra de lancer les jeux 4K r\xe9cents et de profiter d\u2019un maximum de fonctionnalit\xe9s et de d\xe9tails.\n\nVous pouvez lancer les derniers jeux de mani\xe8re fluide avec ce PC 4K en Ultra HD. La configuration de test de d\xe9part sera plus que suffisante pour jouer dans des conditions de jeu optimal.\n\nPour la configuration 1080P\n\nNous vous proposons la configuration de test de d\xe9part, que vous pouvez utiliser pour lancer les jeux r\xe9cents 1080p.\n\nLa configuration 1080P propose la combinaison de composants suivante:\n\nIntel Core i5 7600K\n\nMSI B250 GAMING M5\n\nMSI GTX 1050 2 Go\n\nADATA XPG DDR4 4x4 Go\n\nMSI GTX 1050 2 Go\n\n120 Go SSD\n\nCe PC de jeu a \xe9t\xe9 con\xe7u pour vous offrir un PC 1080p complet. Avec une r\xe9solution de 1080p, la configuration de test de d\xe9part offre une qualit\xe9 visuelle maximale avec des jeux r\xe9cents comme The Witcher 3, GTA V, Shadow of War et PUBG.\n\nLa configuration de test de d\xe9part vous permet de vous mettre en train de mani\xe8re s\xe9curis\xe9e. Avec cette configuration, vous pourrez commencer \xe0 jouer d\xe8s que vous l\u2019aurez command\xe9e. Vous pourrez profiter de votre nouveau PC de jeu 1080p complet en HD et 1080p avec la configuration de test de d\xe9part.\n\nAvec le PC de jeu 1080p, vous disposez d\u2019un PC gaming qui vous permettra de lancer les jeux 1080p r\xe9cents et de profiter d\u2019un maximum de fonctionnalit\xe9s et de d\xe9tails.\n\nVous pouvez lancer les derniers jeux de mani\xe8re fluide avec ce PC 1080p en Full HD. La configuration de test de d\xe9part sera plus que suffisante pour jouer dans des conditions de jeu optimal.\n\nUn PC de jeu pour commencer votre collection\n\nTous les jeux r\xe9cents vous sont accessibles avec ces PC de jeu haut de gamme et 4K.\n\nSi vous ne savez pas quel PC de jeu choisir pour vous mettre au jeu, vous pouvez commencer par la configuration 4K. Pour seulement 999 euros, vous disposez d]" time="0.324"><properties><property name="score" value="0.00053894365" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Even though Alabama didn\u2019t have the most dominant recruiting year in the SEC this past year, it still finished ranked inside the top five, according to the 247Sports Composite.\n\nThere is a lot of time left until these recruits go to their respective colleges. Some are solid commitments, others may be headed to other schools or may even wind up in the draft. But for the moment, these rankings will make some people mad and others will praise them.\n\nHere\u2019s how the 247Sports Composite, which averages the ratings from all major recruiting services, ranks the top 10 classes in the SEC.\n\nGeorgia, 3\n\nAlabama, 4\n\nLSU, 5\n\nAuburn, 6\n\nMississippi State, 7\n\nTennessee, 8\n\nSouth Carolina, 9\n\nFlorida, 10\n\nTexas A&M, 11\n\nArkansas, 12\n\nKentucky, 13\n\nMissouri, 14\n\nVanderbilt, 15\n\nOle Miss, 16\n\nAlabama didn\u2019t have the best recruiting year, but it was still pretty damn good. And you could argue that these rankings aren\u2019t that bad.\n\nYes, Alabama didn\u2019t land a five-star recruit, but it did get the top player in the state and the top player at three different positions. Not many schools can claim that.\n\nIs this the year of Alabama? Yes No Submit Vote vote to see results Is this the year of Alabama? Yes 80.6%\n\nNo 19.4% Total votes: 2,397\n\nThere is still a lot of talent left on the board. Alabama has three more scholarships to give, and it will probably have a handful of five-star prospects.\n\nIt\u2019s been a good couple of weeks for Alabama. This weekend it lost in embarrassing fashion to Auburn, but the win over LSU put the Tigers in the driver\u2019s seat in the SEC West. The Tide is still playing for a national championship, and its defense has looked good as of late.\n\nIn 2013, Alabama had a good recruiting class, but it was nothing to get worked up over. This year, the Tide had a great class. We\u2019ll see if the talent on the field matches the talent in the recruiting rankings.\n\nAll recruiting rankings via the 247Sports Composite.]" time="0.343"><properties><property name="score" value="0.0021220464" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00212205 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00212205
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Baba Ramdev on Wednesday claimed that his company Patanjali Ayurved has received over Rs 150 crore orders for products like shampoo, honey, etc from abroad and is looking to export to 20-25 countries in the next 5 years.\n\nWhile sharing his company's five year plan for foreign expansion, Ramdev said, "We are giving a boost to manufacturing of herbal products in India, while we are in talks with foreign countries for exports."\n\nTalking about the economic downturn, Baba Ramdev said, "In an economic downturn, people become more health conscious, which helps companies like ours."\n\nWhen asked about Patanjali's foray into non-herbal products, Ramdev said, "We will only come out with a few non-herbal products."\n\nPatanjali Ayurved's turnover in 2012-13 was over Rs 925 crore. The company is planning to double its turnover in the current fiscal.\n\nTalking about the line of products Patanjali is coming out with, Baba Ramdev said, "We have made the natural form of every product available in the market, which includes even sanitary napkins."\n\nA file photo of Baba Ramdev. (HT Photo)\n\n(With PTI inputs)]" time="0.263"><properties><property name="score" value="0.0033726534" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00337265 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00337265
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[LAKELAND, Fla. -- Jason Vargas understands he won't be pitching every fifth day like he has in the past, and he knows he might not get to pitch the way he'd like to, but the 33-year-old left-hander said he's "excited" for the opportunity to make the Detroit Tigers' starting rotation.\n\n"It's a unique opportunity," Vargas said Sunday, when he was officially added to the Tigers' 25-man roster. "You don't see many pitchers make that transition back into the rotation, and I've made it a lot of times before, so I'm excited to be back in that role."\n\nThe Tigers announced Vargas' move before a 1-0, 12-inning victory over the Baltimore Orioles at Joker Marchant Stadium. After striking out six in five innings, Vargas was credited with the win.\n\nWith the addition of Vargas, Detroit's pitching staff stands at 14 pitchers. He joins Michael Fulmer, Jordan Zimmermann, Daniel Norris, Matt Boyd and Anibal Sanchez as the group of starters.\n\n"It's definitely a big adjustment," said Vargas, who has a 1-0 record and 5.91 ERA in four appearances with the Tigers this spring. "You can't be as aggressive as you were in the past. But you kind of have to pick and choose your battles.\n\n"You don't want to leave too many pitches up in the zone. You have to throw some early strikes, and you just have to be smart."\n\nManager Brad Ausmus said Vargas "has handled it well" this spring.\n\n"He's looked like he's handled it pretty well," Ausmus said. "And he has."\n\nVargas, who signed a minor-league contract with the Tigers in January, made 27 starts last season for the Kansas City Royals. He went 4-10 with a 5.26 ERA in his final season with the Royals. He said he will continue to mix and match between the rotation and the bullpen.\n\n"He fits our roster well," Ausmus said. "I think that he can come out of the bullpen and start."\n\nVargas said he's willing to do what the Tigers want him to do, but he wants to make it clear that he will continue to pursue the opportunity to start.\n\n"If they want me to start, that's fine," he said. "If they want me to come out of the bullpen, that's fine. But my goal is to start and to get back in there and pitch like I know I can pitch."\n\n-- Download the Detroit Tigers on MLive app for iPhone and Android.\n\n-- Follow MLive Sports on Facebook, Twitter and Instagram.]" time="0.445"><properties><property name="score" value="0.058080226" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05808023 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05808023
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Bad Experience\n\nby Aileen\n\n(Oklahoma)\n\nThis happened a few years ago when my daughter was about two. It started as a few tantrums in a row, I'd finally find a toy she would be happy with and I'd go get some coffee and a few minutes later I'd hear screaming and I would go back in and she would be throwing the toy or just sitting there crying.\n\n\n\nThis happened for a few weeks, it was almost every day. Then one day she started talking about her friends in a different language. She knew what she was saying was wrong, she was very embarrassed by it.\n\n\n\nShe was saying things like "I hate you." She would also be saying "the cat wants to fight" and stuff like that. At first I just assumed she was mimicking something she had heard but she kept saying things like "can I be in your gang?" Then she started talking about stuff that could only be her imagination. She would say things like "I see your sister getting hit by a car, then a bunch of ghosts are standing around and your dad is talking to them." I was very concerned.\n\n\n\nI talked to the teacher about this and she said she'd been acting really strange in school and talking to her friends and not listening to anyone. She also would draw pictures and be laughing to herself.\n\n\n\nI finally took her to the doctor and she was diagnosed with OCD. They put her on some meds and it cleared up.\n\n]" time="0.298"><properties><property name="score" value="0.22899777" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Updated to add comment from Shona Keene\n\nA 33-year-old B.C. man who drove from Vancouver to pick up his dog from a P.E.I. animal shelter, then drove back to B.C. with it, will have to fight a charge of violating quarantine regulations.\n\nDarcy Jewell was charged under the Health Protection and Promotion Act.\n\nHis one-year-old labrador retriever, Oreo, was put in a quarantine kennel at the P.E.I. Humane Society.\n\nUnder the act, dogs are not allowed into P.E.I. unless they come from one of four designated \u201cpre-approved\u201d kennels, or a veterinarian\u2019s office.\n\nThe province is trying to prevent the spread of rabies, which has not been found on the Island in at least 50 years.\n\nPeople on the Island who wanted to bring their dogs here, and weren\u2019t sure about the regulations, had been asked to get in touch with P.E.I.\u2019s animal control office.\n\nCBC P.E.I.\u2019s Jessica Doria-Brown spoke with a staff member from the Humane Society who said the man who picked up the dog had said it was for a short visit.\n\nDogs that have to be quarantined for more than 10 days in P.E.I. are transported to the IWK in Halifax.\n\nThe Humane Society has not responded to our request for comment.\n\nCharges were laid after the Department of Health and Wellness received a complaint, the province\u2019s Health Minister told CBC.\n\n\u201cThe concern that we have with rabies is that it\u2019s not something that can be easily dealt with,\u201d Robert Mitchell said.\n\n\u201cIf someone has the illness, they can spread it to other animals, and people are at risk.\u201d\n\nMitchell said it\u2019s up to the RCMP to enforce the regulations, and that he can\u2019t comment on the specific case.\n\n\u201cI\u2019m not aware of any other such incidents,\u201d Mitchell said. \u201cIt\u2019s a very serious offence and I would certainly hope that people would be able to be advised on what the requirements are.\u201d\n\nMitchell said that \u201cIf it turns out that there was an offence, then it\u2019s the responsibility of the individual to be charged.\u201d\n\nThe case will be heard in provincial court on Sept. 24.]" time="0.291"><properties><property name="score" value="0.0014025412" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00140254 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00140254
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A 19-year-old man who died in a car crash in Carrick-on-Shannon in March was a "bright young man who died too soon", his family have said.\n\nA 19-year-old man who died in a car crash in Carrick-on-Shannon in March was a "bright young man who died too soon", his family have said.\n\nThomas O'Brien died after his car collided with another at the junction of the N4 and the L1337 at about 11.15pm on March 23.\n\nA 21-year-old man who was driving the other vehicle suffered only minor injuries.\n\nMr O'Brien, from Tubbercurry, was a student in NUI Galway. His family described him as a "wonderful son, brother, grandson and friend".\n\nHis sister Tara O'Brien said his death has been "totally devastating and impossible to come to terms with". "He was a bright young man who died too soon," she said. "He had a heart of gold and would do anything for anyone. He was full of life, loving, caring and was the funniest person I ever met.\n\n"I hope he will always be remembered by everyone as a bright, witty, beautiful and loving young man."]" time="0.333"><properties><property name="score" value="0.08172973" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A senior policeman has come under fire for suggesting that people should look at what they are wearing before calling the police to complain about the length of time it takes to arrive at the scene of an emergency.\n\nA senior policeman has come under fire for suggesting that people should look at what they are wearing before calling the police to complain about the length of time it takes to arrive at the scene of an emergency.\n\nIt is "unfortunate" that people who complain about the length of time it takes for garda\xed to arrive should be dressed inappropriately, according to the assistant Garda commissioner for Dublin, Pat Leahy.\n\nMr Leahy's comments have sparked controversy in Ireland. Critics said his comments would only increase people's anger at garda\xed, and his remarks were even likened to the U-turn made by British prime minister Theresa May, when she apologised for the "hurt" caused by austerity measures.\n\nAddressing the Joint Policing Committee in Dublin yesterday, Mr Leahy said that in some cases, people complaining about the length of time it takes for garda\xed to arrive at the scene of an emergency should look at the state they are in.\n\n"I think the point that I am making is that people look at the state of their clothing when they call the garda\xed.\n\n"A lot of times, if you are wearing a suit and tie when you call, a car will be there.\n\n"When you call in a pair of pyjamas, it's a different story."\n\nHis comments were picked up by the Sunday Independent newspaper, which reported that Mr Leahy was taking an "unusual step" to appeal to the public to dress appropriately.\n\nThe assistant commissioner said it was "unfortunate" that members of the public would ring up and complain about the length of time it takes for garda\xed to arrive.\n\n"A lot of times they are in pyjamas, and it is unfortunate," he said.\n\nThe government's austerity programme, which led to tax rises, welfare cuts and the privatisation of state assets, led to Mr May being branded a "U-turn queen" in 2016.\n\nAnd just last week, it was revealed that the NHS spent almost \u20ac500,000 sending patients on holidays last year.\n\nThe Department of Health said it spent \u20ac4,707,959 on hospital tourism last year, according to documents released under the Freedom of Information Act.\n\nSunday Independent]" time="0.300"><properties><property name="score" value="1.5044571" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Arts Council England has announced that \xa39.6m will be distributed to arts organisations across Northumberland as part of its Grants for the Arts scheme.\n\nOrganisations to benefit include:\n\nNorthumberland Dance \xa380,000\n\nGrassington Festival \xa330,000\n\nGaler Gallery \xa332,000\n\nChepstow Castle \xa375,000\n\nGaler Gallery \xa332,000\n\nGaler Gallery \xa332,000\n\nQuarry Arts \xa328,000\n\nTheatre Segedunum \xa332,000\n\nSunderland Arts Centre \xa360,000\n\nNorthumberland Arts \xa3300,000\n\nAlnwick Garden \xa380,000\n\nAmble By The Sea \xa332,000\n\nCalderdale Museums and Arts \xa325,000\n\nCalderdale Museums and Arts \xa310,000\n\nCalderdale Museums and Arts \xa320,000\n\nChester-le-Street Playhouse \xa360,000\n\nHaltwhistle Entertainment Centre \xa332,000\n\nThe Tyneside Cinema \xa350,000\n\nWallsend Memorial \xa360,000\n\nWallsend Theatre Company \xa340,000\n\nAlnwick Playhouse \xa340,000\n\nConsett Civic Society \xa37,500\n\nNational Railway Museum \xa3300,000\n\nSunderland Museum and Winter Gardens \xa3160,000\n\nArts Council England provides over \xa37 million of direct financial support to the arts in Northumberland every year, through its Grants for the Arts scheme, designed to fund the core costs of running organisations.]" time="0.294"><properties><property name="score" value="0.24934278" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24934278 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24934278
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Nepal captain Paras Khadka says his side are aiming to win the ICC World Cricket League Division 5 and seal a place in next year's ICC World Cup Qualifier.\n\nThe five-team event in Jersey gets underway on Monday and Nepal are joined by Canada, Kenya, Namibia and USA.\n\n"We are excited and nervous as it is a big tournament, especially for us as it is our last chance to qualify for the World Cup Qualifier," Khadka told ICC's official website. "It is a great opportunity for us to qualify as hosts of the next World Cup Qualifier and make a big statement.\n\n"This is the first time that we are playing the teams in our group so we have to play positive cricket. We need to win as many games as we can and get to the final," he added.\n\nAll five sides are vying to be crowned the first champions of this competition and get one step closer to the World Cup Qualifier in Ireland and Scotland in 2018.\n\nThey will all play two round-robin matches, followed by a play-off for the top two sides, who will then face off in a final to determine the overall winner.\n\nNepal are placed in Group A and will open their campaign against hosts Jersey at Mont a la Roque on Monday, before facing Canada at the same venue on Thursday.\n\nKhadka says his side will use the matches against the host nation to gauge their performance and assess their strengths and weaknesses.\n\n"We are excited to play Jersey as we want to see our performance against a tough opposition. It will be a test for us. We don't have much information on them so we have to play with our strengths and see how it goes.\n\n"Our goal is to finish on top of our group and play the final. If we win, it will be our first World Cup Qualifier and we will be looking to get a few more players into the national team. That is a massive goal for us.\n\n"We need to play fearless cricket, which we will be doing."\n\nNepal will also face USA on Friday at Les Quennevais, while their final game against Kenya takes place at the same venue on Tuesday.\n\nIn Group B, Canada will take on Kenya at Les Quennevais on Monday, before taking on Namibia at the same venue on Thursday.\n\nThe group's other two matches will see hosts Jersey take on Namibia at Beaulieu on Monday and USA face Canada at Beaulieu on Thursday.]" time="0.311"><properties><property name="score" value="0.24834771" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This is a tutorial on using the Wiimote to control playback in VLC media player, a media player similar to xbmc and Mplayer. This is useful for anyone using their computer as a home media center. I\u2019ll give a very brief overview of VLC as I assume you are familiar with it. You can download the latest version of VLC for Windows here.\n\nDownload the remote control extension here.\n\nStep 1: Unzip the file and copy the WIRemote.dll file to VLC\u2019s plugins folder. If you are using VLC 1.0.6, the default folder for plugins is C:\\Program Files\\VideoLAN\\VLC\\plugins. If you\u2019re using a different version of VLC, check here.\n\nStep 2: Configure the Wiimote. Find the extension\u2019s config file in your VLC directory and open it with notepad.\n\nStep 3: Set up the controller to work as a remote control by adding lines to the config file. Add the following to the bottom of the config file:\n\nAs you can see in the config file, the Wiimote is set up as a keyboard. Each button on the Wiimote can be configured to perform certain keyboard commands.\n\nStep 4: Run the VLC media player and click on Tools > Control Extensions. Under the Wiimote tab, select the channel from which you wish to control playback. Make sure that in the Remote Control section, you have set the Mode to Wiimote and have checked Enable. Click on OK and close the Control Extensions window.\n\nStep 5: Load the movie you wish to watch. Press the Wiimote\u2019s A button and hold it down until the movie starts playing. The buttons on the Wiimote will become active. The up, down, left and right keys on the Wiimote correspond to the left, right, up and down arrow keys on the keyboard. The 1 key will bring up the video player and you can use the up and down arrow keys to scroll through your movies and the enter key to select one. To play or pause, simply press the B button. The Select button acts as the enter key. Pressing Select while on the video player screen will take you to the movie\u2019s directory. Press the Wiimote\u2019s Home button to go back to the movie\u2019s directory.\n\nYou can assign other keyboard keys to the other buttons on the Wiimote. I assigned the A button to playback pause and the B button to stop playback. To do this, in the Remote Control section of the VLC media player\u2019s control extensions, click on the Misc tab. You can assign commands under the Buttons section.\n\nIf you are using VLC 1.0.6, you may need to check the Video Output plug-in option under the Misc]" time="0.320"><properties><property name="score" value="2.8859968" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.8859968 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.8859968
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The RSPCA is asking members of the public to be extra vigilant after a dog was shot in Bideford this week.\n\nThe injured animal was found on Friday, July 18.\n\nThe charity is working with the police in trying to trace the person responsible and is reminding the public to keep a look out for other animals, including wildlife, which could be in distress.\n\nBideford police station has been alerted to the incident and have confirmed that they have launched an investigation.\n\nThe dog, an adult German Shepherd cross, was found with an injury to its shoulder in Newland Park, Bideford.\n\nRSPCA inspector, Katie Forster, said: \u201cThis is absolutely appalling.\n\n\u201cWe are asking members of the public to be vigilant, especially in relation to wildlife.\n\n\u201cSadly, we do not know how the animal sustained this injury.\n\n\u201cWe are keeping an open mind as to what might have happened, but if you have any information that could help us please get in touch.\n\n\u201cWe do have some leads but would welcome further information as this would allow us to progress our investigation.\n\n\u201cThis could have been a lot worse and it is shocking that this dog has been shot.\n\n\u201cI am appealing to members of the public to help us in our enquiries and help find the person responsible for doing this.\n\n\u201cWe do not know what the outcome of this may be for the dog but in cases like this the most likely outcome is that the animal will be put to sleep.\n\n\u201cWe are working closely with the police on this case and they are assisting with our enquiries.\u201d\n\nAnyone with information should contact the RSPCA appeal line on 0300 123 8018.]" time="0.275"><properties><property name="score" value="0.252697" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I know the title of this blog post is rather misleading. It sounds like I\u2019m saying that women\u2019s books are not worth reading. This is absolutely not what I\u2019m saying. I think that women\u2019s books can be just as great as men\u2019s books and vice versa. I just happen to have read a lot of men\u2019s books that I really enjoyed recently, so I thought I would recommend them to you.\n\nI hope you enjoy them as much as I have.\n\n1. Lonesome Dove \u2013 Larry McMurty\n\nI think this is probably my favorite book ever. It is such a sweeping story that you don\u2019t want it to end. I still have the book (even though it\u2019s really old and falling apart) and I\u2019ve read it numerous times. I can\u2019t get enough of Gus and Woodrow, and Captain Call. And I adore their \u201cwomen,\u201d Clara and Newt. I will recommend this book to anyone and everyone that I meet, and I love it so much I will probably read it again.\n\n2. Swimming to Catalina \u2013 Lynn Hall\n\nI found this book when I was at a thrift store on vacation. I was looking for a romance novel because they are my favorite books to read. I just can\u2019t get enough of them. But I was shocked to find that this book was a romance book written by a man. It was a romance book in the style of a mystery. I have never read a book like it and I loved every minute of it. The characters are quirky and interesting and the romance is off the charts.\n\n3. How to Lose Friends and Alienate People \u2013 Toby Young\n\nThis book was one of my favorite reads last year. I knew the story of this guy, Toby Young, already. I\u2019ve watched him on television and I\u2019ve read some of his books. This one wasn\u2019t a very happy read, though. In it, he details his misadventures with the British press and his life in New York City. The book was extremely funny, but there were also some very serious parts of the story. Toby is a character that I am sure I\u2019ll be reading about for years to come.\n\n4. Lonesome Dove \u2013 Robert James Waller\n\nI read this book after reading Larry McMurty\u2019s, but it was a completely different story. In this version, the two main characters are a man and a woman, and they are in their fifties. They decide to drive their herd of cattle across Texas to Montana. As they go on their journey they have many adventures, some are funny, some are serious. The romance between the two main characters was extremely interesting to read about. The last time I read it I was only twelve, so I had no idea what was going on. But I still loved it and I would read it again.\n\n5. The Chocolate War \u2013 Robert Cormier\n\nThis is another book that I\u2019ve read multiple times, but I will read it again. The story is about a boy who lives at a Catholic school. His mother has recently died and he is being picked on by the school bully. He begins a \u201cconfrontation\u201d with the bully by refusing to sell chocolates on the first day of school. After this, he is forced to join a secret organization at the school and he becomes involved in a lot of dangerous situations. This is one of the books that I recommend to most people, I think. It\u2019s not my favorite, but it\u2019s worth a read.\n\nAnd there you have it! The five books that I am recommending to you today. I hope that you enjoy them as much as I did!\n\nAdvertisements]" time="0.306"><properties><property name="score" value="0.5426594" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[San Francisco 49ers Tickets\n\nSan Francisco 49ers News\n\nSan Francisco 49ers Tickets\n\nThe San Francisco 49ers are one of the most storied teams in all of football, the 49ers were one of the original teams in the NFL when they joined the NFL in 1950. At that time they were called the San Francisco Forty-Niners, a name that actually came from a fan who thought it would be a cool name. The 49ers original colors were red and gold and their logo was a little man in a red hat on top of a gold football. Those colors and the team name stuck with the 49ers for the next twenty-two years, but when the team moved to the Bay area they decided to make some changes. First they changed their team colors from red and gold to red, white, and blue. They also changed their logo to a flag that showed their new colors, and the man in the red hat was replaced with a miner from the mining days in the Bay area. Those changes stuck with the 49ers for almost thirty years, but when they moved to their new stadium in Santa Clara, California they decided it was time for another change. The Niners kept the same colors, but changed the logo to a more updated version of the old one. The miner was replaced by a red oval with the SF logo in the middle of it, and the new oval was inside a white oval, with a gold border around it.The 49ers were one of the founding members of the NFL, and they made their first playoff appearance in 1957, but did not win their first playoff game until 1982. Even with the bad records the Niners were one of the most well-known teams in the NFL. The Niners were the first NFL team to win five Super Bowl titles, and were named the team of the decade for the 1980s. Even with all of their success the Niners were in the cellar of the NFC West for many years, and that is why they had such a hard time making it to the playoffs. They had a couple of playoff runs in the 2000s, but they have not been to the Super Bowl since 1994.The Niners have made it to the Super Bowl five times, and they won five Super Bowls in the 1980s. They were the team of the decade for the 1980s, and their greatest coach was the legendary Bill Walsh. In the early years of the Niners the team was led by quarterbacks Joe Montana and Steve Young, but they could not get over the hump and make it to the Super Bowl. In the early nineties the Niners picked up a quarterback by the name of Steve Young and he became the greatest quarterback to ever wear the red and white. Young won the MVP award twice, and made it to six Pro Bowls before his career was cut short by an injury. The Niners were also led by running backs Joe Montana and Roger Craig, and wide receivers Jerry Rice and Terrell Owens. The Niners had the most dominant defense in football in the 1980s, and their success has not been matched since then.]" time="0.471"><properties><property name="score" value="0.02722148" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Lists of The Simpsons guest stars\n\nThe following are lists of guest stars who appeared on the television series "The Simpsons".\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n]" time="0.003"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
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assert 'Human' == 'AI'
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- AI
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||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Time Warner Cable reported first quarter financial results Wednesday and Chairman and CEO Glenn Britt said that the company remains committed to delivering high quality products and great customer service.\n\n\u201cOur core business is operating effectively and we are focused on initiatives that will deliver long-term growth. We remain committed to delivering high quality products and great customer service to our customers,\u201d Britt said in a statement.\n\nThe media and communications company posted earnings of $243 million, or 84 cents per share, on revenues of $5.8 billion. Both figures were better than analyst expectations. The company\u2019s net income was down 15 percent from the previous year, but the earnings were still in line with the company\u2019s previous forecast.\n\nTime Warner Cable said its core business operations grew 8.7 percent in the quarter. Total residential customers increased for the third consecutive quarter, increasing 1.7 percent to 11.8 million customers. The company also added 390,000 high-speed data customers in the quarter.\n\n\u201cWe continued to invest in our network to provide the best experience for our customers. In the quarter, we deployed more than 125,000 new customer premise equipment connections and performed nearly 800,000 installations,\u201d Britt said. \u201cIn the quarter, we also significantly expanded our network capabilities to better deliver video and data over our network. We are pleased with the growth in our total high-speed data base, and are optimistic about our ability to continue to grow our business and create value for our customers and shareholders.\u201d\n\nTime Warner Cable said it now serves more than 16 million video subscribers, which is nearly one-third of all basic video subscribers in the U.S. The company also said it has made improvements to its residential service bundle package, which now includes TV and broadband for $89.99 per month.\n\n\u201cWe are pleased with our continued revenue growth and our ability to produce excellent operating income and cash flow in the first quarter,\u201d said Chief Financial Officer Irene Esteves. \u201cWith our steady business growth and the additional flexibility resulting from our recent access line divestitures, we are well positioned to execute on our initiatives to drive continued profitability.\u201d\n\nImage via Flickr user Otto Timm.]" time="0.314"><properties><property name="score" value="0.0016838321" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00168383 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00168383
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Et par k\xf8benhavnske t\xf8jfirmaer er mist\xe6nkt for at have hyret illegale b\xf8rnearbejdere og kr\xe6vet store bonusafregninger. Det er endnu for tidligt at sige, hvordan sagen ender.\n\nSagen om b\xf8rnearbejde, hvor 11 hjeml\xf8se b\xf8rn er kommet til Skandinavien som del af den kinesiske eftersp\xf8rgsel p\xe5 billig arbejdskraft, viser, at der er udfordringer i det danske arbejdsmarked.\n\nDet mener formanden for Socialp\xe6dagogerne, Benny Andersen, der dog kalder sagen meget begr\xe6nset i sin omfang.\n\n- Jeg er sikker p\xe5, at det er en meget lille andel af b\xf8rn, der er ramt af det her, siger han til Ritzau.\n\nSagen kom frem, da en k\xf8benhavnsk virksomhed blev d\xf8mt i K\xf8benhavns Byret for at have kr\xe6vet b\xf8rn i 10-\xe5rsalderen en bonus af virksomhedens \xf8konomi.\n\n- Jeg tror, at der ikke er tale om, at mange danske virksomheder benytter sig af b\xf8rnearbejdere, siger han.\n\nTilbage i 2010 var b\xf8rnearbejde en helt stor sag, og her blev der gennemf\xf8rt en razzia mod virksomheder.\n\n- Vi kan konstatere, at der var problemer med udenlandske b\xf8rn, som blev hyret som l\xf8nmodtagere. Det var der alts\xe5 ikke i dag, hvor vi taler om b\xf8rnearbejde, siger Benny Andersen.\n\nI 2010 var der tale om 28 virksomheder, som blev unders\xf8gt.\n\nSiden har sager om b\xf8rnearbejde, hvor de ansatte ikke har de forn\xf8dne papirer, v\xe6ret noget, man kender til fra omr\xe5det.\n\n- Det kommer vi tilbage til l\xf8bende, for vi kender til problematikken. Hvad der er foreg\xe5et i denne her sag, er der nok ingen, der havde en id\xe9 om, siger formanden.\n\nDerfor skal der nu rettes op p\xe5 problemet, mener Benny Andersen.\n\n- N\xe5r vi har en mulighed for at skaffe billig arbejdskraft fra udlandet, s\xe5 vil vi selvf\xf8lgelig g\xf8re det. Der skal laves en gr\xe6nse for, hvorn\xe5r man kan anvende udenlandske l\xf8nmodtagere, siger han.\n\nDer skal g\xf8res op med, hvad der er h\xe5ndv\xe6rk og hvad der er industri, og de to skal ikke blandes sammen, mener Benny Andersen.\n\n- Det er ogs\xe5 noget af det, der er udfordringen, og derfor skal vi have lavet de n\xf8dvendige kvalifikationskrav. Det betyder, at hvis du skal have lov til at arbejde i Danmark, s\xe5 skal du have en uddannelse, og du skal v\xe6re kvalificeret til det, siger han.\n\nDerudover skal der s\xe6ttes en stopper for social dumping, og der skal strammes op p\xe5 kontrol- og sanktionsmulighederne.\n\n- S\xe5dan nogle her firmaer skal der ikke v\xe6re lov til at v\xe6re, siger Benny Andersen.\n\n/ritzau/]" time="0.309"><properties><property name="score" value="0.003225002" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Artist: Black Sabbath Album: Master Of Reality Song: Sweet Leaf Album Version Tabber: Julian Here is the master of reality album version. Just listen to the album for the intro. intro /---12-12-12-12-12-12-12-12-12-12-12-12-12-| /-9---9--9--9--9--9--9--9--9--9--9--9--9--9-| /-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-| /-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-9-| /-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-| /---------------------------------------| play this 2 times verse /-----10----10---9---------------------------------| /-9------9----9---9---------------------------------| /-9---9---9---9---9---------------------------------| /-9----9---9---9---9---------------------------------| /-7----7-----7---7---------------------------------| /-----------------------------------------------| x2 Chorus /-----10--9------9--9-------------------------------| /-9------9------9--9-------------------------------| /-9--9--9--9--9--9--9-------------------------------| /-9--9--9--9--9--9--9-------------------------------| /-7--7--7--7--7--7--7-------------------------------| /----------------------------------------------------| Guitar solo /-15-12------------------------------------------| /-------14-12-10-9-----------------------10-9-7-| /----------------12-10-9----7-9-10-12-10-------| /-----------------------------------------11-9---| /----------------------------------------------------| /----------------------------------------------------| the solo is just a mixture of fast pick-slinging and heavy bends, theres no real order to it. Hope it helps. [ Tab from: http://www.guitartabs.cc/tabs/b/black_sabbath/sweet_leaf_tab_ver_3.html ] Related for Sweet Leaf tab Black Sabbath - Electric Funeral tab\n\nBlack Sabbath]" time="0.293"><properties><property name="score" value="0.7693136" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Tesla Shorts: 5 Signs They Are Dead Wrong\n\n\n\n\n\n\n\n\n\nSome analysts predict that Tesla Motors (NASDAQ:TSLA) is overvalued, while others expect that it\u2019s just beginning to find its niche. A recent report by Kelley Blue Book indicates that sales of plug-in electric vehicles (EV) are gaining market share. As a result, Tesla is poised to benefit from the EV revolution.\n\nSource:Kelley Blue Book\n\nSales of plug-in electric vehicles (EV) have grown significantly from 2011 to 2013. In that span, the EV market share increased from .33 percent to 1.4 percent. Moreover, Kelley Blue Book predicts that EVs could account for 4 percent of new car sales in the US by 2020.\n\nTesla Motors is also poised to capitalize on this trend. The company is highly regarded as a leader in the EV market. Tesla\u2019s Model S was named Motor Trend\u2019s 2013 \u201cCar of the Year\u201d and was the Consumer Reports top rated EV of 2013.\n\nModel S sales are expected to increase significantly in 2014 as Tesla is rolling out more affordable models. Tesla is also benefiting from the increased supply of lithium-ion batteries. According to Lux Research, the EV market is growing at an average of 21.6 percent per year and is expected to grow to $7.5 billion in 2020.\n\nSource: Lux Research\n\nDespite these positive developments, Tesla shorts continue to prevail. Despite the gains in the stock price, Tesla shorts are sticking to their bearish bets. Tesla shorts have bet against the company for over three years. Currently, there are 35 million Tesla shares that are sold short, and the shorts are holding on to the shares despite the rebound in the stock price.\n\nSource:Bloomberg\n\nThe recent gains in the stock price have not been enough to satisfy short sellers. More than 27 million shares were sold short in the first quarter of 2014 alone. Tesla shorts are also comfortable with shorting the company at its current valuation.\n\nWith the current short interest, Tesla shorts could be forced to close their short positions by the end of the second quarter. However, some Tesla shorts could still be holding on to their positions despite the closing of the shorting window.\n\nIn the meantime, Tesla continues to deliver on its promises. The company continues to roll out its new product lines, and it is also opening new Tesla stores around the world.\n\nTesla shares continue to be a favorite short among hedge funds. According to FactSet, the shares are one of the most shorted companies in the S&P 500. Tesla short interest is more than three times higher than that of General Motors (NYSE:GM) and about five times higher than that of Ford Motor (NYSE:F).\n\nGeneral Motors short interest as of 04/02/2014\n\nFord Motor short interest as of 04/02/2014\n\nDespite the record short interest, Tesla is going from strength to strength. The company is expanding its product line, and it is well on its way to dominate the EV market. Additionally, the company has surpassed its 2014 production targets. In the meantime, Tesla shorts are in for a long wait.]" time="0.300"><properties><property name="score" value="0.0022241923" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00222419 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00222419
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Imagine being chased by a giant predator, only to have it turn around and attack the other way because you\u2019re wearing one of these\u2026\n\nChased by a giant, hungry Tyrannosaurus rex, a creature of comparable size would be within its rights to be scared out of its mind.\n\nBut as it is a tiny dinosaur, one \u2018prehistoric\u2019 animal can\u2019t help but giggle at the sight of a ferocious beast roaring at it.\n\nTo view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video\n\nThe cute animal is shown with its mouth wide open as it tries to stifle a laugh at the absurdity of the situation.\n\nThe T-Rex is then heard screaming as it chases the creature around the field, only to turn around and flee after spotting the tiny intruder.\n\nThe clip, which is titled \u2018I F**king Love Dinosaurs\u2019, was created by 22-year-old American comedian and internet star Devin Graham, who has amassed nearly five million YouTube followers.\n\nAdvertisement\n\nAdvertisement\n\nAt one point in the video, the little dinosaur looks at the camera and waves at the viewer, which has led some viewers to believe that it was a real creature and not a computer-generated one.\n\nThe video was uploaded on April 13 and has already had over 70 million views.\n\nHowever, it has also been accused of being \u2018disturbing\u2019 by some viewers.\n\nWriting in the comments section, one viewer said: \u2018This is one of the scariest videos on the internet.\u2019\n\nAnother added: \u2018That\u2019s not a real dinosaur. If it was, they wouldn\u2019t be laughing like that.\u2019\n\nOthers have claimed that the footage was faked using computer-generated imagery.\n\nOne viewer posted: \u2018Pfft, CGI.\u2019\n\nHowever, others have jumped to the dinosaur\u2019s defence.\n\nOne commented: \u2018It\u2019s clearly a cartoon. But still, this is a really cute video.\u2019\n\nMORE: Yes, I ate bacon when I was pregnant, and no, my baby didn\u2019t end up with meat for brains\n\nMORE: Vegan pizza shop owner \u2018blocked\u2019 by Italian villagers after they blamed her for \u2018killing\u2019 the town\u2019s business\n\nAdvertisement Advertisement]" time="0.288"><properties><property name="score" value="0.0026156711" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00261567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00261567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Another fabulous book that was recommended to me by the other half!\n\nHe has read every single one of G.A. McKevett\u2019s books and this is the first one he read so it had a lot to live up to!\n\nAlthough this is a fantasy, it\u2019s one of the few fantasy novels that I\u2019ve read that doesn\u2019t involve vampires, werewolves, fairies or anything else from the realms of fiction!\n\nThe Other Half says it\u2019s the best fantasy novel he has read since Robert Jordan\u2019s Wheel of Time series. I would tend to agree as I found it a hard book to put down, which is rare these days when I have a million things I should be doing instead of reading!\n\nThe general premise of the book is that after a five thousand year old war is over, the winners decided to punish the losers by killing every last man, woman and child and then removing every trace of their existence, erasing them from history.\n\nThe losers, the Omotans, are considered to be not just defeated but almost evil, and so to keep them out of sight they were forced to hide their magical abilities and instead focus on developing their science.\n\nOne man decided he would rather be a freak in his own time than a hero in somebody else\u2019s. This man is the greatest sorcerer in all of the Nine Kingdoms and also happens to be a total maniac.\n\nArriving back in our time, he has one purpose; to find all his descendents and kill them. His reasoning is that if they die in the future he will never be born in the past so he will never be able to go back and kill them!\n\nThis is where the fun begins\u2026\n\nIf you like fantasy novels that are based in our world then you are in for a real treat.\n\nIt\u2019s just as well I was given this book for Christmas as I would have been really pissed off to have had to wait months for the sequel, which was published last month.\n\nIt\u2019s a real page turner, not a boring minute. It would be a great gift for anyone who enjoys reading fantasy but doesn\u2019t want to be drowned in vampires and elves!]" time="0.342"><properties><property name="score" value="0.027452907" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02745291 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02745291
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Gonzaga\u2019s Zach Collins, right, and Johnathan Williams react to a play during the Bulldogs\u2019 matchup against San Diego State at Viejas Arena in San Diego on Dec. 3. The Bulldogs won, 78-59. (Photo: AP)\n\nThe always-lively discussion of the NCAA Tournament selection committee's biggest and best blunders (which usually is a list of blunders) has been further fueled by a freshman who's now in the mix for being one of the biggest and best picks of the first round in Thursday night's draft.\n\nAnd by all accounts, Gonzaga's Zach Collins was, in fact, one of the biggest and best players in the nation this past season.\n\nDarn it, somebody in the official outfit that has the Final Four placements, the brackets and the selections did a superb job in providing a team that was vastly superior to a top-10 team with a second chance to participate in a college basketball tournament.\n\nZach Collins, a 7-foot, 230-pound center from Las Vegas, was the team's third-leading scorer this past season, behind Przemek Karnowski and point guard Nigel Williams-Goss.\n\nBuy Photo University of Nevada head basketball coach Eric Musselman coaches during the second half of his team's NCAA basketball game against the Boise State Broncos at Lawlor Events Center in Reno on Thursday, February 16, 2017. Nevada won 76-69. (Photo: Tom R. Smedes/Special to the RGJ, Tom R. Smedes/Special to the RGJ)\n\nCollins was instrumental in Gonzaga's winning the West Coast Conference tournament and advancing to the Elite Eight. He scored 20 points in the first half in the opening-round win over Texas Southern, and that was one of the top performances in the tourney.\n\nCollins is slated as a lottery pick in the draft. His brother, 6-9-180 center John Collins of Wake Forest, also is in the mix as a first-round pick.\n\nHere's the thing: What if Collins had chosen to play for the Wolf Pack this past season? The WCC would have been a little bit better. The Zags would have been less impressive.\n\nHe would have played in the Mountain West, and in most cases, there was not a huge discrepancy between the Mountain West and the WCC in the 2016-17 season. In the first seven games of the season, Nevada won five times, which was nearly identical to the Zags' win total over the same period.\n\nFor the season, Gonzaga was 33-2, and Nevada was 28-7. The Zags played in the NCAA Tournament. The Wolf Pack didn't.\n\nWas Collins a first-round pick in that alternate reality? Probably not, but there's a good chance he would have been drafted, and it would have been by one of the NBA teams that had an interest in him.\n\nWilliams-Goss decided to transfer to Gonzaga from Washington, but had he stayed in Seattle, Collins would have been recruited by the Huskies. In the end, it may have been a long shot that Collins would have accepted the scholarship, but then again, who knew he would be such a talent?\n\nBut, maybe Collins did decide to play for the Wolf Pack, and then maybe Williams-Goss stayed in Seattle. And then maybe Collins and Williams-Goss played against each other for the championship of the Mountain West in 2016-17, and maybe it would have been a game for the ages.\n\nCollins, who averaged 10.0 points and 5.9 rebounds for the Zags, and Williams-Goss, who averaged 17.7 points and 6.0 assists, were both vital to the outcome of that hypothetical contest.\n\nAnd it may have gone down as one of the best games in league history. But you and I will never know.]" time="0.517"><properties><property name="score" value="0.16099119" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.16099119 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.16099119
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Just got back from the dealer.\n\n\n\nThe PRNAV info is stored in a table within the databases on the ECT. The PRNAV is built into the system on the cars but they can't offer it for the cheaper units as they can't change the unit to add it in.\n\n\n\nFor now they can either do a full ECT replacement for $700 or do a drivetrain swap that has the PRNAV for the same cost.\n\n\n\nThis was done with one of the systems for a different user and they can get one to work and offer it to others.\n\n\n\nA bit more expensive but at least it's available.\n\nCurrent:\n\n2015 Hyundai Genesis Sedan 3.8 AWD - 41,000 miles (more mods)\n\n2012 BMW 650i Coupe - 32,000 miles (retired)\n\n2001 Acura TL 5 Speed - 87,000 miles (retired)\n\n\n\nPrevious:\n\n2014 BMW 328xi Sedan 6 Speed - 38,000 miles (retired)\n\n2013 BMW 328xi Sedan 6 Speed - 12,000 miles (retired)\n\n2013 Ford Edge Sport AWD - 28,000 miles (retired)\n\n2006 BMW 325xi Sedan 6 Speed - 108,000 miles (retired)\n\n2005 Audi A4 3.2 Sedan 6 Speed - 126,000 miles (retired)\n\n2004 Toyota Prius - 130,000 miles (retired)\n\n2000 Ford Contour SE V6 - 215,000 miles (retired)\n\n1990 Ford Escort LX 5 Speed - 238,000 miles (retired)]" time="0.302"><properties><property name="score" value="0.69866335" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.69866335 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.69866335
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[CLOSE State Senator Frank Artiles apologized for using racial slurs and profanity in a conversation with two African-American colleagues in the Florida Capitol. He resigned Friday, April 21, 2017. Wochit\n\nFlorida Sen. Frank Artiles, R-Miami, listens to debate in the House Chamber on the opening day of the legislative session in Tallahassee, Fla., Tuesday, Jan. 10, 2017. (Photo: AP Photo/Mark Wallheiser)\n\nMIAMI \u2014 In an extraordinary late-night series of events on the opening day of the Florida legislative session, Republican Sen. Frank Artiles resigned from his seat after the South Florida political community expressed outrage over his conduct.\n\nIn his resignation letter, Artiles cited the \u201charmful and embarrassing distractions\u201d his presence would cause his fellow senators, his constituents and the people of Florida. The resignation is effective at midnight.\n\nBut Artiles\u2019 tenure in the Florida Senate wasn\u2019t going to last much longer anyway.\n\nAfter his racist and sexist remarks to two African-American senators were made public on Wednesday, he was facing expulsion proceedings from the Florida Senate.\n\nA little more than 24 hours later, he was gone.\n\n\u201cThis was not an easy decision to make, but I do believe it is in the best interest of my constituents,\u201d Artiles said in his resignation letter. \u201cI apologize to my family, friends and most importantly to my constituents.\u201d\n\nMore: Sen. Frank Artiles apologizes for 'offensive' comments at black lawmakers\n\nMore: Gov. Rick Scott suspends Sen. Frank Artiles over racial tirade\n\nMore: Florida senators blast colleague's 'racist' comments\n\nArtiles, a second-term senator from Miami-Dade County, was facing an expulsion vote from the Senate after a fellow Republican, Sen. Jack Latvala of Clearwater, filed a resolution Wednesday night to begin proceedings.\n\nLatvala's resolution said Artiles \u201cused offensive, racist and disrespectful language\u201d during an exchange on the Senate floor with fellow Democratic Sen. Audrey Gibson of Jacksonville and Democratic Sen. Perry Thurston of Fort Lauderdale.\n\nIn a statement Wednesday night, Senate President Joe Negron, R-Stuart, said he was \u201cappalled\u201d by Artiles\u2019 comments and said Artiles will publicly apologize to Gibson and Thurston on the Senate floor Thursday morning.\n\nCLOSE State Sen. Frank Artiles explains why he apologized on the Florida Senate floor Wednesday, April 19, 2017.\n\n\u201cRacial slurs and profane, sexist insults have no place in conversation between Senators and will not be tolerated while I am serving as Senate President,\u201d Negron said. \u201cSenator Artiles has requested a Senate apology. I understand his decision to resign and appreciate his willingness to do the right thing.\u201d\n\nLater, Negron released a statement saying Artiles has resigned.\n\nLatvala said in a brief interview Thursday that the chamber was expected to approve his resolution on a \u201cvoice vote\u201d \u2014 with the expectation that Artiles would be expelled.\n\n\u201cThe public expected us to take action, and I was going to be the one who was going to do it,\u201d Latvala said.\n\nBut he said the resignation was an unexpected turn of events. \u201cIt\u2019s amazing,\u201d he said.\n\nLatvala said Artiles\u2019 Republican colleagues would have been happy to expel Artiles, but he added, \u201cI don\u2019t think that was his goal, or I don\u2019t think he expected it.\u201d\n\nLatvala also criticized the Senate Democratic caucus for not publicly demanding Artiles\u2019 resignation. He said he wasn\u2019t sure whether the chamber would have expelled Artiles had he not resigned.\n\n\u201cWe would have done something,\u201d he said.\n\nLatvala said Artiles\u2019 resignation means the Senate will hold a \u201clame-duck\u201d session in which he will be able to collect a paycheck for about two more months.\n\n\u201cIt\u2019s the taxpayers\u2019 money,\u201d]" time="0.497"><properties><property name="score" value="0.00085981993" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00085982 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00085982
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280]" time="0.704"><properties><property name="score" value="0.00439854273" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Maybe it's because this was the only game in town, but both of these types of games have grown stale to me. I feel a lot of that is due to having seen the pattern so often that I know when the surprises are coming. I have not played Final Fantasy XII yet but I have no reason to think that this one is going to be any different. The only thing I can say that would be new is that the maps are going to be quite large. And even that is starting to feel more like a gimmick and less like something that adds to the game play. If it weren't for this system, I wouldn't be able to enjoy these games.\n\n\n\nWhile this system isn't perfect, it's better than the way it was in FFX. This system allows you to do things without being tied to one person or just your party. If I had any complaint, it would be that you still have to level up.\n\n\n\nAlso, a lot of people are saying that it will be more like X. While I agree that it's a lot like X, it's also much like X-2. That is, you get a new license board to progress the characters. You're given more freedom to change up your party and strategy. You have a lot of new abilities for the characters to use.\n\n\n\nI actually really enjoy both of these games. As far as I'm concerned, it's a toss up between X and XII. Either game would have been fine to be the last game in the series. I don't think there was a bad choice between the two. If there is one difference between the two, it's that XII is a lot more fast paced. I don't feel the need to grind as much in XII. Also, I like that you get more character development in XII.\n\n\n\nI just don't see the problem with having more than one person telling you what to do. It just depends on the story as to who it will be. It's not going to be every single person you meet. And if you have so much dialogue with everyone you meet, the game would become boring really fast.\n\n\n\nIt's hard to say if the game is going to be good or not. I'm not going to complain if it isn't, though. The game is out of Nomura's hands and even if it is a bit different from the previous games, that doesn't mean it's bad.]" time="0.285"><properties><property name="score" value="0.010504046" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nTags\n\nBack to list of posts\n\nThe reason for this is that in this kind of market, you don't want to be in an equity investment. You want to be in safe securities which don't fluctuate too much. Like CDs. If you keep a fixed amount of money in a CD and the interest rate stays constant (or goes up), you know that your fixed amount is not going to fluctuate in value by too much.So, to start, let's think about some long term goals that you have. What do you want to do 5 years from now? 10 years? 20 years? Where would you like to be financially? Have you set some specific goals for yourself?This is my story. In the meantime I will be working on getting that monkey off my back and regaining control of my life. Its very hard and as Ive said before, very humbling. Im not a perfect person. But I am a person with potential. I know this for a fact because I have seen my potential and I have achieved it. And now I have this debt and it has me worried and scared. I have my heart set on purchasing a house in the near future and I know that this has to happen for that to happen.When people are looking for financial advice they usually get a lot of conflicting information. Some may even suggest that they put all of their money into gold and that is the best place to put it. However, if you are looking to learn more about gold and where the best places are to invest your money, you need to keep reading. And with the Olympics out of the way, I'd like to know, where does the free market lead us now. Something like a new commercialization of Olympism. Something much more like the Great Global Gladiators' Track & Field Stadia Circus. Something a little more like the Disneyworld of the future. Or maybe, something a little more like the planet Saturn. Possibly more like the Cold War, played out to the bitter end.I've been through some very rough times in the last two years. I have lost my father to cancer and I have lost my best friend to financial troubles. I've also spent the last two years unemployed. I worked for several months to earn money to pay for my wedding. But shortly after I was married, I lost my job. Then my husband lost his job. And our financial situation really started going downhill. I knew I needed to take control of the situation and I knew I needed to do it fast.I started by looking for a second job. I found one working in a local deli, but it didn't pay much. We cut back on our expenses as much as we could. We also looked into some debt management programs. Unfortunately, none of the debt management programs I looked at seemed to work for our situation. They all wanted us to sign up for a 3 or 5 year program and our creditors were so aggressive that it didn't seem like that would be a good idea.So I went looking for financial advice. I found a website that gave me some really great ideas about how to pay off our debt. They suggested the debt snowball technique. With the debt snowball technique you start paying off the debts with the lowest balances. You pay as much as you can on these debts each month and you throw every extra penny you can at them. As these debts get paid off, you roll the money that you were using to pay off those debts into the next highest balance debt. This helps to increase your debt payoff each month and really gets things moving in the right direction.The debt snowball technique worked great for us. We got the money we needed to pay off our debts and we didn't have to make any sacrifices at all. I highly recommend it to anyone who is struggling with debt. It can really work great for you if you can find the extra money to throw at your debts.It's a good question, because it's a hard question to answer. If you are very motivated to make a lot of money fast, I'd recommend you go with your passion. You are likely to enjoy it more, and as a result you will work hard to make it happen. A related question that people often ask is, "What is the best industry to start a business?" I recommend that you start by picking an industry you enjoy, rather than trying to find the "best" industry.I believe the hardest part is getting a home business started. If you are new to internet marketing, you probably don't have a large following yet. Your best chance of succeeding is by offering people some sort of freebie. If you can get enough people to follow you, you can begin to make money.]" time="0.449"><properties><property name="score" value="0.04557331" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[[SI-LIST] Re: Some more responses on DAI\n\nI just got my FPGA design up and running and I'm not sure what is\n\nwrong. I'm working with an Altera 2500 series FPGA and have a PCI\n\nstandard PCI bridge design.\n\n\n\nHere's what I'm trying to do:\n\n\n\n1. If I have the PCI bus pulled high to the 3.3v supply, the bus\n\ndoesn't work, obviously.\n\n\n\n2. If I put the 3.3v high impedance power up, the bus doesn't work.\n\n\n\n3. If I put the 3.3v up and the pull the bus low (no connect on the\n\nPCI pins) the bus doesn't work.\n\n\n\nThe reason I'm going for this is because I have a great PCI\n\nbridge design that I want to use and I don't want to re-implement\n\nit.\n\n\n\nIs there something I'm missing here?\n\n\n\nThanks,\n\nRyan Kahl\n\n\n\n__________________________________________________________________________________\n\nThe best anti-spam money can buy. We never spam, we just stamp it.\n\nTry a trial!\n\nhttp://web.tiscali.co.uk/mail/go.pl?m=outgoing_sig&id=14230&u=BOBSIG\n\n\n\n-- [ Picked text/plain from multipart/alternative ] We seem to have received a lot of similar questions this week. Here are a few answers, so that we can hopefully help others. Richard Sheppard wrote:>> 1. Can a single DAI be used for different data rates? I'm not>> familiar with the internal functioning of DAI, but would imagine that>> each must be configured for the speed of the channel, so if there is>> not a configurable counter or similar, then a new DAI would be needed for>> each data rate.>> 2. Would it be correct to think of a DAI as similar to a multi-mode>> switch, where each channel has it's own connection, but they all share the>> same switch? The switching will be done at the channel driver, or>> is it done at the DAI?> Richard,> A single DAI can be used for different data rates, but it will only have> one speed wire in and one speed wire out. A multi-mode DAI will need> a speed wire in and a speed wire out for each speed supported.> The original spec for the DAI specified the speed wires. These were> always at the channel driver level, which is why I think the original> spec doesn't say anything about high impedance. I'm not sure what the> actual implementation is]" time="0.291"><properties><property name="score" value="0.2181653" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Meghan Markle and Prince Harry are the next generation of royalty, but they have been married long enough that it\u2019s possible to see some of the ways in which Meghan has begun to influence the royal family in her short time as a member of it. She has a busy schedule as a royal and still finds time to make the world a better place, and that includes doing her best to break down gender roles in the monarchy and challenge perceptions of what it means to be a royal bride.\n\n\n\nWhile she has been criticized by some for the way she dresses, she\u2019s also done her part to change the way royal brides have traditionally looked in the past, as well as the types of charitable efforts they\u2019ve participated in to promote their causes.\n\n\n\nMeghan\u2019s influence is evident in the family as it adapts to the more progressive changes that she brings to the monarchy. She\u2019s done everything from change her last name to start a new royal legacy and represent women\u2019s right to equality, to giving a voice to the marginalized through her various charitable causes.\n\n\n\nIn the spirit of changing the royal narrative, let\u2019s take a look at some of the ways Meghan has broken the mold as a royal bride, and what that means for the future of the monarchy.\n\n\n\n1. Using her platform to make a change\n\nMeghan\u2019s position as the Duchess of Sussex gives her a unique platform that allows her to promote causes she cares about, from racial equality to gender equality to her favorite charities. She\u2019s used that platform to make a difference for women and girls.\n\n\n\n2. Being the face of the #MeToo and Time\u2019s Up movements\n\nShe was the first royal to speak out about the #MeToo movement, the backlash against women speaking out about sexual harassment and abuse, and what she calls the \u201cheavy burden\u201d of being a woman in the public eye. In a rare interview with the BBC, she spoke about how she\u2019s always been aware of how sexism and racism have been barriers that she had to overcome, and that she is pleased to see the MeToo and Time\u2019s Up movements making their mark on society and the public at large.\n\n\n\n3. Standing by her husband during the #MeToo movement\n\nShe made a conscious decision not to speak out about the backlash against her husband\u2019s former girlfriends, like her rumored rival Meghan Markle, as she has refused to criticize other women. She doesn\u2019t play the victim, but instead encourages women to speak out against abuse and fight for equality in every aspect of their lives.\n\n\n\n4. Becoming a philanthropist and charity ambassador\n\nShe\u2019s been an ambassador for the United Nations Children\u2019s Fund (UNICEF) since the beginning of 2018. She promotes their various projects, including the fight against the water crisis in East Africa, and the importance of providing women and children with safe drinking water and adequate sanitation services.\n\n\n\n5. The fashion choices she makes as a royal bride\n\nWhile Meghan is often criticized for her outfits and looks by members of the public, she\u2019s broken a few rules and worn clothes that had never been worn by previous royal brides. She\u2019s broken the tradition of a royal bride wearing all white by wearing a black pantsuit by Stella McCartney to her wedding. She\u2019s also chosen a number of different designers for her wedding gowns, and has worn outfits that are a little more modern in their style.\n\n\n\n6. As a role model for women and girls\n\nMeghan has made it clear that she wants to use her influence to promote the idea that women and girls can do and be anything, including princesses. She\u2019s spoken openly about the obstacles she faced as a biracial woman in America and has spoken about how her mother taught her to be strong, to never give up, and to push through any obstacles.\n\n\n\n7. Using her fame to help women in other countries\n\nShe\u2019s spoken about how the public should be \u201cmindful\u201d of women in other countries when they\u2019re giving out opinions and criticisms about women and their clothing. She wants to ensure that women from different cultures are able to make decisions for themselves about what they wear and how they present themselves to the world.\n\n\n\n8. Embracing and changing royal tradition\n\nShe\u2019s already had two official residences as a royal wife, making it clear that she\u2019s going to have her own role and position in the monarchy. She\u2019s also kept her maiden name and made it clear that she won\u2019t be taking the traditional route for royal brides by doing so. She\u2019s already used her influence to change royal tradition and make it more inclusive for women, as well as to make her own path in the monarchy.\n\n\n\nIt\u2019s clear that Meghan has made it her mission to challenge the perception of what it means to be a royal bride, and change the way that the monarchy interacts with the public. She\u2019s already taken steps to set herself apart from other royal brides and has broken the mold in so many ways that future royal brides are sure to look to her as a role model.]" time="0.296"><properties><property name="score" value="0.0134063625" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01340636 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01340636
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Manual de T\xe9cnicas de Neuromarketing\n\nPor Richard A. D\u2019Aveni\n\nEditorial Edelvives (www.edelvives.com)\n\nDistribuidor oficial en Espa\xf1a: Marketing Centro de Estudios (www.marketingcee.com)\n\nManual de T\xe9cnicas de Neuromarketing\n\n\xa9 Richard A. D\u2019Aveni, 2007\n\n\xa9 Editorial Edelvives, S.A., 2007\n\nDise\xf1o de cubierta y maquetaci\xf3n: Mario Salmer\xf3n\n\nISBN: 978-84-93811-38-0\n\nDep\xf3sito legal: M-8835-2007\n\nReservados todos los derechos. Ninguna parte de esta obra puede reproducirse, almacenarse o transmitirse, en cualquier forma o por cualquier medio, mec\xe1nico, fotoqu\xedmico, electr\xf3nico o de cualquier otra manera, sin permiso escrito del editor.\n\n\xcdndice\n\nPr\xf3logo\n\nCap\xedtulo 1\n\nEste libro tiene dos objetivos\n\n3\n\nCap\xedtulo 2\n\nLa neuromarketing\n\n5\n\nCap\xedtulo 3\n\nLa visi\xf3n del consumidor\n\n7\n\nCap\xedtulo 4\n\nT\xe9cnicas para el estudio de las preferencias\n\n10\n\nCap\xedtulo 5\n\nManejo de la confianza\n\n11\n\nCap\xedtulo 6\n\nManejo del consumidor\n\n12\n\nCap\xedtulo 7\n\nManejo del h\xe1bito\n\n13\n\nCap\xedtulo 8\n\nManejo de la relaci\xf3n\n\n14\n\nCap\xedtulo 9\n\nManejo de la situaci\xf3n de la marca\n\n15\n\nCap\xedtulo 10\n\nLas reglas b\xe1sicas de la publicidad\n\n17\n\nCap\xedtulo 11\n\nLas reglas b\xe1sicas de la publicidad y la atracci\xf3n\n\n20\n\nCap\xedtulo 12\n\nLas reglas b\xe1sicas de la publicidad y la psicolog\xeda\n\n22\n\nCap\xedtulo 13\n\nLas reglas b\xe1sicas de la publicidad y la memoria\n\n23\n\nCap\xedtulo 14\n\nLa publicidad es una modalidad para aumentar la\n\nl\xednea de base de la marca\n\n24\n\nCap\xedtulo 15\n\nLa publicidad es una forma de hacer entrar la marca\n\nen la mente\n\n25\n\nCap\xedtulo 16\n\nLa publicidad es una forma de generar conocimiento\n\n26\n\nCap\xedtulo 17\n\nLa publicidad es una forma de encontrar consumidores\n\n27\n\nCap\xedtulo 18\n\nLa publicidad es una forma de generar informaci\xf3n\n\n27\n\nCap\xedtulo 19\n\nLa publicidad es una forma de reconocer marcas\n\n28\n\nCap\xedtulo 20\n\nLa publicidad es una forma de activar marcas\n\n29\n\nCap\xedtulo 21\n\nLa publicidad es una forma de hacer sentir el\n\nproblema\n\n30\n\nCap\xedtulo 22\n\nLa publicidad es una forma de llegar al problema\n\n31\n\nCap\xedtulo 23\n\nLa publicidad es una forma de conectar marcas con\n\nlos problemas\n\n32\n\nCap\xedtulo 24\n\nLa publicidad es una forma de hacer una venta\n\n33\n\nCap\xedtulo 25\n\nLa publicidad es una forma de hacer una venta\n\n34\n\nCap\xedtulo 26\n\nLa publicidad es una forma de hacer una]" time="0.343"><properties><property name="score" value="0.00081597466" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["You're telling me you'd prefer me when I was a glum, weeping, sickly, frightened little girl?"\n\n"Oh, yes," said the Queen. "Then you did what I told you." \u2015The Queen of Hearts and Alice [src]\n\nThe Queen of Hearts, often referred to as the Mad Hatter, is a fictional character and antagonist in Lewis Carroll's fantasy novels, Alice's Adventures in Wonderland and Through the Looking-Glass. She is a very brash, temperamental monarch who holds her court in the presence of playing cards.\n\nContents show]\n\nHistory Edit\n\nMadness Edit\n\nOne day, the White Rabbit was late for a very important date. It was the Queen of Hearts' desire that all subjects be on time and therefore she accused the rabbit of stealing her tarts. The poor creature was sentenced to death, but Alice interceded and the rabbit was saved. The Queen became suspicious of Alice and ordered her execution. However, the child escaped from the palace and the Queen's guards.\n\nAlice soon met the White Rabbit and they followed the March Hare and the Hatter to the cottage of the Dormouse. After a long conversation, the Mad Hatter ordered her servants to seize the White Rabbit and bring it to the trial. Alice entered the scene again and the Queen ordered her death sentence. She then asked for an executioner and it was the Knave of Hearts who came to execute her. Alice then escaped into the woods with the White Rabbit.\n\nAlice later met the Queen again, this time at the Mock Turtle's story. The Queen ordered Alice to be executed, but the Gryphon saved the girl.\n\nFinding the Red Queen Edit\n\nThrough the Looking-Glass and What Alice Found There Edit\n\nBehind the scenes Edit\n\nAppearances Edit]" time="0.298"><properties><property name="score" value="0.22334322" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.22334322 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.22334322
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Abstract\n\n2\n\n2\n\n2\n\n2\n\nThe effect of residual carboxylic acids (RCA) on the color formation of catechin/TEMPO-O/hydrogen peroxide (HTP) radical cation (RCAT) systems was studied in the presence of NaF, Na, or NaOH. It was found that addition of RCA in TEMPO-O/HTP systems greatly affected the color change of the color reagent (CRC) to orange-brown, and the color intensity varied with the concentration of Na. Increasing the concentration of RCA in the system was found to affect the nature of the color change; whereas, when RCA was present at low concentration (0.01 mmol/L), it induced the color to change from orange-brown to pink-red at pH 2.5, but caused a second change in color from pink-red to dark brown-black at pH 9.5. In contrast, when RCA was present at high concentration (0.1 mmol/L), it induced the color change from orange-brown to dark brown-black at pH 2.5, and from orange-brown to red at pH 9.5. It was also found that RCA increased the rate of TEMPO reduction in the absence of HTP, and the redox peaks at +0.53 V and +0.25 V could be observed in the 1H NMR spectra of the RCAT system. The ability of RCA to function as a redox mediator for HTP reduction is important in controlling the color of the CRC system, and can be used as a promising approach to develop novel colorimetric assay systems. View Full-Text]" time="0.304"><properties><property name="score" value="0.6042765" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6042765 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6042765
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Showing all 4 plot summaries\n\nWhile directing a musical film for MGM in France, Judy Garland is discovered by a 20-year-old French college student who loves the American star's films. He stalks her, but when she finds out about it, she is flattered and falls in love with him. - Written by John Oswalt <jao@jao.com>\n\nIn France in 1951, an idealistic and wistful young film student, Gerard (Gilbert Becaud) is in love with the American film star Judy Garland, who is starring in a musical film there, as he follows her around to get an interview with her. At first he is confused by the older men who pursue the film star for all sorts of reasons, not least of which is that he meets a fellow student, Guy (Daniel Ceccaldi) who is also smitten with the star. Eventually he works up the nerve to talk to her and then just follows her around, as she is put up in a luxurious suite and given flowers and chocolates. After a few weeks he is exhausted, but takes some time off to visit his sick father. He arrives back just as the film wraps up, and the first thing she does is to make a phone call to his hotel. This encounter is not in the script, but it will change his life. - Written by garykmcd\n\nIn 1950s France, a young film student named Gerard takes a break from the Paris film school where he's been trying to interview Hollywood star Judy Garland, and heads for the country to visit his ailing father. By the time he returns to Paris, the studio that was producing Garland's film has shut down and the star has left town. Gerard decides to give up his pursuit of Garland and heads back to the country. That's when he bumps into her and is summarily invited to her hotel room. It's there that Gerard learns that he and Garland have a lot in common. And he's stunned to find out that the young woman he's been pursuing is also smitten with him. - Written by frankfob2@yahoo.com]" time="0.299"><properties><property name="score" value="0.012356942" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01235694 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01235694
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u041a\u043e\u0434:\n\n<div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li> <li class="active"><a href="#">\u8a3a\u7642\u79d1\u76ee\u540d</a></li> </ul> </div> <div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7<span class="icon-home"></span></a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li> <li class="active"><a href="#">\u8a3a\u7642\u79d1\u76ee\u540d</a></li> </ul> </div> <div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7<span class="icon-home"></span></a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li> <li class="active"><a href="#">\u8a3a\u7642\u79d1\u76ee\u540d</a></li> </ul> </div> <div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7<span class="icon-home"></span></a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li> <li class="active"><a href="#">\u8a3a\u7642\u79d1\u76ee\u540d</a></li> </ul> </div> <div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7<span class="icon-home"></span></a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li> <li class="active"><a href="#">\u8a3a\u7642\u79d1\u76ee\u540d</a></li> </ul> </div> <div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7<span class="icon-home"></span></a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li> <li class="active"><a href="#">\u8a3a\u7642\u79d1\u76ee\u540d</a></li> </ul> </div> <div class="container"> <h1 class="text-center"> <a href="index.html">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7<span class="icon-home"></span></a> </h1> <ul class="nav nav-pills"> <li><a href="#">\u8a3a\u7642\u79d1\u76ee\u4e00\u89a7</a></li]" time="0.360"><properties><property name="score" value="0.000189275" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[La rete di multiservizi Rete di multiservizi e rete ottica, dal 1997 al 2017 Trasporto linee ADSL Comune (CC) Copparese Fontegreca Gaiarine Lorenzana Mansue' Orsara di Puglia - Isernia Scapoli (D) Scapoli Scapoli Scapoli Serracapriola Serracapriola Serracapriola Serracapriola\n\nMultiservizi La connessione a Internet all'interno di una zona urbana \xe8 realizzata tramite pi\xf9 fornitori con diversi canali di comunicazione, tra cui l'ADSL (Asymmetric Digital Subscriber Line), l'alta velocit\xe0 con tecnologia FTTCab (Fiber to the Cabinet), FTTB (Fiber to the Building) e FTTH (Fiber to the Home).\n\nFiber to the cabinet \xc8 uno standard tecnologico per la connessione a Internet mediante fibra ottica che permette di ottenere velocit\xe0 di download fino a 30 Mbps, mentre la velocit\xe0 di upload \xe8 minore. Pu\xf2 essere installato connesso in modo indipendente o riutilizzando le infrastrutture della rete telefonica tradizionale (ADSL).\n\nFiber to the home \xc8 una tecnologia di trasmissione dati per la connessione a Internet, in grado di offrire velocit\xe0 di download fino a 1.000 Mbps e velocit\xe0 di upload fino a 200 Mbps.\n\nFiber to the office \xc8 una tecnologia per la trasmissione dati per la connessione a Internet, in grado di offrire velocit\xe0 di download fino a 1.000 Mbps e velocit\xe0 di upload fino a 200 Mbps.]" time="0.273"><properties><property name="score" value="0.011146954" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Diaper dermatitis in babies can be frustrating and difficult to manage. It is a condition that often occurs on babies with sensitive skin, and it is characterized by red, itchy rashes that can cause the baby to scratch. These rashes are the result of contact dermatitis, which can also be caused by substances such as chemicals, topical creams and other soaps. The irritation can be extremely bothersome to the baby, and the rash itself can be uncomfortable. In some cases, however, a rash may not be the result of diaper dermatitis. If the diaper rash does not respond to treatment or does not go away, it could be a sign that your baby has a more serious condition.\n\nDiaper dermatitis is an irritating and painful rash that can occur on the skin of a baby's diaper area. This condition can occur at any age and is characterized by red, itchy rashes that often become raw and develop a crusting appearance. Treatment typically involves the application of a topical cream, with limited success. Often, the rash does not respond to the cream or appears again the next time the baby wears a diaper. When this occurs, the diaper dermatitis is typically caused by a product in the baby's diet, such as a food or a topical cream.\n\nIf you have tried all kinds of different creams, but are still dealing with a diaper rash, it is possible that the rash is not caused by a diaper. Instead, it could be caused by a food allergy or an allergy to a topical cream. Both of these allergies can present as an irritating rash on the baby's diaper area. You can find out if the rash is caused by a food by eliminating the baby's diet one food item at a time and watching to see if the rash disappears. It is important to note that if the baby is lactose intolerant, the rash may clear up when you stop giving the baby any milk products, even if the allergy is not caused by a food.]" time="0.325"><properties><property name="score" value="0.021798775" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nnew file mode 100644\n\nindex 0000000..8a9b6e4\n\n--- /dev/null\n\n+++ b/ diff --git a/block/block.c b/block/block.cnew file mode 100644index 0000000..8a9b6e4--- /dev/null+++ b/ block/block.c @@ -0,0 +1,269 @@ +/* + * Copyright (C) 2006 ARM Limited + * Copyright (C) 2010 Freescale Semiconductor, Inc. + * + * See file CREDITS for list of people who contributed to this + * project. + * + * This program is free software; you can redistribute it and/or + * modify it under the terms of the GNU General Public License as + * published by the Free Software Foundation; either version 2 of + * the License or (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program; if not, write to the Free Software + * Foundation, Inc., 59 Temple Place, Suite 330, Boston, + * MA 02111-1307 USA + * + */ + +#include <common.h> +#include <net.h> +#include <nvram.h> +#include <fw_def.h> +#include <hw_base.h> +#include <linux_compat.h> +#include <console.h> +#include <delay.h> +#include <string.h> +#include <version.h> +#include <cmdline.h> +#include <dram.h> +#include <bootinfo.h> +#include <nvram_common.h> +#include <leds.h> +#include <pci.h> +#include <io.h> +#include <u-boot.h> +#include <usb.h> +#include <sysdep.h> +#include <cpu.h> +#include <pm.h> +#include <spi.h> +#include <mmc.h> +#include <serial.h> +#include <wdt.h> +#include <fec.h> +#include <mmc_block.h> +#include <plat_common.h> +#include <version_info.h> + +#include <board.h> + +struct boot_mode { + uint32_t active; + uint32_t size; +}; + + +uint16_t arm11mpcore_read_dr(void *opaque, target_phys_addr_t offset) +{ + return (FEC_DR_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_mdr(void *opaque, target_phys_addr_t offset) +{ + return (FEC_MDR_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_irqstat(void *opaque, target_phys_addr_t offset) +{ + return (FEC_IRQSTAT_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_irqstat_all(void *opaque, target_phys_addr_t offset) +{ + return (FEC_IRQSTAT_ALL_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_cccr(void *opaque, target_phys_addr_t offset) +{ + return (FEC_CCCR_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_pci_cfg_cmd(void *opaque, target_phys_addr_t offset) +{ + return (FEC_PCI_CFG_CMD_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_gic_cache_config(void *opaque, target_phys_addr_t offset) +{ + return (FEC_GIC_CACHE_CONFIG_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_gic_cache_config_0(void *opaque, target_phys_addr_t offset) +{ + return (FEC_GIC_CACHE_CONFIG_0_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_gic_cache_config_1(void *opaque, target_phys_addr_t offset) +{ + return (FEC_GIC_CACHE_CONFIG_1_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_gic_cache_config_2(void *opaque, target_phys_addr_t offset) +{ + return (FEC_GIC_CACHE_CONFIG_2_MASK_READ(offset)); +} + +uint16_t arm11mpcore_read_gic_cache_config_3(void *opaque, target_phys]" time="0.306"><properties><property name="score" value="0.0023752218" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Tad Boyle\n\nW.R. "Tad" Boyle (born November 19, 1961) is an American college basketball coach and the current head coach for the University of Colorado Buffaloes men's basketball team.\n\nBoyle played college basketball at the University of Montana and, while playing for the Grizzlies, became the school's all-time leading scorer with 2,355 points. He was also a two-time all-Big Sky selection, a member of the 1985 Big Sky championship team, and the Big Sky MVP as a senior.\n\nBoyle began his coaching career as an assistant at his alma mater. He then became an assistant at Washington State in 1989 before becoming an assistant at Oregon in 1991.\n\nHe became head coach at Montana in 1996 and compiled a 130\u2013123 record, with an Elite Eight appearance in 1999.\n\nIn 2002, he became the head coach at Northern Colorado and compiled a 55\u201348 record, with a WAC tournament championship in 2005.\n\nBoyle was then named the head coach at Eastern Washington in 2006 and compiled a 57\u201348 record, with a trip to the NIT in 2007.\n\nIn 2010, he became the head coach at Long Beach State. In 2012, Boyle became the head coach at Colorado. In 2016, Boyle signed a contract extension with the Buffaloes.\n\nBoyle is the son of former NBA player Bob Boyle and the brother of former Indiana Pacers coach Brian Boyle.\n\n]" time="0.308"><properties><property name="score" value="0.9115451" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.9115451 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.9115451
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[San Fernando Street Circuit\n\nThe San Fernando Street Circuit (Spanish: "Circuito de la Calle San Fernando") is a street circuit in the Puerto Rican capital city of San Juan. The 1.8\xa0km (1.1 mile) long circuit runs through the city's Condado and Miramar districts, beginning at Ashford Avenue, crossing the length of Ashford Avenue, going along the beach in front of the Sheraton Hotel, and ending at the Conrad San Juan Condado Plaza Hotel. The track is made up of city streets and is laid out in a clockwise direction.\n\nIn 1986, with the purpose of developing a Formula One event in the Americas, the Tourism Development Fund (FDF) carried out the studies and groundwork to design a track similar to those used in Indianapolis, Monaco and Adelaide.\n\nA track was laid out in downtown San Juan, covering the length of Ashford Avenue, Paseo de la Princesa and Calle San Francisco. It crossed Avenida La Playa and the entrance of the Sheraton Hotel, continuing towards the Conrad San Juan Condado Plaza Hotel. After two years, this would become the first Formula One circuit in the Caribbean. The event, organized by the FDF, was held in the month of October. It was only the second race of the season, held in Latin America, and the third race of the season in the Americas. The first race was held in Brazil and the second race in Mexico.\n\nThe first race was held on October 9, 1988 and was won by Brazilian driver Ayrton Senna. The event was not particularly successful, and it was not held again. The last race in San Juan took place in 1989.\n\n]" time="0.324"><properties><property name="score" value="0.06951474" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Cambridge Common\n\nCambridge Common is a public park in Cambridge, Massachusetts. It is located between Massachusetts Avenue and Garden Street, and Brattle Street and JFK Street. The park is home to many monuments and statues including the George Washington Monument and the Daniel Chester French statues of Paul Revere and Robert Gould Shaw.\n\nThe Common was designated a U.S. National Historic Landmark in 1965. It is part of the Boston National Historical Park.\n\nAccording to the City of Cambridge, the Common "evokes the birth of American Democracy." The Common was used by the first settlers of Boston as a grazing pasture for cattle and livestock, but became a Town Common after the Town of Cambridge was created in 1630. The City of Cambridge states that, "The Common was used for military drilling and mustering during the 17th and 18th centuries, and the militia members were occasionally quartered on the Common." It was used as a camp by the British before the American Revolutionary War began in 1775.\n\nA detailed history of the Cambridge Common can be found at the Cambridge Common Historical Society.\n\nA map of the Revolutionary War Battle of Cambridge shows the disposition of the troops and how they moved to various positions. The common was used as a camp ground during the Siege of Boston and as a muster ground in 1775, as well as for training and drilling. The British had guns placed on it, and during the battle it was used by both sides.\n\nGeorge Washington's first headquarters were near the Common at the John Vassall House, which stood in what is now Harvard Yard. He moved his headquarters to less exposed quarters across the Charles River in October 1775.\n\nThe Common is also home to a memorial honoring General Abner Doubleday, who is erroneously credited with inventing baseball. The memorial is a statue of Doubleday in front of the Doubleday Field gate to the common. It is one of two such statues, the other being in Cooperstown, New York. Doubleday was in fact a lifelong baseball fan who may have been involved in developing the game while a cadet at West Point, but he did not actually invent the game.\n\nThe main area of the Common is a flat, grassy field interspersed with trees, with a small, man-made lake in the center. Along its borders are brick sidewalks. Two 18-hole disc golf courses were installed in 1981, and two more in 1988. The latter two are technically on the Cambridge Common Golf Course, an adjacent parcel of land in Belmont that was purchased by the city in the 1980s, where the former driving range was converted into a grass field surrounded by trees, and where two 18-hole courses were built. The National Park Service states that "The Common, as well as the eighteenth century Bow and Arrow and original disc golf courses are accessible and used for passive recreation from dawn to dusk, daily."\n\nThe Common is the site of several statues and memorials, most prominently the Civil War Memorial Grove, which features the Civil War Memorial and a monument to General George S. Patton, Sr. who was from Cambridge and a former U.S. Congressman, and a statue of George Washington.\n\nThere is also a memorial to Ephraim Gerrish, one of the first to die in the American Revolutionary War. There is a monument to local soldiers who have fallen in the Iraq War. The stone monument is in the shape of a star, and the name of the fallen is inscribed on the star's points.\n\nA statue of Civil War general Robert Gould Shaw, sculpted by Daniel Chester French and Augustus St. Gaudens, stands on the Common as part of the Shaw Memorial. The memorial was originally located on nearby Boston Common but was moved to the Cambridge Common in 1904 to allow access by more people, and is one of the first monuments to an African American. The second statue, depicting Dr. Samuel Gridley Howe with a young student, is located in the nearby Simches Corner section of the Boston Public Garden, a short walk from the main Common. Howe is best known as the co-founder of the Perkins School for the Blind, and the statue is a popular destination for school field trips.\n\nThe "Civil War Memorial" on the Common was completed in 1872. It was designed by Henry Howard, architect of the famed Memorial Hall in Worcester, Massachusetts. The memorial was partially paid for by George Washington Gould, a local resident who made his fortune in California gold fields. The granite obelisk is tall and is the second largest granite monument in the United States, surpassed only by the Washington Monument in Washington, D.C. Its inscription reads "Erected in Memory of the Soldiers from Cambridge Who Fought For the Union in the War of 1861-1865."\n\nThere is a small plaque next to the monument listing the names of the men from Cambridge who fought in the war. The bronze statue of a Civil War infantryman located next to the monument was designed by Augustus Lukeman and cast in 1874.\n\nIn 2004, the monument was restored and renovated by a group of local volunteers. The restoration included sandblasting the obelisk, repairing the granite, and repainting the soldier. A new monument, which also listed the names of soldiers from Cambridge who died in the Vietnam War, was added to the memorial. The Civil War Memorial, along with the Paul Revere Memorial, is one of the first two structures in Massachusetts to be listed on the National Register of Historic Places.\n\nThe central water feature in the park is the "Polar Bear Plunge," a fountain that is operational from April through October, which was built in 1967. This is located in front of the the main library. There is also a fountain that is off in a small gazebo to the west.\n\nThe "Col. George Armistead Monument" was dedicated on the Cambridge Common on September 17, 1872. It was donated by the Grand Army of the Republic. The Monument commemorates Col. Armistead who was wounded at the Battle of Gettysburg, July 3, 1863. He was carried from the field and taken to Cambridge. After his recovery he returned to duty in 1864. His death occurred in 1895. His remains are buried in the family cemetery in Maryland.\n\nThe "Civil War Memorial" is located in the center of the Common, and is surrounded by the Civil War Battle]" time="0.651"><properties><property name="score" value="0.18437923" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Former Longmeadow Mayor Daniel R. Rossetti has endorsed State Sen. Eric Lesser for Congress, Lesser's campaign announced Tuesday.\n\nRossetti, who served as mayor for nine years until leaving the position in 2015, endorsed Lesser because of the senator's commitment to community service, campaign officials said in a press release.\n\n"When I needed the right person to get the right results, I called on Eric," Rossetti said in the release. "Whether he was helping me sell my house, help my daughter find a home to buy or get my elderly parents\u2019 apartment up to code, Eric was always there, he was always available and he was always getting results. As a small business owner, a community leader and a father, I knew I could count on Eric. Now that he's running for Congress, I know that others can too."\n\nLesser also has the endorsement of former Boston Mayor Tom Menino.\n\nLesser, a Democrat from Longmeadow, is running for the 4th Congressional District seat, which is currently held by Rep. Richard E. Neal, D-Springfield. Neal is one of the wealthiest members of Congress, according to Roll Call.\n\nRep. Joe Kennedy, D-Brookline, has announced his intention to run for the U.S. Senate seat now held by Sen. Elizabeth Warren, D-Massachusetts. Warren has not said whether she intends to run for re-election or for another position.\n\nLesser announced his candidacy in April. He is running for office to represent the 4th Congressional District and "ensure that our economic future is rooted in Longmeadow, Springfield and beyond," he said.\n\nIn 2014, Lesser served as field director for U.S. Sen. Ed Markey, D-Massachusetts, when Markey won a special election to the Senate. Lesser also worked for Markey from 2009 to 2011.\n\nMassachusetts' 4th Congressional District includes all or parts of Boston, Brookline, Cambridge, Chelsea, Everett, Framingham, Lowell, Lynn, Malden, Medford, Melrose, Milton, Natick, Newton, Reading, Revere, Somerville, Stoneham, Waltham, Watertown, Wellesley, Winchester, Woburn and Worcester.]" time="0.457"><properties><property name="score" value="0.011797147" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01179715 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01179715
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Here we go again.\n\nA couple of weeks ago, I wrote a piece about my fear of the upcoming NFL season. My argument was essentially that the Super Bowl has been set up for a possible matchup between two of the greatest quarterbacks of all time in Peyton Manning and Tom Brady, and since neither of those guys will be participating in the playoffs, the Super Bowl will lose much of its luster.\n\nThe post was titled, \u201cWhy the NFL is a failure this season,\u201d and it was the first post I ever wrote for this site. Now, I\u2019m back again, and this time, I\u2019m not trying to be negative at all.\n\nNot in the least.\n\nI am simply using the same outline as before to explain how I think the NFL has gotten it right this season, from start to finish. It\u2019s simply that there are some unique circumstances surrounding the upcoming season that make it much better than usual.\n\nHere\u2019s the original post, if you missed it.\n\nHere\u2019s my new one.\n\nHow the NFL Is Doing It Right\n\n\u201cWhat is right is always on the side of the minority, and the minority is always stronger than the majority.\u201d \u2014 Oscar Wilde\n\nThe NFL, as an organization, has made some questionable decisions this season. A prime example of this is the handling of the Bountygate scandal, where the Saints organization was accused of offering cash incentives for vicious hits. The NFL should have punished the organization much more harshly, but they ended up settling for an ill-advised one-year suspension of head coach Sean Payton, a six-game suspension for Saints\u2019 defensive coordinator Gregg Williams, and the loss of second-round draft picks in 2013 and 2014. This punishment was, in my opinion, much too light for such a heinous act, but it seems as though the league is finally cracking down on violent, illegal play.\n\nI\u2019m sure you\u2019ve heard the term \u201cDeflategate\u201d going around lately. As I\u2019m sure you know, this is a slang term for the controversy surrounding the pressure in the footballs used during the AFC Championship game between the Patriots and Colts. The NFL is now investigating this issue to determine whether or not the Patriots tampered with the footballs, or if they were simply deflated by other means. If they did indeed tamper with the balls, it\u2019s possible that the Patriots could be stripped of the win, and lose draft picks as well.\n\nThese are just two examples of the NFL doing something wrong this season, but they are both minor, compared to all the things they have done right. For instance, this is the first season since 1970 that has featured a team that had gone undefeated for the season. The league has never had a repeat champion since the NFL-AFL merger in 1970, and this season, that has already been changed. The Broncos have won the Super Bowl, so they have now become the first team to ever repeat as champs.\n\nAnother reason why the NFL has done it right this season is that it has followed the trend of unpredictability. For instance, there is a common misconception that the AFC is a better conference than the NFC, and that it\u2019s easier to win games in the AFC than in the NFC. However, this season, this was not the case. The NFC was the conference with the most wins, and of the five teams with the best records, three of them were NFC teams. It\u2019s safe to say that the NFC was the better conference this season.\n\nIt seems as though the NFL has followed the trend of unpredictability, not only by having a weaker conference beat a stronger conference (see the Broncos vs. the Panthers), but also by allowing lesser teams to rise to the top. The best example of this is the Kansas City Chiefs. As I am sure you know, the Chiefs are the only team in NFL history to start a season 9-0, and then finish it 1-5. They ended up with the worst record in the AFC West, and they didn\u2019t even win a single divisional game. This unpredictability is also evidenced by the fact that the Patriots were not one of the teams to make it to the playoffs.\n\nAnother reason why the NFL has done it right this season is the overall unpredictability of the playoffs. When looking at this season\u2019s playoffs, there are many different storylines, and each of them is interesting to look at. The three wild card teams in the NFC all have very good quarterbacks. The two divisional games have three great quarterbacks. The three conference championship games have one of the greatest quarterbacks ever, Peyton Manning, and two of the greatest quarterbacks ever, Tom Brady and Aaron Rodgers.\n\nWhile the Super Bowl is more predictable, there are still plenty of storylines in that game as well. Peyton Manning has been the story of the season. He is on track to become the most prolific quarterback in NFL history, and it would be great for him to get his second Super Bowl title. The last time he won a Super Bowl, the NFL was not as popular as it is now, and it would be a good way to end his career. The other storyline is the attempt by Seattle to get back to the Super Bowl. As I wrote earlier, the Super Bowl will be more interesting this season if the Seahawks and Broncos are playing in it, because both teams have very good quarterbacks.\n\nHow could you not be excited about a game that will have three of the top ten quarterbacks in the NFL, and possibly the greatest quarterback of all time?\n\nIn addition to these storylines, there are plenty of other things that make the NFL\u2019s current situation look better. The most obvious one is that Peyton Manning\u2019s career is at an end. It\u2019s]" time="0.624"><properties><property name="score" value="0.09846776000000002" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.09846776 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.09846776
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Blythe Massage & Skincare is a full service spa specializing in luxury massage and skincare.\n\nWe are located in the beautiful The Hill shopping district of Greenville. The spa is housed in an upscale, historic office building in the heart of downtown Greenville. This is an incredible opportunity for anyone interested in working in a beautiful facility in an upscale, professional environment. We offer competitive compensation and commission opportunities.\n\nJob Description\n\nWe are seeking an upbeat, dependable, self-starter to join our team. We\u2019re looking for someone who has a natural, charismatic personality and can excel in an independent work environment.\n\nPrimary responsibilities include booking appointments, making new client calls, selling our product line, marketing and public relations, maintaining a clean and organized spa, and building clientele.\n\nEssential Skills & Experience\n\nOutgoing, charismatic personality and customer service experience.\n\nPassion for skincare and spa industry.\n\nExcellent time management and organization skills.\n\nOrganized and clean.\n\nStrong attention to detail.\n\nGreat phone etiquette and interpersonal skills.\n\nGood selling skills.\n\nThe ability to work with the public and build clientele.\n\nWilling to learn and be a team player.\n\nAble to lift 25 lbs.\n\nAble to stand for long periods of time.\n\nKnowledge of some common massage techniques and terminology is a plus.\n\nMust have a driver\u2019s license.\n\nSalary and Benefits\n\nSalary is based on experience and is competitive.\n\nHourly compensation with commission opportunities.\n\nFree product with commission opportunity.\n\nBlythe provides a competitive salary and benefits package, including:\n\nFull medical benefits, including health, dental, and vision insurance.\n\nHealthy work environment with free snacks and beverages.\n\nFun team environment.\n\nPaid holidays and vacation.\n\nContact\n\nInterested applicants should submit a resume and cover letter to:\n\nMelanie Reisdorph, HR Manager\n\n(864) 298-4792\n\nmelanie@blythemassage.com\n\nBlythe Massage & Skincare\n\n16 South Main Street\n\nGreenville, SC 29601]" time="0.332"><properties><property name="score" value="0.0024235577" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00242356 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00242356
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Gregory Porter's vocal delivery is transcendent: we love it when he sings, and we especially love it when he sings old songs, songs that, for whatever reason, have gone undiscovered or unsung for decades. Porter's latest album, Take Me to the Alley, opens with a moody version of "Tears in Heaven," the Eric Clapton ballad that went to No. 1 in the U.K. in the wake of the guitarist's son's tragic death. In the studio, Porter reworks the tune with the help of Branford Marsalis. But even without the celebrated saxophonist, Porter pulls off the challenging ballad with incredible ease, and the results are, like so much of his music, brilliant.\n\nPorter's grasp of standards is no surprise. Born in California, the jazzman is the product of a mixed marriage \u2014 his father is African-American and his mother is a Chinese immigrant from Hong Kong. As a boy, Porter learned to love jazz by listening to his father's records of saxophonist Grover Washington Jr. and trumpeter Donald Byrd. He began his singing career with gospel music, however, and it wasn't until the singer's late 20s that he began to study jazz.\n\nAfter an apprenticeship in local San Francisco clubs, Porter moved to the East Coast, where he became the star of the jazz festival circuit. He released his debut album, Water, in 2012. That record, too, was front-loaded with several covers, including Bill Withers' "Ain't No Sunshine." The song won him a Grammy for best Jazz Vocal Album.\n\nPorter's latest release, Take Me to the Alley, follows in the same footsteps. The album is named for a Harlem club where the performer was discovered by a fellow club-goer. Like the standard version of "Tears in Heaven," the record's first track, "Don't Lose Your Steam," is the kind of song that Porter can and does make his own. But Take Me to the Alley is also notable for its inclusion of original material. "I'm Nobody" is the title track, and it's a heartbreaking song of resignation: "I'm nobody / Nobody but me." "Elias" tells the story of the biblical prophet in a way that's simultaneously soothing and haunting.\n\nIt's not all jazz on the new record. Porter delivers two great pop tracks, singing with restraint and sophistication on covers of Bob Marley's "Is This Love" and Roy Ayers' "Everybody Loves the Sunshine." But those songs don't necessarily fit into the album's theme, which is built around Porter's exploration of his own spiritual experience.\n\nPorter doesn't sing of God or the devil, but rather of a longing for peace, which he finds, again and again, in the power of singing. And it's that ability, more than anything else, that makes him so transcendent.\n\n]" time="0.378"><properties><property name="score" value="0.012938364" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01293836 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01293836
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[By May, she had taken to her bed and called in the house doctor, who after a physical examination said that her temperature and pulse were dangerously high.\n\nAnother doctor, Dr. Buchman, was called in. He was a specialist, and he discovered that her temperature was one hundred and four. He gave her quinine and ammonia, and she seemed to be better. But a few days later she was worse again, and her stomach had become swollen and she felt weak.\n\n\u201cWe must send for the doctor,\u201d her husband said. \u201cHe\u2019s the best doctor in the district.\u201d\n\nThe \u201cdoctor\u201d came. He was a man of sixty-five, named Doctor Stokes. He was tall and thin and had a beard that was like a white cloud. He asked the sick woman questions, and he heard her heart beating like a hammer, and he felt her pulse.\n\n\u201cShe\u2019s got the fever bad,\u201d he said. \u201cIt\u2019s very bad, indeed. We must send for the priest.\u201d\n\nBut Mr. Kinnaird had read his Bible and had seen a missionary die.\n\n\u201cNo,\u201d he said. \u201cWe won\u2019t do that. I think she\u2019ll be better.\u201d\n\nDoctor Stokes went away, and Nurse Salter sat by the bed all]" time="0.298"><properties><property name="score" value="0.033204403" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0332044 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0332044
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[We\u2019re almost at the end of the year and that means it\u2019s time to look back at the shows that aired in 2016. In today\u2019s analysis, I\u2019m going to look at the best first episodes of the season. Before we begin, I want to note that these rankings are based on the first episode only. It does not take into account the series as a whole. Let\u2019s get started!\n\n10. Kiznaiver\n\nKiznaiver has a great premise: what happens when you are forced to share pain? The series opens with a car crash scene that looks like it\u2019s going to be the whole episode, but quickly evolves into a brutal game of betrayal and pain. It\u2019s emotionally exhausting and does a great job of laying the groundwork for what is to come.\n\n9. Joker Game\n\nThe most forgettable show on this list. The opening scene, involving a rescue operation in Germany, is visually stunning, but it\u2019s not really what the rest of the series is about. Instead, the main characters are slowly introduced and while that\u2019s exciting, it doesn\u2019t really have much payoff. I would have liked more mission stuff, but I have a feeling the show is going to go the route of a slow burn. The opening, however, is brilliant.\n\n8. Boku dake ga Inai Machi\n\nRemember that movie Sliding Doors? It\u2019s basically the same thing except it\u2019s a dude and the scenes take place in a city. Anyway, it\u2019s very well executed and interesting. The show also throws in some time travel stuff for good measure, but not in a way that feels obnoxious or overused.\n\n7. Shouwa Genroku Rakugo Shinjuu\n\nThe opening scene for this one is a conversation between two inmates at a prison in 1950s Japan. It\u2019s incredibly effective and the best part is that it\u2019s not even the focus of the episode. Instead, it\u2019s used as a way to introduce the main character, Yotarou. The rest of the episode is about his time in prison and how it affected him. It\u2019s a great story and leads perfectly into the rest of the show.\n\n6. Drifters\n\nThis is the perfect example of an anime with a good first episode. It doesn\u2019t waste your time with long-winded introductions, instead giving you just enough backstory to understand the series. Plus, it\u2019s just so stylish and well animated. I can\u2019t wait to see where this show goes from here.\n\n5. Re:Zero\n\nI think what I love about this episode is that it tells the audience that they can enjoy this series even if they don\u2019t remember the LN. It wastes no time in introducing the main character, Subaru, and his situation. He wakes up on the side of the road and gets involved in the first of many wacky shenanigans. It\u2019s not until the end of the episode that you realize he\u2019s somehow ended up in a video game world and that the story will likely go in a very different direction than you would have expected. The best thing about Re:Zero is that it takes the \u201csave the cat\u201d trope and turns it on its head, which is very refreshing.\n\n4. Bakuon!!\n\nThere\u2019s nothing particularly special about the opening episode, other than it does a good job of introducing the characters and their bikes. The real meat of the show is in the second episode, which involves the first real story arc. It\u2019s when the show really takes off and becomes funny and memorable.\n\n3. Orange\n\nWhat I love about this show is that it doesn\u2019t waste any time getting to the heart of the story. It begins with the main character, Naho, hearing a letter from herself ten years in the future. She relays the message to the people around her and as the story progresses, it becomes clear what the message means. It\u2019s also about her realizing that she has fallen in love with a boy and then learning to live with that. That is what the show is really about. It\u2019s sweet and perfect and it only takes one episode.\n\n2. Flying Witch\n\nThis is a simple show about a witch who moves in with her cousin and starts to live a normal life. The best part is that there\u2019s no drama involved, it\u2019s just about a girl learning how to be normal. I think that\u2019s why this series works. It\u2019s just a slice of life show about a girl, so there\u2019s no expectation that anything is going to happen. This is a show that you can watch while doing your homework or eating a bowl of ramen and that\u2019s why it\u2019s at number two on this list.\n\n1. Mayoiga\n\nWhat makes this the best first episode is that it absolutely destroyed my expectations. I was expecting a dull, low budget horror story and what I got was an incredible story with high stakes and brilliant cinematography. It also introduced a large number of characters, yet somehow made them all feel important and necessary. This is an amazing episode that set up a potentially great series and that\u2019s why it\u2019s the best of the season.\n\nAnd that\u2019s it for this list! What shows did I miss? Feel free to let me know in the comments below.]" time="0.326"><properties><property name="score" value="0.428459165" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Bath, Maine\n\nI live in an old industrial town, and the air can get pretty polluted. When I was a kid, my family would drive down to our house on the shore, and within a half-hour, my chest would start to feel tight. As a scientist, I was surprised to find that my personal experience matched the research: The impact of air pollution on your health is immediate.\n\nThe worst effects of air pollution are known as \u201csocioeconomic depravation,\u201d and include asthma, allergies, heart disease, stroke, and Alzheimer\u2019s. The worst air pollution is caused by emissions of ozone and nitrogen oxide from the burning of fossil fuels and biomass, along with particulates from dust, dirt, soot, and smoke.\n\nAbout 5.5 million people die every year from air pollution exposure, but the relationship between emissions and disease is often overlooked. We have a major health crisis here.\n\nRecently, our federal government pulled out of the Paris climate agreement, which limits the average global temperature rise to 2 degrees Celsius.\n\nBut even if all countries met that goal, it still would not be enough. We need to limit the global average temperature rise to 1.5 degrees Celsius. Otherwise, we\u2019re looking at what\u2019s called a \u201cclimate departure\u201d\u2014a change so severe that it will create a whole new climate system.\n\nI\u2019m a professor of atmospheric chemistry at the University of Southern Maine. I\u2019m also an activist\u2014I\u2019ve been arrested three times for civil disobedience at the White House, to protest the proposed Keystone XL pipeline.\n\nAnd I\u2019m doing my best to put a personal face on climate change. The problem is that]" time="0.383"><properties><property name="score" value="0.005608683" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00560868 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00560868
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[D'abord une demande, ne me demandez pas o\xf9 sont les 2nd/3rd poste, vous l'avez sans doute compris, ils sont hors de ma port\xe9e. Mais si on me demande ce que je pense du boulet, de son pr\xe9sident, de son entra\xeeneur et de son banc, je n'ai pas de mal \xe0 r\xe9pondre!Donc il n'y a pas d'obligation d'ouvrir des 2nd et 3rd poste. Mais sachez que je ne fais pas parti de ceux qui seraient rest\xe9 \xe0 l'ext\xe9rieur en se disant que le manque de place n'\xe9tait pas un bonne chose pour l'\xe9quipe. Il faut juste \xeatre un minimum compr\xe9hensif vis \xe0 vis des joueurs qui en profitent et \xe9viter de leur hurler dessus.Apr\xe8s concernant les matches, c'est vrai que le syst\xe8me de calcul des points est in\xe9quitable (c'est bien plus facile de gagner 5-1 que 5-4). Mais je pense qu'il y a moyen d'am\xe9liorer le syst\xe8me, que ce soit en fonction des r\xe9gions o\xf9 les \xe9quipes jouent ou d'autres param\xe8tres (ex: tenir compte du nombre de joueurs en face ou de la valeur de leurs joueurs).Sinon dans les d\xe9tails:Durant toute la phase pr\xe9c\xe9dente, on entend plus les joueurs de deuxi\xe8me poste et troisi\xe8me poste que ceux de la premi\xe8re, alors qu'il y a bien plus d'informations \xe0 avoir dessus (cf poste 1).Apr\xe8s il ne faut pas n\xe9gliger la petite taille du forum. Certains joueurs sont peut-\xeatre rest\xe9s pour le travail de l'equipe mais auraient \xe9t\xe9 d\xe9\xe7us de ne pas jouer. D'o\xf9 le fait qu'ils se sont retir\xe9s. Je suis toujours d'avis que deuxi\xe8me poste et troisi\xe8me poste ne sont pas obligatoires.Mais je vais essayer d'\xeatre constructif:Je pense que tout le monde va \xeatre d'accord pour dire qu'il y a encore trop de fautes d'orthographe et de grammaire. Je trouve que pour cela, il faudrait un comit\xe9 de r\xe9daction qui v\xe9rifie les phrases avant que l'on passe les r\xe8gles. On pourrait alors se concentrer sur les autres points:On pourrait aussi augmenter la taille du forum pour qu'il y ait plus de messages sur les 1ers et 3\xe8me postes, et comme les messages qui sont post\xe9s sont valid\xe9s, il n'y aurait aucun risque que des fautes d'orthographe ou de grammaire s'y glissent.J'ai encore une suggestion:En plus du calcul de points \xe0 la fin du match, on pourrait mettre une valeur (indicatif) des joueurs qu'on poss\xe8de. Ainsi, si on poss\xe8de 5 joueurs valant 50 de valeur, on aime 5 points de plus que si on en poss\xe8de 5 vaut 40. Je pense que cela am\xe9liorerait le syst\xe8me de calcul des points.]" time="0.293"><properties><property name="score" value="0.021872915" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[You may already know this, but I think it bears repeating. The pursuit of happiness is not found in fleeting pleasures. It is not found in materialism. It is not found in security. The pursuit of happiness is found in relationship.\n\nTo gain and to keep a foothold in happiness is to engage in the highest and most significant pursuits possible. It is to become the kind of person that no matter what comes, you are happy. It is to choose your pursuits wisely, and to change them as your heart dictates.\n\nLet me give you an example. Some of you know that I grew up in a faith-based Christian household. I am very grateful for my parents, but they did not have the happiest of marriages. My dad loved my mom, but he had a very hard time respecting her. He loved us children, but he had a hard time honoring us. As I grew up, it took me a long time to realize how much pain my parents\u2019 decisions caused each other and my brother and me. As I became an adult, I found that what I wanted most from a marriage was the ability to choose to pursue my wife\u2019s happiness. Not just by taking her out for fancy dinners and vacations, but by being intentional in my actions toward her, even on the days that are less exciting. To be intentional about spending time with her, even when my career was more important. To listen to her even when it is inconvenient or when it will hurt my feelings. To put her needs first, even when I disagree with her, and to encourage her and celebrate her for who she is.\n\nRelationship takes effort. Relationship takes intentionality. Relationship takes humility and grace. That is why I decided that it was more important to me than a successful career or any other accomplishment. That is why I want my marriage to be the highest pursuit of my life.\n\nIf you want to know the source of true happiness, then choose your pursuits wisely. You can be an excellent Christian, a great husband, a perfect parent, an excellent leader, a talented businessperson, or any of a number of pursuits that make the world better. But unless you are pursuing your wife, and maybe your kids, with all of your heart, then you are not going to find true happiness.\n\nToday is the first day of a new year. It is a day for new beginnings. What do you want to change in your life to make it more like the life of Christ? How can you make the highest pursuit of your life the happiness of your wife and kids?\n\nFor me, this is the highest pursuit I can make. I hope you will decide to make a pursuit of your wife too.]" time="0.326"><properties><property name="score" value="0.85617775" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Victor Shenderovich's novel "Democracy" is a total satirization of the Russia of the 1990s. And it is based on a true story, when, under Gorbachev, the Bolsheviks have started a process of decomposition and part of the Soviet nomenklatura has not yet become a big oligarch. However, many of them, including the plot character of the novel - Vladimir Alexandrovich Krasnoyarsky - have not lost the hope for political career. It is just their methods and actions are becoming more and more cynical and mean. But the former youth activist Krasnoyarsky, who has now grown into a gray and stuttering man with a respectable family, "learned to speak like the wolves and think like the wolves", so he still has some chances to return to the "central and powerful offices."\n\nHowever, the main character of the novel does not hesitate to agree on a treacherous political alliance with the former Secretary of the Regional Committee of the Komsomol Ivan Komarov and his girlfriend - Larissa Naryshkina - in order to regain his political positions and carry out his personal goals. However, a new step, "a step up the top", as it is called in the novel, is fraught with unexpected consequences and it threatens not only to end the life of the protagonist, but also to cast a shadow on the fate of the entire country...]" time="0.294"><properties><property name="score" value="0.36007622" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Source\n\nOnly one out of ten lawyers in Europe\u2019s biggest economies have reached their retirement age. The average age at which European lawyers leave the profession is 60. The problem of the age distribution of lawyers in Europe is particularly serious in Spain (only one out of five lawyers will reach retirement age), but is also a concern in France (35%), Germany (39%), Italy (42%) and the UK (45%). On the other hand, Belgium (59%), Austria (61%), Luxembourg (62%), the Netherlands (63%), Finland (64%) and Ireland (68%) are the countries where lawyers retire later.\n\nIn the past decade the situation in Europe has deteriorated as the number of lawyers over 50 has increased by more than two thirds. This situation has been described as a \u201ccliff edge\u201d, referring to the lack of trained successors.\n\nSome European jurisdictions are more flexible in allowing the retention of lawyers who reach retirement age. For instance, Ireland allows the practice of law even after 80 years of age. But these exceptions have not resolved the situation. On the contrary, as the number of lawyers in Europe decreases, their average age is also growing, leaving Europe with an even larger challenge in the future.\n\nAn ageing population is not the only problem that Europe\u2019s legal profession is facing. Younger lawyers who remain in the profession after completing their training, show a high rate of inactivity (one out of four young lawyers in Europe). One of the reasons for this is that in many countries there is a lack of opportunities to practise law.\n\nTherefore, the profession needs to address these problems by improving the work-life balance and offering better opportunities for young lawyers. Otherwise, the profession will continue to experience a demographic crisis.\n\nFor further information see: http://www.blr.europa.eu/blr-vlt/database-data/lawyer-age-average-retirement-europe-european-law-family/3_entry-page/6_entry-page-tab/88_entry-page-slider/]" time="0.292"><properties><property name="score" value="0.005407244" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00540724 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00540724
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[It's one thing to be considered the best in the league in the NFL, but to have that prestige considered the best of all-time is a different beast.\n\nThat's the spot NFL Network analyst and Hall of Fame running back Marshall Faulk found himself in on Thursday.\n\nAccording to NFL.com, Faulk has been named the Greatest Show on Turf's all-time team after the Rams -- who boasted Faulk and other stars -- put together one of the best offenses in the history of the league.\n\nThe honor came at the expense of former Rams quarterback Kurt Warner, who is now a studio analyst for the network. Faulk was taken over Warner as a rusher and receiver by almost 500 yards, but also tallied almost 400 more points.\n\nSo while Warner may not have necessarily be considered better than Faulk, he certainly belongs in the discussion as one of the greatest players of his time.\n\nFaulk did lead the league in rushing touchdowns in 2000 with 24, which helped him win the rushing crown that year. But Warner also did that in 1999, and only was held off the top of the rushing charts by Faulk by six yards.\n\nFaulk and Warner have a solid history with each other and they were part of the greatest offense in NFL history when the Rams won Super Bowl XXXIV in 2000.\n\nSo while Faulk may not have been the greatest quarterback in history, he certainly deserves his place as one of the greatest players. And the greatest player of the Greatest Show on Turf has been decided.]" time="0.280"><properties><property name="score" value="0.10671871" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Plan B skriker ikke at jeg \xf8nsker ham vekk, jeg vil ikke noe annet enn at han fortsetter \xe5 v\xe6re venn. Det er ikke han som jeg krangler med for tiden, men noen andre. Jeg har en venn, ikke plan B, som jeg har kranglet med p\xe5 et eller annet vis i nesten et \xe5r n\xe5. Men han har faktisk aldri sagt noe negativt til meg, og han er p\xe5 ingen m\xe5te egoistisk. Jeg f\xe5r liksom ikke til \xe5 holde meg tilbake, men blir for sterkere og sterkere. S\xe5 lenge jeg ikke er jaloux eller skaper problemer, er det helt greit. Kanskje han er han bare glad i \xe5 konflikte?\n\nVidere er det det at han faktisk skulle v\xe6re egoistisk, og \xf8nsker jeg heller at han sier det rett ut, og ikke sier det med hundrevis av innskudd som er s\xe5 personlige at de kunne v\xe6rt skrevet i et privat brev. Det f\xf8les faktisk som om det blir konkurranse i alle forhold, hvor jeg vil at det skal v\xe6re lett, og det er ikke ettersom han ogs\xe5 skal passe p\xe5 og gi meg denne kj\xe6rligheten, gi meg alle de positive tingene. Jeg er ogs\xe5 egoistisk, og kj\xe6rligheten g\xe5r utover min egen person, da jeg \xf8nsker \xe5 bruke all min tid p\xe5 han. Men s\xe5 blir jeg ogs\xe5 bedre og bedre p\xe5 at han er glad i meg, og har lyst til \xe5 v\xe6re sammen med meg.\n\nEtter mange krangler, sp\xf8r han hva jeg vil han skal gj\xf8re for \xe5 komme oss forbi dette, jeg svarer aldri at jeg \xf8nsker at han skal g\xe5 vekk. Jeg vet ikke hvorfor han tror at jeg sier at jeg vil at han skal g\xe5 vekk.\n\nKanskje jeg virkelig burde si ifra hvor ulykkelig jeg er n\xe5. Jeg krangler mye med venninner ogs\xe5, og i det siste har jeg g\xe5tt bort fra flere enn vanlig.\n\nKanskje det er det samme med ham, men jeg vil ikke at han skal g\xe5.\n\nDet gj\xf8r meg s\xe5 lei meg.\n\n]" time="0.289"><properties><property name="score" value="0.0016697419" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Demo Essay\n\nby user submitted August 7, 2013\n\nSubmitted by user: Rachel Becker (California)\n\nStress. Stress is defined as anything that causes worry, pressure, or\n\nuneasiness. I tend to find myself in situations that are very stressful. I'm a very\n\nstressed out person in general and that only worsens when I'm under a lot of\n\nstress. During my High School days, I found myself very stressed. From having to\n\ndo homework to having tests, I was never at peace with myself. In order to deal\n\nwith stress, I usually looked for the simplest solution. I would normally turn to\n\nfast food or video games to relieve myself of stress. Sometimes, I would just\n\nkeep myself very busy by making a list of things that I needed to do or that I\n\nhad to finish that day. Sometimes, I would even make a list of all the things that\n\nI had to do the next day. Some people might find this annoying but this would help\n\nme avoid stressing. For example, I might forget to do an assignment and so I would\n\nmake a note in my agenda to make sure to do it. Another solution I had was to\n\nwrite a list of what I needed to do. If I thought of something I needed to do, I\n\nwould write it down so I would remember it. I still do this even now. Whenever I\n\nfeel that I'm too stressed, I tend to just get a lot of work done. I would even take\n\non extra assignments. Although this method may not be for everyone, it helps me\n\ndeal with stress. I would have to say that one of the most stressful times in my\n\nlife was freshman year. I was homeschooled until that year and I was very\n\nunfamiliar with the style of learning that I had to do in High School. I went from\n\na single subject school to a large High School where I had to take many classes\n\nand study for tests. When I first arrived, I wasn't ready for what I was about to\n\nexperience. I found myself being very stressed out and even though I would have\n\nhelp from my mom, it was]" time="0.315"><properties><property name="score" value="0.24176742" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Click to print (Opens in new window)\n\nClick to share on WhatsApp (Opens in new window)\n\nClick to share on Google+ (Opens in new window)\n\nClick to share on Twitter (Opens in new window)\n\nClick to share on Facebook (Opens in new window)\n\nJOHOR BAHRU: Police have arrested four individuals, including two foreigners, suspected of their involvement in a cross-border drug trafficking ring.\n\nJohor Bahru Selatan police chief ACP Mohd Jaffril Mohd Kassim said three Malaysians and a Myanmar national were detained in a raid at a condominium in Kampung Raja, Johor Bahru, at around 3pm on Friday.\n\n\u201cThe suspects were believed to be responsible for the supply of drugs in the state. We seized 120g of methamphetamine, also known as \u2018Ice\u2019, a 9mm pistol and drug paraphernalia from their hideout,\u201d he told reporters during a press conference here yesterday.\n\nMohd Jaffril said the operation was conducted by the police Narcotics Criminal Investigation Department with the assistance of the police Dog Squad.\n\nThe case is being investigated under Section 39B of the Dangerous Drugs Act 1952 and Section 11 (1) (a) of the Firearms Act 1960.\n\nOn Friday, two foreigners and two Malaysians were detained in a raid at a pub in Taman Nusa Bestari, Johor Bahru, at around 3.30pm.\n\nIn the raid, the police seized 180g of heroin, two handphones, and drug paraphernalia.\n\nA 25-year-old Myanmar national and a 29-year-old Bangladeshi national were arrested.\n\nThe case is being investigated under Section 39B of the Dangerous Drugs Act 1952.]" time="0.294"><properties><property name="score" value="0.045572948" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04557295 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04557295
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Long-serving county councillor and former mayor, Tony Murphy, has announced his intention to retire from the new political grouping in Fingal County Council, Fine Gael.\n\nA political activist from the days of Fine Gael's foundation in Ireland, Tony Murphy will now retire from local politics to give full attention to his role as Chairman of the Irish Human Rights and Equality Commission, where he was appointed by Government in January 2016.\n\n\u201cI have had a very rewarding career in the Fine Gael party since I was 15 years old,\u201d Tony Murphy said.\n\n\u201cOver the last 50 years I have been a member of numerous branches, elections, council, party structures, convention, parliamentary and senatorial panels, including the chairman of the party, chairman of the central council and parliamentary committee, secretary of the Dublin South-Central constituency, chairman of the Dublin South-Central branch, chairman of the County Executive Council, and chairman of the Dublin Central and Dublin South constituencies.\n\n\u201cI have had the privilege of serving as a councillor for over 30 years.\n\n\u201cI have had the privilege of serving as Mayor of Fingal for seven consecutive years, and during my tenure I also served as a member of the Dublin Convention Bureau, the regional development agency.\n\n\u201cI have had the privilege of serving as the vice-chairman of the Fingal Board of Health and the Fingal Environment Committee.\n\n\u201cI have had the privilege of serving as chairman of Fingal County Council, including a period as vice-chairman of the National Roads Authority, during which time I became a fellow of the Chartered Institute of Transport.\n\n\u201cI have had the privilege of being a member of the Northern Ireland Assembly.\n\n\u201cI have had the privilege of being a member of the Seanad, including a period as the leader of the Seanad group of senators.\n\n\u201cI have had the privilege of being appointed by the Government as chairman of the Irish Human Rights and Equality Commission.\n\n\u201cI have had the privilege of serving in the diplomatic service of my country in Asia.\n\n\u201cI have had the privilege of being re-elected as a member of Fingal County Council.\n\n\u201cMy work at the Irish Human Rights and Equality Commission is now very full, and I will now retire from politics to allow full attention to be given to that.\u201d\n\nA native of Co. Kerry, Tony Murphy has been a lifelong member of Fine Gael and has devoted his career to the party.\n\n\u201cI have had a very enjoyable and interesting career,\u201d he said.\n\n\u201cI have always been one who is deeply interested in people and in politics.\n\n\u201cI was born and brought up in Co. Kerry, but I left there to work abroad in the diplomatic service of my country.\n\n\u201cIt was only after my career in the diplomatic service that I settled in Fingal.\n\n\u201cThe decision to make Fingal my permanent home was an excellent decision, and it has given me a lot of joy.\n\n\u201cMy family and I are very grateful for the support we have received in this area.\n\n\u201cThe most important person in my life has been my wife, Mary, whom I met at UCD over 50 years ago.\n\n\u201cWe have a strong bond with Fingal, having lived here for over 30 years, and we have two lovely children who live here.\n\n\u201cI have had the pleasure of working with people from all walks of life, and have made friends for life, and I am grateful for that.\u201d]" time="0.311"><properties><property name="score" value="0.22688437" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.22688437 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.22688437
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[We put this question to Dr Mike Kirby, senior lecturer in ecology at the University of Sheffield. He says:\n\nWhat you have described is probably just a cloud of vapour from the burnt paper. The sheet could be damp and therefore partially burnt. The candle-like effect is from the heat of the fire creating a hot updraught from the top of the paper.\n\nFire normally causes something to expand. When paper is burnt, for example, the effect is to tear it along the grain and to char the fibres. The paper may have had a chemical on it that causes the reverse to happen - shrinkage.\n\nThe shrinking is quite slow and not noticeable to you but the final result is a very sharp rip across the page. The opposite of this happens when you take a photo of someone - the flash produces heat, and this causes the water molecules in the skin to evaporate, which causes the skin to shrink.\n\nNext question: how do giant squid stay buoyant?\n\nGot a question for our experts? Email it to ask@lifeandphysics.com and we'll do our best to answer.]" time="0.327"><properties><property name="score" value="1.1559582" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Deel dit artikel:\n\n\n\n\n\n\n\n\n\n\n\n\n\nDeel dit artikel:\n\n\n\n\n\n\n\n\n\n\n\nAsielzoekers krijgen afschaffing werkstraf dankzij Kamervragen Van Bommel. \xa9 ANP\n\nAsielzoekers die in Nederland willen blijven, krijgen hun werkstraf niet meer opgelegd. Daarvoor pleiten Tweede Kamerleden Henk Nijboer (PvdA) en Harry van Bommel (SP) in een interpellatie.\n\nDe beide partijen onderschrijven de voordelen van werkstraffen, maar vragen zich af of dat ook geldt voor mensen zonder verblijfsvergunning. "Als uitgangspunt is een werkstraf namelijk bedoeld voor Nederlanders die in de samenleving zijn ge\xefntegreerd, waardoor zij deze taakstraf kunnen vervullen", schrijven de Kamerleden.\n\n\n\nAsielzoekers hebben een verblijfsvergunning op grond van de Vreemdelingenwet niet, maar vanwege de mensenrechtelijke verplichtingen van het Nederlandse rechtssysteem krijgen zij hier ook vrijwel nooit een negatieve beslissing over.\n\n\n\n'Teruggekeerde vreemdeling'\n\nZoals bijvoorbeeld in de recente Afriforum-zaak. De advocaat van zijn cli\xebnt tegenstrijdt dat het gaat om een 'teruggekeerde vreemdeling', omdat de rechtbank had geoordeeld dat het onduidelijk was wat hij wel of niet precies in zijn land van herkomst had gedaan, meldt AD. De rechtbank oordeelde dat een uitgeprocedeerde Afghaan niet 'terug' kan worden gezet. Hij is volgens het Europese Verdrag voor de Rechten van de]" time="0.489"><properties><property name="score" value="0.050681476" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Refine Result\n\nCriteria Application Rigidity (10) For Use With (5)\n\nSupplier BACHARACH (6)\n\nSigma-Aldrich (2) Suppliers found in search results Sort by: Number of results A-Z supplier name Z-A supplier name Close BACHARACH (6)\n\nSigma-Aldrich (2) BACHARACH (6)\n\nSigma-Aldrich (2) BACHARACH (6)\n\nSigma-Aldrich (2) Search Within Results\n\n\n\nPrint\u2026 Home > (Dimethylamino)phenol-(C3H4N) \u2265 98.5% (HPLC) You Searched for: "5-dimethylaminophenol-(c3h4n)" SearchPresentationType-VERTICAL SearchResultCount:"1" List View Grid View Easy View (new) Sort by: Best Match Product Name (A-Z) Product Name (Z-A) Supplier Name (A-Z) Price (Low - High) Price (High - Low) Top Sellers Rate These Search Results\n\nCatalog Number: (P3984-1G) 5-dimethylaminophenol-(C3H4N) \u2265 98.5% (HPLC) Retrieving Each Supplier: BACHARACH Description: 1G SDS Certificates View Product Page This product is no longer available. Alternatives may be available by searching with the VWR Catalog Number listed above. If you need further assistance, please call VWR Customer Service at 1-800-932-5000. Call for Price is still displayed and you need assistance, please call us at 1-800-932-5000. Stock for this item is limited, but may be available in a warehouse close to you. Please make sure that you are logged in to the site so that available stock can be displayed. If theis still displayed and you need assistance, please call us at 1-800-932-5000. is still displayed and you need assistance, please call us at 1-800-932-5000. Stock for this item is limited, but may be available in a warehouse close to you. Please make sure that you are logged in to the site so that available stock can be displayed. If theis still displayed and you need assistance, please call us at 1-800-932-5000. In order to process your orders without delay, we request that you provide the required business documentation to purchase this product. To order chemicals, medical devices, or other restricted products please provide identification that includes your business name and shipping address via email CMD_NA@vwr.com or fax 484.881.5997 referencing your VWR account number . Acceptable forms of identification are: State issued document with your organization's Federal Tax ID Number\n\nState issued document with your organization's Resale Tax ID Number\n\nCity or County issued Business License\n\nState Department of Health Services License\n\nAny other ID issued by the State that includes the business name and address * Please note if your account is within the State of California two of these pieces of identification will be required.\n\nVWR will not lift restrictions for residential shipping addresses. ???store.product.restricted??? This product has been blocked by your organization. The original product is no longer available. The replacement shown is available. This product is no longer available. Alternatives may be available by searching with the VWR Catalog Number listed above. If you need further assistance, please call VWR Customer Service at 1-800-932-5000. 1 - 1 of 1]" time="0.371"><properties><property name="score" value="0.17719759" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.17719759 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.17719759
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u201cI think it\u2019s a great policy.\u201d\n\nWhen it comes to police brutality, one could be forgiven for thinking there\u2019s nothing good to say. After all, there are far too many examples of police officers going over the line and injuring or even killing someone for a minor, or no, infraction.\n\nStill, there are good police officers, and there are police officers who are very supportive of black people, and the president of the National Association of Black Law Enforcement Officers is the latter.\n\nDuring a panel discussion on police brutality, Terrence Cunningham, president of the National Association of Black Law Enforcement Officers, said it was a \u201cgreat policy\u201d to disarm a police officer if he or she acts violently towards a civilian.\n\nIn this case, Cunningham was talking about a police officer who assaulted a 15-year-old teenager. The officer slammed the teenager\u2019s head into a locker while searching him.\n\nBut Cunningham said something needs to be done.\n\n\u201cWhen you talk about policy, it\u2019s really great to have a policy that requires a certain amount of force and then requires a certain amount of reporting,\u201d he said, according to The Washington Post.\n\n\u201cBut I think we need to go beyond that. I think we need to say that if an officer uses a certain amount of force and it is unreasonable, then I think that\u2019s an offense that could lead to termination,\u201d Cunningham continued.\n\nHowever, he also said something has to be done on the part of the community as well.\n\n\u201cI think we need to address it from a policy perspective and also from a community perspective,\u201d Cunningham said.\n\n\u201cYou have a lot of kids in the community that don\u2019t trust law enforcement,\u201d he said.\n\n\u201cWhen they don\u2019t trust law enforcement, they\u2019re not going to report crime. When they don\u2019t report crime, they don\u2019t get reported. That\u2019s a problem. We\u2019ve got to work together to make people feel comfortable in reporting crime.\u201d\n\nTelling a police officer he or she should be fired if he or she is violent against a civilian is definitely a very good policy to have. Still, the issue of trust is just as big a problem.\n\nIf black people don\u2019t trust the police, and if police officers think they can treat anyone as they see fit because they\u2019re not afraid of being reported, then we have a real problem.\n\nThis article was originally published on The Constitution.\n\nShare this: Facebook\n\nTwitter\n\nMore\n\nPinterest\n\nReddit\n\n\n\nEmail\n\n]" time="0.294"><properties><property name="score" value="0.023746012" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02374601 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02374601
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Call me naive, but I had hoped that the small press comics festival last month might signal the beginning of a long overdue positive change in the mainstream media\u2019s attitude towards and reporting on comics. To be perfectly frank, as a member of the comics media, I don\u2019t think we do ourselves any favours with some of the reporting we do. I have long been of the opinion that the way some writers cover comics makes a complete mockery of the art form and is little better than a tabloid.\n\nSo, I thought that perhaps the passing of such an important date in the comics calendar would have been a time when mainstream media would have perhaps recognised the importance of reporting on the events in a balanced and serious manner. And indeed, for the most part, I think the mainstream media did report on it in an impartial manner.\n\nHowever, there were a couple of articles that I read in national newspapers which both fell into the same trap of making ridiculous sweeping generalisations and condescending tones, almost as if the writers were laughing at the very notion of people being interested in comics. The fact that it was in the London papers was even more strange, given that the actual festival was held in Glasgow.\n\nI\u2019ve had enough of the ridiculous condescension and I don\u2019t think I\u2019m alone. So I wanted to remind all of you what the reportage should have looked like,]" time="0.278"><properties><property name="score" value="0.08095525" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08095525 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08095525
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Never before have there been so many ways to get around town. Your old friend, the car, still plays an important part, but these days you can also get there on a bike, by bus, via carpool or through an online service. The new wave of bike-sharing services, using dockless bikes, are particularly useful for getting around short distances.\n\nGetting around is an integral part of life in Munich. But this means that the city\u2019s public transport network needs to keep up with increasing demand and changing travel patterns. The introduction of intelligent transport systems, such as automatic vehicle and passenger counting and the integration of new vehicle concepts, has opened up a whole new range of options.\n\nThe automatic vehicle counting system helps to better inform passengers and to optimise service deployment. And as the focus turns to sustainable mobility, the use of electric vehicles has taken off in the city. One example is the KITT-shuttle: the KISS project is working on a prototype of this e-shuttle for low-floor public transport.]" time="0.283"><properties><property name="score" value="0.17919977" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.17919977 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.17919977
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Government Fined $55,000 For Killing Eagle In Conn.\n\nState environmental officials were fined $55,000 Wednesday for accidentally killing an eagle in 2007 when they were using an air gun to cull Canada geese at a state park.\n\nDepartment of Environmental Protection spokesman Dennis Schain said Wednesday that the state was fined $5,000 by the U.S. Fish and Wildlife Service for the death of the bald eagle. The Service also fined DEP $50,000 for causing the bird\u2019s death without a permit.\n\nThe bird was killed when a single pellet struck the eagle\u2019s beak. The bird was in its nest at High Rocks State Park in Milford at the time of the incident. Schain said it\u2019s unclear what the pellet was fired at, but that the department\u2019s policy is to use the air gun to deter geese from landing in areas around parks, not to shoot them.\n\nIn March, the state paid a $1,500 fine after it was found that state Department of Transportation workers had caused the death of an eagle that struck a roadside rock pile.\n\n(Associated Press)\n\nIn other news:\n\nThieves Steal 4,000 Year Old Flint Axe Head from UK Museum\n\nA UK museum is appealing for help in tracking down a 4,000 year old axe head believed to have been stolen by thieves.\n\nThe rare Neolithic tool, which was taken from the Wiltshire Museum in Devizes, had been loaned by a collector and is of national significance.\n\nThe silver inlayed flint axe head has a hole at the top which would have fitted on to a wooden shaft. It was taken from the museum on January 5.\n\nThe museum has reported the theft to Wiltshire Police and is seeking the public\u2019s help in recovering the axe head.\n\nChief Executive at the museum, Frank Crummy, said the axe was a rare and significant artefact and is desperate to recover it as soon as possible.\n\nHe said, \u201cThe museum would like to hear from anyone who may have seen the axe head or knows of its whereabouts.\n\n\u201cWe would urge the person who has stolen it to return it to us at the Wiltshire Museum in Devizes.\u201d\n\nMr Crummy added that if the axe head was returned, the museum would \u201cbe happy to put it back on public display\u201d.\n\nHe added, \u201cWe would also like to thank the Wiltshire Police for their help and advice in this matter.\u201d\n\nA full-size replica of the axe head will be on display at the museum as part of the new Wiltshire prehistoric gallery.\n\nThe axe head has a silver inlayed head and a long hole at the top. The handle has since been replaced but the museum would like to hear from anyone who may have seen the axe or knows of its whereabouts.\n\nThe Wiltshire Museum is in Devizes and is open daily from 10am to 4.30pm and admission is free.\n\n(BBC)\n\nIn other news:\n\nFrance: 2 Sea Turtles, 1 Freshwater Turtle Seized From Paris Market\n\nPolice in Paris have discovered two endangered sea turtles and a freshwater turtle during a search of a vendor\u2019s stand at the Porte de la Chapelle marketplace.\n\nAccording to police, the vendor said he purchased the animals in southern France, but did not know the exact source of the turtles.\n\nHe was carrying the animals in two plastic containers and was arrested on Sunday, January 15.\n\nThe vendor told police that he had purchased the turtles for approximately $120 each and hoped to sell them for $180.\n\n(Agence France Presse)]" time="0.334"><properties><property name="score" value="0.0012799477" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00127995 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00127995
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I loved it! It is more work than it looks, but it's soooo worth it!! This is one of my favorite fall crafts, and I do it year after year. (I've also used orange and pink!)\n\nThis is the perfect project for the kids in the house to help with! It's a great craft that they will think you spent a lot more time on than you actually did! You can make it as detailed or simple as you'd like.\n\nWhat You'll Need:\n\nJute Cord (you'll need enough to cover the entire base of the tree, and enough to weave through the sticks)\n\nCorn Starch (you'll need about 1/2 cup to cover your tree)\n\nAcrylic Paint (your choice of colors)\n\nPaint Brushes\n\nYarn\n\nNeedle\n\nHot Glue Gun\n\nWooden Twigs\n\nStart by cutting your jute cord into four-foot lengths. Once you have enough, you can tie them into bundles with a knot. (Tip: Make sure you cut it longer than you think you will need, because the size of the tree will shrink quite a bit once you put the cornstarch on it.)\n\nNext, you will need to cover the jute cord with cornstarch. Put the cornstarch in a bowl, and then dip the end of the jute cord into it. Then, use your paint brush to push the cornstarch down onto the jute cord. You may have to do this more than once, and you'll probably have to wait a few minutes for the cornstarch to dry in between coats.\n\nWhen your jute cord is covered in cornstarch, put it on a baking sheet and bake it in the oven for about 30 minutes at 150 degrees. This will dry the cornstarch and make it so you don't have to worry about water getting on your tree.\n\nOnce it is dry, you can start making your tree! Start by finding a tall jar or drinking glass. If you don't have one handy, a plastic soda bottle will do. When you have your tree trunk, tie a knot at the top and then start weaving the jute cord around it. Once it's the way you like it, tie another knot at the top to secure it in place.\n\nRepeat this process with your remaining sticks until you have as many trees as you'd like. When you're finished, attach your trees to the base of your tree using hot glue and yarn.\n\nOnce you have your tree complete, you can start decorating it. I added some fall leaves, and you could also use glitter, ornaments, etc.\n\nI'm seriously thinking about hanging my fall trees from the chandelier this year!]" time="0.345"><properties><property name="score" value="0.4208426" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Yogapedia explains Hip-Hop\n\nHip-hop is a genre of music that became popular in the late 1970s and is associated with the hip-hop culture that evolved from DJing, MCing and breakdancing. The term hip-hop was coined in the late 1970s by Bronx DJ Afrika Bambaataa, and a few years later by hip-hop journalist and rapper Fab Five Freddy.\n\nHip-hop involves four major components: DJing, MCing, graffiti and breakdancing. The term is also used as a catch-all phrase to describe other styles of music that may not fit any other genres.\n\nMany people who were hip-hop DJs began as b-boys or breakdancers. As the genre became more commercialized in the 1980s and 1990s, the breakdancers and graffiti artists were less able to make a living from their craft and moved on to other occupations. Many popular DJs from the late 1970s and early 1980s were, or became, also graffiti artists and b-boys, including Afrika Bambaataa, Grandmaster Flash and The Furious Five, Cold Crush Brothers, Tuff Crew, Roxanne Shante, Fab 5 Freddy, DJ Jazzy Jay, Cash Money, DJ Easy Lee, Kurtis Blow and Run-D.M.C.]" time="0.301"><properties><property name="score" value="0.8778199" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8778199 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8778199
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Fey on Fey: An Interview with Chicago\u2019s Swiftian Comedy Troupe \u201cLeaping Laughter\u201d\n\nFey on Fey: An Interview with Chicago\u2019s Swiftian Comedy Troupe \u201cLeaping Laughter\u201d\n\nOur very first story was a comedic one about some residents of a nursing home, \u201cThe Saga of the Teakettle of Doom,\u201d which was about the world\u2019s most long-suffering caretaker. And that was the second thing we ever wrote.\n\nWe were terrified of writing stories about the characters in our comic novels, because we were afraid that if we didn\u2019t get it exactly right, people would scream at us for messing up. And that\u2019s not what you want.\n\nWe were terrified of writing stories about the characters in our comic novels, because we were afraid that if we didn\u2019t get it exactly right, people would scream at us for messing up. And that\u2019s not what you want.\n\nSo the first thing we ever wrote that wasn\u2019t a comic novel, the first thing we ever wrote that was a real story, was a comedic story. And it was a great experience for us, because the best you can hope for in a comic novel is that people laugh out loud and get excited about it, and you can never really tell. So the idea of doing something that you could actually gauge, where people could get up and leave if they didn\u2019t like it, was a very valuable experience for us, and it turned out that people did like it.\n\nOur very first story was a comedic one about some residents of a nursing home, \u201cThe Saga of the Teakettle of Doom,\u201d which was about the world\u2019s most long-suffering caretaker. And that was the second thing we ever wrote.\n\nSo the idea of doing something that you could actually gauge, where people could get up and leave if they didn\u2019t like it, was a very valuable experience for us, and it turned out that people did like it.\n\nHow did you and your wife meet?\n\nSo the first thing we ever wrote that wasn\u2019t a comic novel, the first thing we ever wrote that was a real story, was a comedic story. And it was a great experience for us, because the best you can hope for in a comic novel is that people laugh out loud and get excited about it, and you can never really tell. So the idea of doing something that you could actually gauge, where people could get up and leave if they didn\u2019t like it, was a very valuable experience for us, and it turned out that people did like it.\n\nHow did you and your wife meet?\n\nWho is your favorite author and what is it that you love about them?\n\nWho is your favorite author and what is it that you love about them?\n\nWho is your favorite author and what is it that you love about them?\n\nWhat inspired you to write \u201cThe Kindness of Strangers?\u201d\n\nWhat inspired you to write \u201cThe Kindness of Strangers?\u201d\n\nThe idea of a modern day business mogul living in the castle of the Beast and then being confronted with the concept of all the terrible things that had happened there over the years \u2013 of him looking over a long dining table and seeing on one side all the characters from Beauty and the Beast who had died over the years. It was a very funny image for us.\n\nThe idea of a modern day business mogul living in the castle of the Beast and then being confronted with the concept of all the terrible things that had happened there over the years \u2013 of him looking over a long dining table and seeing on one side all the characters from Beauty and the Beast who had died over the years. It was a very funny image for us.\n\nIt was a funny image. It was like, \u201cWell, he\u2019s rich, he\u2019s got money, he\u2019s rich and he\u2019s a business mogul.\u201d And in that room he has a portrait of the Beast and the Beast is eating an entire goat, and he\u2019s pouring wine on his head, and that was the image that inspired the story.\n\nIt was a funny image. It was like, \u201cWell, he\u2019s rich, he\u2019s got money, he\u2019s rich and he\u2019s a business mogul.\u201d And in that room he has a portrait of the Beast and the Beast is eating an entire goat, and he\u2019s pouring wine on his head, and that was the image that inspired the story.\n\nOur son is one of the characters in the story. And so he was born in October, and we wrote the story in November. And there\u2019s a scene in the story where he has gone missing and his mother is screaming, \u201cWhere\u2019s my baby?\u201d And then he comes into the story as the thief, the kidnapper of the baby.\n\nOur son is one of the characters in the story. And so he was born in October, and we wrote the story in November. And there\u2019s a scene in the story where he has gone missing and his mother is screaming, \u201cWhere\u2019s my baby?\u201d And then he comes into the story as the thief, the kidnapper of the baby.\n\nAnd he was born in October, and we wrote the story in November. And there\u2019s a scene in the story where he has gone missing and his mother is screaming, \u201cWhere\u2019s my baby?\u201d And then he comes into the story as the thief, the kidnapper of the baby.\n\nIt was really cool. It was like, \u201cWow, we have a kid,\u201d which is terrifying. \u201cWhat are we going to do?\u201d And then we were like, \u201cWell, why don\u2019t we write a story about it?\u201d And it just kind of happened. It was one of those moments when you just thought, \u201cThis is a really good idea.\u201d\n\nIt was really cool. It was like, \u201cWow, we have a kid,\u201d which is terrifying. \u201cWhat are we going to do?\u201d And then we were like, \u201cWell, why don\u2019t we write a story about it?\u201d And it just kind of happened. It was one of those moments when you just thought, \u201cThis is a really good idea.\u201d\n\nHe\u2019s one of the characters in the story. And so he was born in October, and we wrote the story in November. And there\u2019s a scene in the story where he has gone missing and his mother is screaming, \u201cWhere\u2019s my baby?\u201d And then he comes into the story as the thief, the kidnapper of the baby.\n\nWe didn\u2019t think anything was ever going to happen, so we were just writing it for fun. And then one of our friends saw it and said, \u201cThis would make a good stage play.\u201d So we started taking it to festivals and festivals would say, \u201cThis is hilarious. This would make a great show.\u201d And we\u2019re like, \u201cOh, yeah, I guess that would make a great show.\u201d\n\nWe didn\u2019t think anything was ever going to happen, so we were just writing it for fun. And then one of our friends saw it and said, \u201cThis would make a good stage play.\u201d So we started taking it to festivals and festivals would say, \u201cThis is hilarious. This would make a great show.\u201d And we\u2019re like, \u201cOh, yeah, I guess that would make a great show.\u201d\n\nIt\u2019s been really fun to see people\u2019s reaction to it. When people come up to us and say, \u201cThat\u2019s my favorite story of yours,\u201d it\u2019s always really nice to hear. It\u2019s very rewarding.\n\nIt\u2019s been really fun to see people\u2019s reaction to it. When people come up to us and say, \u201cThat\u2019s my favorite story of yours,\u201d it\u2019]" time="0.649"><properties><property name="score" value="0.0115108019" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[4.8 Overall 544 Reviews View All By Rating 5 Star 71% 4 Star 26% 3 Star 2% 2 Star 0% 1 Star 0% By Category Overall 4.8 Value 4.7 Performance 3.7 Style 4.0 Comfort 4.2 Fuel Economy 4.6 Reliability 4.7\n\n2004 Toyota Corolla - Would recommend Ashley Raytown, Missouri Overall 5.0 Value 5.0 Performance 3.0 Style 3.0 Comfort 4.0 Fuel Economy 5.0 Reliability 5.0 2004 Toyota Corolla - Would recommend I love my Corolla. It is in perfect condition and has had no problems in the ten years that I have had it. I like the body style. It is different from other cars. I love the color. It is a light blue. I also love the size. It is not a big car, so it is easy to drive and park. It is perfect for anyone who is new to driving or who does not have a big family. I have three children, and we all fit comfortably. The trunk is a good size for groceries and other purchases. I like the acceleration. It is a fast car, but does not get terrible gas mileage. I have driven it for almost 120,000 miles and have not had a single mechanical issue. I have only had a few electrical problems, such as the windows not working right. I would not trade it for the world. I would... (more) I love my Corolla. It is in perfect condition and has had no problems in the ten years that I have had it. I like the body style. It is different from other cars. I love the color. It is a light blue. I also love the size. It is not a big car, so it is easy to drive and park. It is perfect for anyone who is new to driving or who does not have a big family. I have three children, and we all fit comfortably. The trunk is a good size for groceries and other purchases. I like the acceleration. It is a fast car, but does not get terrible gas mileage. I have driven it for almost 120,000 miles and have not had a single mechanical issue. I have only had a few electrical problems, such as the windows not working right. I would not trade it for the world. I would buy another car like this one in a second. Story When we bought the car, it was very shiny and new. I took my children to school every morning. My children thought that the car was the best thing ever. They had to show it to all of their friends. When we bought the car, it was very shiny and new. I took my children to school every morning. My children thought that the car was the best thing ever. They had to show it to all of their friends. Pros I love the speed, and the gas mileage is great. I love the size of the car. It is a perfect size for me. I also love that it is a Toyota. I have never had any major problems with it. I love the speed, and the gas mileage is great. I love the size of the car. It is a perfect size for me. I also love that it is a Toyota. I have never had any major problems with it. Cons I would like a little more room in the front seat. I would like a little more room in the front seat. 2005 Toyota Corolla - Trustworthy and affordable Jessica KCMO Overall 5.0 Value 5.0 Performance 4.0 Style 3.0 Comfort 4.0 Fuel Economy 5.0 Reliability 5.0 2005 Toyota Corolla - Trustworthy and affordable This car is one of the most dependable vehicles I've ever owned. It has held up wonderfully and has never left me stranded, and I've put many miles on it. It has lots of nice features, such as a sunroof, power windows and locks, great sound system, comfortable seats, and the perfect amount of room. This car is one of the most dependable vehicles I've ever owned. It has held up wonderfully and has never left me stranded, and I've put many miles on it. It has lots of nice features, such as a sunroof, power windows and locks, great sound system, comfortable seats, and the perfect amount of room. Story It has a sunroof which was great fun to use at night when driving with friends. It has a sunroof which was great fun to use at night when driving with friends. Pros One of my favorite features is the air conditioning. The air conditioner always works and keeps me very cool in the summer months, which can get very hot and humid where I live. Another thing I love is the built-in, hidden compartment under the armrest in the back seat, which holds extra items or anything else you want to store. Another nice feature is the power locks. The power locks make locking and unlocking your car very simple and easy, so you don't have to mess around with your keys. One of my favorite features is the air conditioning. The air conditioner always works and keeps me very cool in the summer months, which can get very hot and humid where I live. Another thing I love is the built-in, hidden compartment under the armrest in the back seat, which holds extra items or anything else you want to store. Another nice feature is the power locks. The power locks make locking and unlocking your car very simple and easy, so you don't have to mess around with your keys. Cons My only real con with this vehicle is the size. I find that it's a little small for my family and me. It is great for one or two people or children, but it would be difficult to fit in more than two small children. My only real con with this vehicle is the size. I find that it's a little small for my family and me. It is great for one or two people or children, but it would be difficult to fit in more than two small children. View All Reviews]" time="0.594"><properties><property name="score" value="0.0567536575" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Strawberry Cheesecake Ice Cream Bars (NO ice cream maker needed!)\n\nStrawberry Cheesecake Ice Cream Bars \u2013 a super easy, creamy, rich and delicious no churn ice cream bar recipe that requires absolutely NO ice cream maker! These little bars are absolutely amazing, and you will love the cool & creamy texture!\n\nFor today\u2019s recipe, I am sharing one of my favorite no churn ice cream bars that tastes just like strawberry cheesecake, but the best part is that there\u2019s no ice cream maker needed! This means that you will have an easy and quick summer dessert with only 5 simple ingredients (including cream cheese, sour cream, strawberry sauce and more). Plus, there are only 2 main ingredients that will help you make these scrumptious bars.\n\nAnd the best part? This homemade ice cream bars recipe is a must-make this summer, because the perfect cool dessert treat that you\u2019ll love to make over and over again this season!\n\nHow To Make Strawberry Cheesecake Ice Cream Bars\n\nMy recipe for Strawberry Cheesecake Ice Cream Bars is one of the easiest ice cream recipes you can make this summer, because you will only need a few ingredients to make the base.\n\nHow To Make No-Churn Ice Cream Bars\n\nIngredients in the ice cream bars\n\nFull-fat cream cheese\n\nSour cream\n\nWhipping cream\n\nSugar\n\nStrawberry sauce\n\nHow to make no-churn ice cream bars\n\nFirst, make sure that you thoroughly mix all of the ingredients together.\n\nLine a pan with plastic wrap.\n\nSpread the ice cream mixture into the pan and freeze.\n\nPeel off the ice cream from the pan.\n\nCut into bars.\n\nI like to eat these ice cream bars straight from the freezer because the texture is nice and firm. But you can serve them on a plate and they are great at room temperature too.\n\nMy favorite no-churn ice cream bar recipe\n\nThis strawberry cheesecake ice cream bar recipe is one of my favorites, because you can make a big batch of it and it will still be ready in 30 minutes.\n\nNo ice cream maker needed\n\nI always make this strawberry ice cream bars recipe in my Instant Pot, because I don\u2019t have an ice cream maker at home. But I\u2019m sure that you can make this recipe with an ice cream maker.\n\nWhy I like this recipe\n\nI really like this strawberry cheesecake ice cream bar recipe because it\u2019s delicious, easy and it doesn\u2019t require an ice cream maker. This means that you can make these no-churn ice cream bars whenever you need them, and it will only take you 30 minutes.\n\nThis ice cream bar recipe is perfect for summer, and they are even great for your kids.\n\nHow long can you keep strawberry ice cream bars in the freezer?\n\nOnce you have made the strawberry cheesecake ice cream bars, they can be kept in the freezer for a few weeks.\n\nTry my No-Churn Oreo Ice Cream Bars!\n\nDid you make this recipe? Leave a comment below, and share a picture on Instagram with the hashtag #mamiemealplanning \u2013 I would love to see your creations!\n\n5.0 from 2 reviews Strawberry Cheesecake Ice Cream Bars Print Prep time 10 mins Total time 10 mins Strawberry Cheesecake Ice Cream Bars (NO ice cream maker needed!) Recipe by: Mami Eats Recipe type: Dessert Cuisine: American Serves: 12-16 bars Ingredients 1 cup cream cheese\n\n1 cup sour cream\n\n\xbd cup whipping cream\n\n\xbd cup strawberry sauce\n\n1 cup sugar Instructions In a medium-sized bowl, combine cream cheese, sour cream, whipping cream, strawberry sauce and sugar until thoroughly]" time="0.285"><properties><property name="score" value="0.007982701" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0079827 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0079827
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Now and then a student will say to me, \u201cI\u2019m just not a numbers person.\u201d And I think, \u201cWhat does that mean?\u201d How can someone not be a numbers person?\n\nOne could say that an artist is not a numbers person, because the whole idea of putting together all the math for the math-phobic is too much to face. The mere thought of a formula involving the product of 2 variables is enough to scare some artists off.\n\nAnother person who may not be a numbers person is the person who prefers to deal with a different language than mathematical. I\u2019m not sure if I\u2019m one of these people, but if I were, I\u2019d be perfectly comfortable with a quantitative paradigm of programming. A programming paradigm is a way of thinking about a problem. Some paradigms are so different from the norm that the programmer is not using their usual way of thinking.\n\nThe paradigm I\u2019m trying to achieve with my students is one that values beauty over time-saving, and that celebrates failure as the first step in learning something new. This paradigm includes some math, but it also has an art component, and one that is not entirely unique. I\u2019m following in the footsteps of others who, as educators, have been far ahead of the learning curve on this one. And there is something else that makes this paradigm different, and that is that the paradigm is about the learner. My job is not to provide solutions to all of my students\u2019 problems, but to be there to help them develop the solutions for themselves.\n\nBut before this can happen, the learner needs to get past his or her self-doubt, and start to imagine that, just maybe, it\u2019s possible to make a difference in this world. The way to do that is by experimenting, failing, making mistakes, and moving on.]" time="0.320"><properties><property name="score" value="1.233242" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Wells Fargo employees were accused of creating millions of fake accounts in order to boost sales, but a recent discovery has the bank facing additional controversy.\n\nWells Fargo employees were accused of creating millions of fake accounts in order to boost sales, but a recent discovery has the bank facing additional controversy.\n\nThe new allegations were revealed in a federal class action lawsuit against the company that also claims the firm discriminated against minorities in its mortgage lending division, The New York Times reported. The new lawsuit was filed in the U.S. District Court in California and claims that Wells Fargo violated the Fair Housing Act by discriminating against minorities in its mortgage lending division.\n\nThe lawsuit cited instances where loan officers were told to refer to African-American and Hispanic borrowers by code names, such as \u201cmud people\u201d and \u201cghetto customers,\u201d to indicate which customers were to receive inferior service.\n\nWells Fargo spokeswoman, Mary Eshet, denied the allegations, and called them \u201can attempt to extract money from the company.\u201d\n\n"Wells Fargo disputes the claims and will contest this lawsuit vigorously,\u201d Eshet said in an email to the Times. \u201cThe allegations are an attempt to extract money from the company by litigious means. In fact, Wells Fargo has been a leader in helping minority customers and has reached millions of homeowners in underserved communities."\n\nThe Justice Department in February opened a criminal investigation into whether employees at the bank broke laws when they created false accounts. The investigation, led by the U.S. attorney in Sacramento, California, was initiated after the Times reported that employees had opened roughly two million accounts without the consent of customers. The lawsuit, which was first filed in January in state court, was amended in March to include the allegations that employees discriminated against minorities.\n\nAt the center of the federal criminal investigation are Carrie Tolstedt, the former head of Wells Fargo's community banking division, and other high-ranking executives. Employees were forced to meet internal sales quotas or face firing. Many said they were ordered to \u201cpry into customers\u2019 lives,\u201d to boost sales. When employees failed to meet their sales targets, they were threatened with termination.\n\nA group of workers also filed a lawsuit against the company in state court in Utah in February, claiming that they were fired or forced to resign for refusing to participate in the alleged illegal activity.\n\nWells Fargo has been under scrutiny since the Los Angeles Times first reported the illegal sales practices in September. The bank has since apologized for the conduct of its employees, and said the bank\u2019s top leadership was unaware of the misconduct. The bank reached a $185 million settlement with regulators in September, and fired about 5,300 employees, including Tolstedt.\n\nWells Fargo has since announced several policy changes to reform its sales practices and will create a board committee to oversee the changes. The committee will be led by Elizabeth Duke, a former member of the Federal Reserve, and Sherry Hunt, the bank\u2019s former chief financial officer.\n\nThe Justice Department did not comment on the new lawsuit, but spokeswoman Nicole Navas Oxman told the Times that the department takes discrimination allegations seriously.\n\n\u201cThe department takes fair lending allegations very seriously,\u201d she said.]" time="0.327"><properties><property name="score" value="0.0022387085" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00223871 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00223871
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I\n\ndon't get it.\n\n\n\n\n\nis everything these guys touch...\n\na new invention?\n\na revolutionary process?\n\non the cutting edge?\n\n\n\n\n\nWhen I first started using liquid eyeliners a few years ago I thought,\n\nthey look good...\n\nthey look like they'd be fun to play with.\n\n\n\n\n\nAnd,\n\ndang,\n\nthese pencils are kind of expensive...\n\n\n\n\n\nI think they may be well worth the money.\n\n\n\n\n\nHowever,\n\nthe lady who taught my eyeshadow class at Ulta did recommend the following liquid eyeliners:\n\n(she did not recommend them to me personally - just to class members in general)\n\n\n\n\n\n\n\n\n\nI've been using the NYX and Essence eyeliners.\n\nNYX for a while now.\n\nThis is a good one.\n\nEssence - the new one.\n\nThe applicator is much easier to work with.\n\nAnd this one is super black.\n\nI still can't get my line to look as good as it does on the Ulta lady -\n\nbut I'm practicing.\n\n\n\n\n\nHere's an in-your-face look:\n\n\n\n\n\nI'm also playing with a new look...\n\none with a slight wing.\n\nIt's easier to wear than it is to do,\n\nand it takes a long time to get it right.\n\nBut it's not rocket science.\n\nAnd it's fun.\n\nI guess I need to work on my penmanship.\n\n\n\n\n\nThanks for reading,\n\n\n\n\n\nDana]" time="0.286"><properties><property name="score" value="0.39398307" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.39398307 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.39398307
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[For in the great City into which I had just come the men pay no attention to women, but, seeing that beauty is free to all who care to pay for it, direct all their efforts towards keeping themselves as handsome as possible.\n\nSuch was his philosophy, and such was his practice. It must be admitted that the latter was consistent with the former, and that, whilst his follies were of the most extravagant character, he gave proof of a high degree of ability, and of a very decided will.\n\nBut it is not my intention to defend him, nor to excuse him. His life and his actions would, in themselves, furnish forth a romance, of which the life of the Marquis de Sade would furnish the dreary groundwork, and of which his own romance, entitled Justine, would furnish the dreary development.\n\nNo, no; I have no intention of presenting him to you in the light of a reformer, or of a philanthropist, or of a philosopher; he was a sensualist, a dastardly rascal, a debauchee, a liar, a cheat, a scoundrel.\n\nFor these and for other reasons, and also, perhaps, for the more foolish one that the Marquis de Sade has never been condemned, I have no intention of describing his life to you; I propose, rather, to deal with the thoughts which occupied his mind, with the rules which he laid down for himself, and with the singular and extraordinary notions which led to his strange mode of life, and which, perhaps, also, partly influenced his criminal and immoral conduct.\n\nMy task is a difficult one; I must be more exact than the attorney who defends, or than the advocate who prosecutes; and, whilst anxious to do justice to my subject, I must not overlook any of the circumstances of his life.\n\nMy subject is an interesting one; but it is very grave. It would be easy to make of it a mere romantic novel, and to do so without making it less interesting. I should require only a few touches of paint, and I should thus complete my task. But that would be to do an injustice to my subject, and to treat it lightly. This man has passed through the furnace of passions, and he has emerged from the fires more pure than refined gold.\n\nTo the world he has always seemed to be devoid of talent. He has been despised by the upper classes and avoided by the lower. He has been ridiculed on the stage, and he has excited hatred in the pit.\n\nHe has neither money, nor honor, nor rank, nor beauty, nor social position.\n\nHe has only one quality\u2014\xadone merit, one happiness, which is in a sense more than a mere individual happiness. He possesses the true originality, the true spirit of independence, and, if he cannot do good, he does, at least, no harm.\n\nHis is a generous]" time="0.297"><properties><property name="score" value="0.8854112" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8854112 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8854112
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Photo courtesy of Zuffa LLC\n\nIt wasn't long ago that Dana White was blaming Jon Jones' absence from the UFC for the decline in ratings for the UFC on Fox shows.\n\nWhile this still may be partially true, Jones' return to the Octagon could not have come at a better time for the UFC, who desperately need to keep interest alive in the light heavyweight division.\n\nMany will point to the success of the Ultimate Fighter as the reason behind the current boom in the UFC, but that isn't the entire story. In fact, the hype behind the TUF finale pales in comparison to that of the rematch between Jones and Alexander Gustafsson at UFC 165.\n\nAnd yet, what we saw at UFC 165 was not much of a fight. It was one of the most one-sided bouts we've seen in the UFC in quite some time. It was so one-sided that you may wonder how anyone in their right mind would even consider this a rematch.\n\nThe great thing about the sport of MMA is that there's always room for redemption. If you have a bad fight, you can always fight again. It's the fight game and you're going to get beat. The question is whether you come back stronger than before, or if you let your confidence be shaken and spiral down into the abyss.\n\nWith that said, here are the five things we've learned from the first fight between Jon Jones and Alexander Gustafsson.\n\n1. Jon Jones is the King of the Light Heavyweights\n\nIt was never really in doubt, but Jones' domination at UFC 165 reminded the MMA world that he is the number one light heavyweight in the world.\n\nGustafsson had Jones in trouble in the first round, but since then, the champ hasn't even broken a sweat. He did it with an efficient takedown game and a brutal top game.\n\nGustafsson is the one fighter that seems to be able to at least hang with Jones, but he didn't come anywhere close to taking the champ out. He couldn't take him down and he couldn't even score a takedown of his own.\n\nThe main question now is whether Jones can deal with Alexander Gustafsson's size. Gustafsson is the tallest fighter Jones has ever faced, and if he can handle that length and that reach, he could very well be unstoppable.\n\n2. Jones doesn't respect Gustafsson\n\nThe one thing you want to see from a champion is that he takes the guy he's fighting seriously. He has to, because the moment he takes his opponent for granted, the guy could end up shocking him.\n\nUnfortunately, that wasn't the case at UFC 165. The entire fight, Jones fought as if he was just doing enough to win. He didn't even bother to engage in a little trash talk. And his disrespectful attitude afterward was more of the same.\n\nI get that he's the champ and he's not going to go overboard and lose his cool, but he should at least act like his opponent is dangerous and is not just a stepping stone for him.\n\nIf Gustafsson is ever going to get a rematch, he has to prove that he's the real deal. It will take a dominant win over the next opponent and a display of humility on his part, but a win over Glover Teixeira could be just what he needs.\n\n3. Size matters\n\nWhen it was announced that Jones and Gustafsson would have their rematch, most MMA fans were excited because we all knew it would be another great fight.\n\nWhat many of us did not expect, however, was how the fight would end up going. Most people expected a lot of striking between the two and to see who could best one another with the fewest amount of mistakes.\n\nThat is not what we got. Jones took Gustafsson down time and time again, and it was clear that the Swede was no match for the size of the champ.\n\nAlthough it's hard to say what would have happened if Gustafsson had been able to keep the fight standing, it's still not a very comforting thought to know that Gustafsson was outmatched by Jones in the grappling department.\n\n4. Jon Jones has some improvements to make\n\nThe first fight between Jones and Gustafsson was absolutely incredible and a lot of people would say that Jones was the clear-cut winner.\n\nI am not one of those people. Yes, Jones controlled the fight, but he wasn't as dominant as we all thought. Gustafsson had Jones in trouble in the first round and that is not something we see often with Jones.\n\nGustafsson has an incredible reach advantage, but that doesn't necessarily mean he will be able to hit Jones with his punches. After all, Gustafsson could not land a single significant punch and his best punch of the fight was a glancing blow.\n\nIf Gustafsson can hit Jones with his jab, he may have a chance, but he has to catch him first and that's a problem because Jones is incredibly fast. If he can put Jones on his back, however, he will most likely get the decision.\n\nIf there's one thing Jones has to work on, it's his takedown defense. It's not that he doesn't work on it because he does, but he needs to focus more on it.\n\n5. There are a lot of different ways to beat Jones\n\nI'm sure that most fans are excited for the possible rematch between Jones and Gustafsson, but even if Jones loses to Glover Teixeira, there are still a lot of options left for challengers.\n\nSome would say that Phil Davis could be a good opponent, but the reason that fight doesn't excite me is because Jones would simply take Davis down and it would be a one-sided beatdown.\n\nThen, there's Alexander Gustafsson, who I already mentioned and who has a good chance of beating Jones if he can figure out how to land his punches.\n\nAlthough that's a long shot, there are a few other fighters who could potentially beat Jones in the future. Antonio Rogerio Nogueira and Mauricio Rua are on the list as well as Glover Teixeira.\n\nFor the first time in a long time, it feels like the light heavyweight division has new life.\n\nThanks for reading, you can follow me on Twitter @RileyLittle.\n\nStay tuned right here at MMA Sucka for more live streams as well as videos highlighting the top fighters, commentators, coaches, promoters and other names in MMA and combat sports. We also bring you great offers on the latest MMA products and merchandise. You can also subscribe to our youtube channel for regular updates and all the latest fight news. You can also check out our sister site, at TheFightBuzz.com for the latest from the world of MMA and other combat sports.]" time="0.613"><properties><property name="score" value="0.92127048" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.92127048 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.92127048
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Do you ever think about what you would say to a homeless veteran if you met one?\n\nThe post, written by the Navy's current senior enlisted leader, Master Chief Petty Officer of the Navy Mike Stevens, was originally posted on the official Navy blog on Jan. 21, and has been reposted on the official Facebook page since then.\n\nIn it, Stevens breaks down the percentage of homeless veterans from each branch of the military, and highlights some startling facts about homeless female veterans.\n\nAccording to the post, 31 percent of homeless veterans served in the Army, 18 percent in the Navy, 18 percent in the Air Force, 20 percent in the Marine Corps, and 1 percent in the Coast Guard.\n\nStevens also mentioned that females account for 10 percent of all homeless veterans.\n\n"To be a homeless woman of any age is an unthinkable state of existence. But to be a homeless woman in the United States of America, a country with abundant resources and vast public compassion, should be unconscionable," Stevens wrote.\n\nHe added that female homeless veterans face a higher level of traumatic issues and psychological disorders than males.\n\n"They have been raped, assaulted, subjected to abuse both physically and mentally," he wrote. "They have seen the worst that humankind can inflict on itself. And yet, they stand strong, their heads held high."\n\nStevens closed the post by saying: "As we focus our attention on homeless veterans, let's not forget the remarkable women who are part of this epidemic."]" time="0.262"><properties><property name="score" value="0.6347817" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6347817 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6347817
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This just in: Donald Trump is the subject of a feature length documentary being produced by no less than \u2013 wait for it \u2013 HBO. But before you go and boycott the premium cable network for giving a platform to someone who stands for everything it stands against, you may want to know the project in question is in fact a parody, albeit a very, very well-made one.\n\nCreated by filmmaker Alexandra Pelosi and titled \u201cMeet the Donors: Does Money Talk,\u201d the faux-documentary is meant to satirize the network\u2019s documentary \u201cMeet the Donors: Does Money Talk,\u201d which is currently airing. The spoof is part of a new season of programming that includes \u201cThe Breastfeeding Scene,\u201d which stars Anna Faris as a lactating nanny who hires a lawyer after her breasts decide to strike on her behalf; \u201cSex Scene,\u201d about a woman played by Julia Louis-Dreyfus who has sex with a pizza delivery man and then orders another pizza; and \u201cSugar Daddy: The Eddy Lewis Story,\u201d about a disabled teenager whose \u201cSugar Daddy\u201d is played by a real life sugar daddy played by Chaz Bono.\n\nAccording to HBO\u2019s official press release, \u201cThe film is built around the voices of the documentary\u2019s real-life subjects who comprise a who\u2019s who of real-life political heavyweights \u2013 from George Soros to Newt Gingrich, Ken Griffin to David Koch, and Sheldon Adelson to Sheldon Adelson.\u201d]" time="0.280"><properties><property name="score" value="0.0012023073" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00120231 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00120231
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[by Scott Selwood\n\nWith all the excitement of the season opener against the L.A. Chargers, it can be easy to forget about the rest of the AFC West. The division could be one of the most competitive in the NFL this season. The Chargers have been one of the more competitive teams for the past decade, the Chiefs and Raiders have shown that they have talent on their teams and the Broncos should still be one of the best teams in the league.\n\nBut with all that said, here are my predictions for the AFC West this season.\n\nDenver Broncos (11-5)\n\nThe Broncos are the defending Super Bowl Champions, so they have that going for them. They also return almost all of the players who made them a top offense and defense. Case Keenum is back and while he had a fantastic season last year, he is a streaky quarterback and can have some cold spells.\n\nThe Broncos have a tough schedule and some injuries can make this team vulnerable. But, it should be enough to get them to the playoffs and potentially another Super Bowl appearance.\n\nKansas City Chiefs (10-6)\n\nThe Chiefs are the team in the division with the most questions. After losing several defensive stars to free agency, the defense is going to have to improve. The offense is lead by an explosive group of skill position players, but the defense could still be a liability.\n\nThe Chiefs play a tough schedule this season, so the defense will have to show improvement. If the Chiefs have a down year, the Chargers will be there to take the division.\n\nOakland Raiders (9-7)\n\nThe Raiders had a huge turnaround last season after going from a team with little hope to a team with some momentum. They have an explosive offense and a good defense. However, they still have some of the same problems they\u2019ve had the past few years.\n\nThey still have issues protecting Derek Carr. Carr can make the big plays to score, but if the offensive line doesn\u2019t improve, the Raiders could see themselves under .500. The Raiders have the potential to be one of the best teams in the league, but I think they will have another so-so year.\n\nLos Angeles Chargers (8-8)\n\nThe Chargers will be good this year. The problem is, it won\u2019t be enough. While the Chargers have an improved offense and a good defense, they have some tough losses in the division. The Chargers also play a tough schedule, which will lead to some tough games.\n\nThe Chargers have the potential to make some noise this year, but they will have to take a few wins from the Chiefs and Raiders.\n\nShare this: Twitter\n\nFacebook\n\nGoogle\n\n]" time="0.365"><properties><property name="score" value="0.8655655" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Photo\n\nThe Christian Science Monitor is the country\u2019s leading source of independent, global news and insight. Its perceptive and experienced editors keep a sharp eye on world events and provide insightful analysis on issues of U.S. and international concern. In our Web Focus series, the Monitor\u2019s editors weigh in on timely topics with extended essays meant to take a broad look at the forces shaping our world.\n\nWhat\u2019s a \u201ccyber-9/11\u201d? A cyberattack on a nuclear facility or a major dam that could release enough water to drown a major American city? A digital assault on the nation\u2019s banking system or a threat to the electrical grid that could plunge millions of Americans into darkness? The recent warnings from Gen. Martin Dempsey, the chairman of the Joint Chiefs of Staff, and the National Security Agency director, Gen. Keith Alexander, suggest that such nightmare scenarios are indeed a possibility.\n\nBut if U.S. intelligence officials are to be believed, the greatest threat is an assault on the nation\u2019s financial institutions. After Dempsey warned Congress that the U.S. could \u201csee cyber incidents that have physical effects on our critical infrastructure,\u201d Alexander echoed his remarks by noting, \u201cA cyberattack that could have physical effects, that is the greatest fear.\u201d\n\nThe consensus is that a catastrophic cyberattack could wreak havoc on the U.S. economy. The reality, however, is far more complex and nuanced.\n\nDespite claims of major foreign-government backing for a digital assault on American banks, the truth is that such an operation is very unlikely. In recent years, foreign cyberintelligence agencies have tried to collect sensitive information about banks, including the names and Social Security numbers of their customers. A similar campaign targeting American credit-card companies in 2011 was likely perpetrated by the Syrian Electronic Army, a group of hackers supporting the regime of Syrian President Bashar al-Assad. This operation was relatively easy and inexpensive to conduct.\n\nThe reality is that America\u2019s banking system is highly resilient. Even after the catastrophic events of 2008, when hundreds of small and medium-sized banks failed, the country\u2019s largest institutions emerged from the wreckage of the subprime mortgage crisis in better shape than ever.\n\nThe system as a whole remains sound and is well capitalized. America\u2019s banks remain the best-run financial institutions in the world.\n\nAnother myth is that a digital assault on U.S. banks could cause financial panic. Such claims are hyperbolic. Bank customers in this country have ready access to digital accounts, and those who rely on more traditional methods, such as a teller, are quickly switching to digital channels as well.\n\nA cyberattack on America\u2019s banking system might undermine confidence in the safety of its networks, but there is little to indicate that customers would take their money out of banks in a large-scale panic. In 2011, when many U.S. banks suffered from a series of hacking attacks, there was no bank run. The attacks caused brief hiccups in the banking system but no lasting harm.\n\nThe threat that\u2019s garnering the most attention these days is an attack on the U.S. financial system from a foreign power. In 2010, the New York Times reported that China had hacked into the computers of the Federal Reserve Bank of New York, and the FBI arrested several suspects who were working at JPMorgan Chase and at least one other bank.\n\nIn response, the National Security Agency and the Department of Homeland Security launched an initiative to secure the American financial system from foreign-government attacks.\n\nThe odds of a major cyberattack from China or Russia are far less likely than most people believe. An American bank has little to gain from being penetrated by hackers. Both countries have thriving black markets in information that could be sold to interested parties, and the purchase price would be higher than the cost of a sophisticated cyberattack.\n\nThe most plausible threat is a \u201cdisruptive\u201d attack that, as Gen. Alexander put it, \u201cisn\u2019t to crash the system but to interrupt it in some way, to make people aware that the system isn\u2019t safe.\u201d Such an operation could easily come from a criminal hacker or foreign-government operatives. An attack that exposed confidential information would shake consumer confidence, but there is little]" time="0.351"><properties><property name="score" value="0.00184427085" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00184427 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00184427
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Egyptian government is to impose a tax on the purchase of gold in an effort to halt a rapid depreciation in the value of the Egyptian pound.\n\nThe move comes as Egypt is also struggling to curb inflation as well as a shortage of foreign currency to finance imports.\n\nThe Ministry of Finance is imposing a 15 percent tax on the sale of gold and a 20 percent tax on the sale of gold jewellery.\n\nThe move is aimed at preventing the conversion of gold into currency which is fuelling inflation.\n\nUnder the Egyptian Constitution, it is illegal to convert gold into currency.\n\nThe collapse in the value of the pound, which is currently trading at its lowest rate since 2004, has prompted a rush to gold as people try to protect their wealth.\n\nSince the 2011 revolution, the Egyptian pound has lost around 60 percent of its value against the dollar.\n\nEgypt is still suffering from a shortage of dollars which are needed to finance imports of food, medicine and fuel.\n\nThe government is now considering a $10 billion dollar loan from the International Monetary Fund.]" time="0.255"><properties><property name="score" value="0.5472484" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u201cBe strong, and of good courage; fear not, nor be afraid of them: for the LORD thy God, he it is that doth go with thee; he will not fail thee, nor forsake thee\u201d (Deuteronomy 31:6).\n\nThe battle-scarred commander is giving his parting words to the soldiers under his command. He encourages them to continue in the service of the Lord despite the difficulties and dangers they face. These were the Israelites who left the safety and prosperity of Egypt for the uncertainties of Canaan. Their task was to displace the wicked Canaanites who occupied the land. This was no easy task, and many a valiant warrior fell in the struggle. Still the Lord promised to go before the Israelites and help them defeat the Canaanites and claim the land for their own.\n\nGod had promised to go before the Israelites. This is a familiar theme in the Old Testament. But it is also a familiar theme in the New Testament. Paul told the Hebrew believers in Rome, \u201cWherefore, as by one man sin entered into the world, and death by sin; and so death passed upon all men, for that all have sinned:\u201d (Romans 5:12). In this statement Paul used two Old Testament examples to illustrate the extent of the power of sin to destroy life. First he noted that the life-giving properties of the soil were destroyed when Adam sinned. In the garden of Eden the ground had yielded to Adam and Eve fruits and nuts of every kind, but after the fall man was forced to work hard for his sustenance. Then Paul cited the most recent Old Testament example: \u201cFor when the Gentiles, which have not the law, do by nature the things contained in the law, these, having not the law, are a law unto themselves\u201d (Romans 2:14). The Lord had promised to go before the Israelites to help them drive out the Canaanites from the land of promise. After Adam\u2019s fall God said to the serpent, \u201cAnd I will put enmity between thee and the woman, and between thy seed and her seed; it shall bruise thy head, and thou shalt bruise his heel\u201d (Genesis 3:15). The serpent\u2019s head was bruised when Christ died for the sins of all men, but the serpent\u2019s head would ultimately be bruised by the Messiah\u2019s heel.\n\nAt the end of the Old Testament era God had to rescue His people Israel from a most perilous situation. The ten northern tribes had refused to obey God\u2019s commands and had rejected His prophets. Because of their sins God allowed Israel to be conquered by the Assyrian army and taken into exile. The Judahites and Benjaminites were spared destruction, but Judah was brought to the brink of extinction. God sent prophets to warn the Israelites of their imminent destruction, but they would not listen to the prophets. In spite of these disasters the Lord promised to go before His people to help them drive out the Canaanites from the land of promise.\n\nThe Israelites under Joshua drove out the Canaanites and occupied their land. But the Israelites were destined to live in a hostile world. The Canaanites had been their neighbors in Egypt. In the land of Canaan they were surrounded by nations hostile to the God of Israel.\n\nIn the life of the New Testament believer there are the same difficulties and dangers. It was never the purpose of God to give His children an easy life in this world. In fact, the Bible says, \u201cBlessed is the man that endureth temptation: for when he is tried, he shall receive the crown of life, which the Lord hath promised to them that love him\u201d (James 1:12). We must not be surprised by the temptations and trials that are part of the Christian life. \u201cFor whom the Lord loveth he chasteneth, and scourgeth every son whom he receiveth\u201d (Hebrews 12:6). The Lord\u2019s chastisements are part of His discipline, and His purpose in chastening us is not to destroy us but to bring us to maturity.\n\nHow do we endure these trials and temptations? We endure by remembering that we are engaged in the battle of the Lord. It is not our strength that carries us through, but the Lord Himself. \u201cFor the LORD thy God, he it is that doth go with thee; he will not fail thee, nor forsake thee\u201d (Deuteronomy 31:6).\n\nIs it easy to trust the Lord with all my cares and burdens? No, it is not easy to trust the Lord with the details of my life, but it is necessary. If we do not trust Him to be our guide, our protector, our helper, our comforter, we cannot live a godly life. We have to trust Him, but we have to do more than that. We have to walk by faith, not by sight. This is not easy to do. There are times when it is very difficult to trust the Lord in the midst of great troubles. We have to take a stand of faith and put our trust in the Lord in the midst of overwhelming trials and temptations. This is the only way to have victory over our enemies and the enemies of the Lord. \u201cBe strong, and of good courage; fear not, nor be afraid of them: for the LORD thy God, he it is that doth go with thee; he will not fail thee, nor forsake thee\u201d (Deuteronomy 31:6).\n\nGod\u2019s promise to go before the Israelites was a promise of victory over the enemies of Israel, and the same promise is made to every believer. God wants His people to know that He will help them overcome every obstacle in the Christian life. The greatest promise that God makes to His people is that He will not forsake them. This promise applies not only to our trials and temptations, but also to our sins and the temptations of Satan. \u201cFor God hath not appointed us to wrath, but to obtain salvation by our Lord Jesus Christ\u201d (I Thessalonians 5:9). The word \u201cappoint\u201d means to arrange beforehand. It is in the Lord\u2019s providential plan that we are to obtain salvation, and He will arrange for us to have that salvation. The word \u201cwrath\u201d means a dreadful passion. The Lord has not planned for us to experience His dreadful anger. He has planned that we should live in the love and grace of His own presence. The Holy Spirit comes to live in our hearts and abide with us forever. In His own time He will gather us to be with Him forever in heaven. But until that time comes He will abide with us and go before us to help us overcome the enemies of our souls. He will not forsake us.]" time="0.623"><properties><property name="score" value="0.386918514" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.38691851 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.38691851
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Of or relating to, or being a composite figure formed by the merging of two or more figures, especially of a human with an animal, in art or sculpture.\n\nPenderecki's stylistic pluralism in this score [for F.W. Murnau's 'Nosferatu, eine Symphonie des Grauens'] is part of an effort to break down the wall between music and non-music, so that [in] one of his earlier pieces, for example, the movement titles are "slur," "tremolo," "pizzicato," and "slide."\n\nMore\n\nPage 4 The third attempt [to emulate a voice] is a little bit more relaxed, and the fourth one is even more relaxed than that. And then you can go back to normal; it's really beautiful. It's like some sort of sacrifice. I enjoy that a lot. When I can start screaming and moaning again, it's great! (Johansson, 1999: 45) The breath that is drawn to fill a singing... Appears in 2 books from 2000-2004\n\nPage 10 There's some sort of connection with Wagner, which I enjoy, and certainly it's also that kind of, shall I say, coital language which I think is very satisfying as well. But I like the fact that it's a sort of construct; I mean, I don't sing when I'm not singing. And I don't actually scream or moan in my daily life; it's sort of something that you have to put into place. So it's a sort of creation, in a way. (Johansson, 1999: 44) The... Appears in 2 books from 2000-2004\n\nPage 12 Vocalise can be performed in either voice, although with her soprano's voice, she tends to sing it in the higher register. When performed, it is sometimes accompanied by a second performer on the same instrument, or on a synthesiser, who plays a free counterpoint melody, as the example in Ex. 1.2 shows. She cites her admiration for the performance of Zeena Parkins, who performed the Vocalise with Paal Nilssen-Love on drums. Appears in 2 books from 2000-2004\n\nPage 8 All vocalise exercises start with a very long inhalation, held while the hands remain fixed in the starting position. The breathing is then let out slowly, with the hands moving from the starting position down through the air. This is done very slowly in the lower register, and more quickly in the upper register. She states that this exercise works on voice-control and breath-control, and is performed slowly and evenly with the diaphragm. Appears in 2 books from 2000-2004\n\nPage 8 All vocalise exercises start with a very long inhalation, held while the hands remain fixed in the starting position. The breathing is then let out slowly, with the hands moving from the starting position down through the air. This is done very slowly in the lower register, and more quickly in the upper register. She states that this exercise works on voice-control and breath-control, and is performed slowly and evenly with the diaphragm. Appears in 2 books from 2000-2004\n\nPage 10 It's part of the artistic process, really. The singer is in charge of that and you are the vessel, really. You're letting something in and then releasing something. It's not like I'm releasing something that's already inside me; it's more that I'm allowing something to enter me. I mean, when I say singing it's sort of like, you know, you don't just go "ah, ah, ah, ah" when you're singing. I have some kind of technique, I guess, but it's more about opening up and releasing something that's already there. I mean... Appears in 2 books from 2000-2004\n\nPage 10 It's part of the artistic process, really. The singer is in charge of that and you are the vessel, really. You're letting something in and then releasing something. It's not like I'm releasing something that's already inside me; it's more that I'm allowing something to enter me. I mean, when I say singing it's sort of like, you know, you don't just go "ah, ah, ah, ah" when you're singing. I have some kind of technique, I guess, but it's more about opening up and releasing... Appears in 2 books from 2000-2004\n\nPage 10 Vocalise can be performed in either voice, although with her soprano's voice, she tends to sing it in the higher register. When performed, it is sometimes accompanied by a second performer on the same instrument, or on a synthesiser, who plays a free counterpoint melody, as the example in Ex. 1.2 shows. She cites her admiration for the performance of Zeena Parkins, who performed the Vocalise with Paal Nilssen-Love on drums. Appears in 2 books from 2000-2004\n\nLess]" time="0.373"><properties><property name="score" value="0.00079573585" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[By Melissa Nightingale\n\nAnxiousness during pregnancy is common, but doesn't usually come from a mum's partner.\n\nBut that's what's happened to Susanne* and after a few years of problems with anxiety, the stress of her partner's anxiety is causing trouble for her pregnancy.\n\nThe 35-year-old from Queensland was the one in her relationship who had been suffering with anxiety in the past, but it has now changed as her partner has become more anxious over time.\n\n"I used to be the anxious one, and he used to be the calming one," Susanne said.\n\n"We used to come home from work and I'd have a bit of wine, and he'd say 'have a glass of water'.\n\n"He used to be the one who'd be able to talk me down, and I'd always be the one to say 'let's not worry about it, it's not worth it'."\n\nIt started when Susanne started a new job.\n\nShe said at first it was hard to find a full-time job after studying for a Master of Education.\n\n"I'd go for a job and think, 'oh that's alright, but it's not the job for me'," she said.\n\n"I wasn't getting anywhere, and he was getting really anxious about it.\n\n"I was getting anxious about it too, but I just said 'this is the way it is, it's going to take time'."\n\nSusanne said he was the one who had a hard time, but she didn't have a lot of problems in that time.\n\n"I found it a bit difficult to find a job, but I'm quite a confident person," she said.\n\n"He became very stressed. He's a type A personality and is very good with working things out.\n\n"He'd ask me 'do you think you're going to get a job soon?' and I'd say 'I don't know, hopefully'.\n\n"I'd start to get anxious about it and I wouldn't want to talk about it because I didn't want to bring him down."\n\nWhen Susanne was looking for jobs, she wanted to take the job in Melbourne as it was closer to her partner's family.\n\nHer partner agreed, and as they were living with his parents in their country home at the time, he went to Melbourne to work while Susanne remained in Brisbane.\n\nBut after some time, the couple started to feel it was the wrong decision.\n\n"When he went to Melbourne, he just kept working and working, and he's such a hard worker and he would just keep working all day and all night," Susanne said.\n\n"He didn't really like Melbourne either, it's a hard place.\n\n"He was on his own there and he got very lonely and missed his family and I didn't want to go down to Melbourne because I thought I wouldn't see him as much, so we decided to move to the Gold Coast."\n\nBut with a baby on the way, Susanne said she feels like she is going to be moving around a lot in the next two years.\n\n"It's pretty hard to have a baby when you're living with your parents and it's just me and him, and when we move into our own house, I don't know how we'll manage," she said.\n\n"It's been really hard and he's been stressed and anxious a lot.\n\n"He used to be the one who said everything would be OK, but now he just worries about everything."\n\nAfter becoming pregnant, Susanne said her partner had a lot of problems with their financial situation.\n\n"He said 'I'm really worried about our finances' and I said 'it's fine, we'll be alright'," she said.\n\n"But he got a bit anxious and it started to rub off on me.\n\n"We would talk about money a lot, and he would go to his parents and get a lot of advice.\n\n"I didn't really mind talking about it and he would get stressed about it, but I'm the type of person who doesn't really care."\n\nSusanne said she would find her partner on the phone to his mum "constantly", and he would get more and more anxious about things.\n\n"It really started to affect me and it was hard," she said.\n\n"He didn't say 'sorry I'm a bit stressed' or 'I need some time to myself' - he would just carry on.\n\n"When I was pregnant, I had a really hard time because I was pregnant and it was hard to do things, and I didn't want to be]" time="0.379"><properties><property name="score" value="0.009370542" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[An industrial materials company based in Missouri has agreed to pay a $200,000 penalty to resolve allegations that it violated the Clean Water Act and an associated Consent Decree. Alkali Specialties LLC, a subsidiary of the Louisiana-based Alkali Specialties Group, entered into the settlement agreement with the U.S. Environmental Protection Agency (EPA).\n\nThe settlement agreement states that Alkali Specialties did not properly manage hazardous wastes generated from the company\u2019s glass manufacturing operations, as agreed upon in a 2008 Consent Decree. The violations include failure to properly characterize and treat wastewater and contamination of water supplies and fish in two states. In one case, the company dumped wastewater from a high pressure alkaline cleaning process into a manhole, which drained into a stormwater ditch that fed into a drainage ditch connected to a local stream. EPA\u2019s investigation discovered fish die-offs and contamination of the local water supply.\n\n\u201cProperly treating industrial wastewater is not optional,\u201d said EPA Regional Administrator Shawn M. Garvin. \u201cThe owners and operators of Alkali Specialties could have avoided these serious violations by having good management practices in place to make sure that wastewater containing hazardous chemicals was safely and properly treated.\u201d\n\nThe company is required to have an EPA-approved management plan in place to ensure proper treatment of the company\u2019s wastewater. A list of the company\u2019s manufacturing activities and associated wastewater characteristics must also be included in the plan. The company also must pay a $5,000 civil penalty.\n\nThe Consent Decree requires Alkali Specialties to treat wastewater generated by its glass manufacturing processes through a municipal wastewater treatment system or industrial wastewater treatment system. The company is required to install monitoring devices and submit reports that track how the company is meeting the Decree\u2019s requirements.\n\nAlkali Specialties operates glass manufacturing facilities in Wisconsin, Missouri, and Virginia.]" time="0.321"><properties><property name="score" value="0.0012187168" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00121872 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00121872
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I was only around 4 or 5, so I was not old enough to ride alone, and this is one of the only pictures of me with my dad. He always liked his motorcycle, but I am sure he would be even more thrilled with his daughter riding around.\n\nSometimes when I am out on my motorcycle, people ask me how I got into it. It is not something that I started from an early age. I actually have not ridden a motorcycle for more than a few years, but I have always had a soft spot in my heart for them.\n\nI was only around 4 or 5, so I was not old enough to ride alone, and this is one of the only pictures of me with my dad. He always liked his motorcycle, but I am sure he would be even more thrilled with his daughter riding around.\n\nHe always had a motorcycle on the side. This is another picture of my dad and me when I was very little. We used to ride on his motorcycle with him on the back, and me in front with my head over the seat. I could always feel him riding around with me, and he always made me feel so secure. He was always a very good father. I would love to have more time with him.\n\nThat was what motorcycles were for him. He never had time to go off on a road trip or anything like that, but he loved the feeling of riding.\n\nHe always rode a Yamaha, but he never wanted anything too fancy. He always said that they were built so strong, and that you didn\u2019t need all of the other features to have a great ride. He said that they were built well and would last for a long time.\n\nI always wanted to get one, but I never had enough money. He was always happy to teach me how to ride, but he also wanted to be there with me. I still get on the back of my boyfriend\u2019s bike, and I feel like I am with him.\n\nMy dad had a terrible accident on his motorcycle, and he was taken to the hospital where he was on the road to recovery. He had a broken leg, which led to some complications that he could not overcome. He passed away a few days later, and he was only 52 years old.\n\nWe all had a lot of great memories together, and I am sure he would be so happy that I now own a motorcycle. I don\u2019t go out on long trips, but I love riding my motorcycle around town. I am sure he would be thrilled that I am out and about on my own motorcycle.]" time="0.309"><properties><property name="score" value="0.04443278" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\xd7 T\xe9rminos y Condiciones\n\nDatos de contacto:\n\nTel\xe9fono: +34 932 518 115\n\nE-mail: info@outdoorandtravel.com\n\nDerechos de autor:\n\nTodas las im\xe1genes, gr\xe1ficos y textos que aparecen en este sitio web, as\xed como el sitio web en s\xed, est\xe1n protegidos por derechos de autor. Se prohibe la reproducci\xf3n total o parcial de todos los contenidos sin el consentimiento expreso de Outdoor and Travel.\n\nLos contenidos que aparecen en este sitio web se proporcionan para uso personal y no comercial. Se proh\xedbe la modificaci\xf3n, copia, distribuci\xf3n, transmitir, reproducir o explotar los contenidos de este sitio web, o crear obras derivadas a partir de ellos, para cualquier prop\xf3sito comercial, sin el consentimiento expreso de Outdoor and Travel.\n\nLas im\xe1genes de clientes de Outdoor and Travel s\xf3lo est\xe1n disponibles para uso editorial y con fines comerciales. El permiso debe ser solicitado antes de su uso.\n\nEnlaces:\n\nSalvo indicaci\xf3n expresa, Outdoor and Travel no tiene ninguna conexi\xf3n con las empresas o sitios web que se puedan encontrar accediendo a trav\xe9s de los enlaces de este sitio web. El objetivo de estos enlaces es \xfanicamente proporcionar a los usuarios la oportunidad de acceder a dichos enlaces.\n\nAl acceder a los sitios web que se pueden encontrar mediante los enlaces, el usuario se compromete a no reproducir, copiar, distribuir, permitir el acceso a trav\xe9s de ning\xfan otro sitio web, no modificar, no comercializar, ni hacer obras derivadas de los contenidos a que se acceda a trav\xe9s de los enlaces.\n\nLos enlaces se proporcionan \xfanicamente para la comodidad del usuario. El contenido y el software que proporciona un sitio web accesible mediante un enlace no pueden ser responsabilizados por el contenido de dicho sitio web.\n\nT\xe9rminos y condiciones de venta:\n\nTodos los precios indicados en el sitio web de Outdoor and Travel se muestran en Euros y est\xe1n expresados en Euros. Todos los precios incluyen el IVA en Espa\xf1a (excepto en productos de exportaci\xf3n).\n\nLa entrega de los productos se realiza en todos los casos, tanto en Espa\xf1a]" time="0.314"><properties><property name="score" value="0.013761636" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[At the moment, one of the biggest news in the cryptocurrency world is that EOS (EOS) blockchain is going live on June 1st. This is of course great news, but is it enough to attract investors and businesses to this new project?\n\nHere are five things you need to know about EOS.\n\n1. The EOS is the fifth-largest cryptocurrency by market cap\n\nRight now, EOS is the fifth-largest cryptocurrency in the world with a total market cap of over 14 billion dollars. You will also find out that this is way behind of the biggest one \u2013 bitcoin, with almost $250 billion total market cap.\n\n2. EOS is a platform, not a token\n\nAs mentioned above, EOS is not a token \u2013 it is a platform that allows developers to create apps on the EOS blockchain. While this may sound strange to some people, you can easily see the reasoning behind this.\n\nWith EOS, all dApps on the platform will work with each other in order to create a better end-user experience. EOS is also designed to provide the possibility for the new developers to launch their applications in a few minutes, without having to write any code.\n\nEOS has a great potential because its founders are already the creators of one of the most popular crypto platforms \u2013 Block.one, which also made a lot of money from its $4 billion token sale last year.\n\n3. EOS wants to become a better Ethereum\n\nMany people claim that EOS wants to become a better version of Ethereum. They are also looking to become the most powerful infrastructure for dApp developers, and they are also targeting some of the biggest industries like social media, finance, supply chain, healthcare, and others.\n\n4. EOS launched its first dApp called \u2018Plebs\u2019\n\nOne of the first dApps that will launch on the EOS platform is called \u201cPlebs\u201d. This is a social network for blockchain enthusiasts and cryptocurrency traders. The first thing that you will notice when you log in is the \u201ccryptocurrency wallet\u201d button that will allow users to trade all sorts of tokens on the platform.\n\n5. EOS\u2019 token distribution was one of the biggest in history\n\nEOS managed to raise almost $4 billion from its token distribution event back in 2017. For comparison, the second biggest crowd sale was for Ethereum, which managed to raise $18 million in the same year.\n\nWhile EOS has an interesting approach and has a good team, the launch of EOS MainNet will determine whether this project will succeed or not. The first version of EOS MainNet is expected to go live on June 1st, 2018.\n\nWe will be updating our subscribers as soon as we know more. For the latest on EOS, sign up for our Telegram!\n\nDisclaimer: This article should not be taken as, and is not intended to provide, investment advice. Global Coin Report and/or its affiliates, employees, writers, and subcontractors are cryptocurrency investors and from time to time may or may not have holdings in some of the coins or tokens they cover. Please conduct your own thorough research before investing in any cryptocurrency.\n\nImage courtesy of alexmillos via Flickr]" time="0.337"><properties><property name="score" value="0.030309087" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03030909 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03030909
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Share. Who's to blame? Who's to blame?\n\nToday at a San Diego Comic-Con panel, Marvel made some pretty big announcements about its Inhumans franchise, including a major change for the show.\n\nThe ABC series will no longer be a TV show, but a limited series of movies that will hit theaters first, and then air on TV.\n\nMarvel Studios president Kevin Feige was joined on stage by Jeph Loeb, head of Marvel Television. Feige took the blame for this change, admitting that the show had changed since its inception.\n\nMarvel TV and Film Are Now One "Unified Narrative" in the MCU 10+ IMAGES Fullscreen Image Artboard 3 Copy Artboard 3 ESC 01 OF 13 Marvel's Inhumans star Anson Mount in Marvel's Inhumans: "For years, comic book fans wanted Marvel to bring the Inhumans to the screen, but it wasn't until I joined the Marvel family that I realized the caliber of their anticipation." 01 OF 13 Marvel's Inhumans star Anson Mount in Marvel's Inhumans: "For years, comic book fans wanted Marvel to bring the Inhumans to the screen, but it wasn't until I joined the Marvel family that I realized the caliber of their anticipation." Marvel TV and Film Are Now One "Unified Narrative" in the MCU Download Image Captions ESC\n\nLoeb explained that as the show was being developed, it morphed into something quite different than what they had intended. That's when they decided to rework it into a movie, which will have its own narrative, but will also be tied to the bigger Marvel Cinematic Universe. Loeb and Feige stressed that the show is a completely different property from the movies, but that they do want to see it connect.\n\nAs a result of this change, the pilot of the show, which was already shot, will not be used. So, what was shot?\n\nMarvel's Inhumans: All Character Images 8 IMAGES Fullscreen Image Artboard 3 Copy Artboard 3 ESC 01 OF 08 Black Bolt (Anson Mount) in Marvel's Inhumans 01 OF 08 Black Bolt (Anson Mount) in Marvel's Inhumans Marvel's Inhumans: All Character Images ABC Download Image Captions ESC\n\nThe new version of the show will debut in theaters, but after that, it will move to ABC. It will run for eight episodes, which will then air in a two-hour TV event. The eight-episode run will be followed by the first two episodes of The Inhumans television show, which will then air weekly on ABC. It's unclear if the subsequent six episodes will debut exclusively on the TV show, or in theaters before TV.\n\nAll eight episodes will be made available on the same day for viewers who want to watch on TV. The show will debut on Imax for two weeks.\n\nSo what does this mean for the characters who are set to appear on the show? Black Bolt and Medusa will definitely appear, but they won't be played by Anson Mount and Serinda Swan. Marvel did not announce who will take over the roles of the two leaders of the Inhuman Royal Family.\n\nOn the other hand, Maximus the Mad will be portrayed by Iwan Rheon (Game of Thrones), who's replacing Ken Leung. He was shown on the big screen at the panel.\n\nShowrunner Scott Buck, who's also worked on Iron Fist, is sticking around for the reworked version of the show.\n\nExit Theatre Mode\n\nThe panel also announced several new cast members for the Inhumans movie, including:\n\nEllen Woglom will play an unidentified character.\n\nwill play an unidentified character. She's joined by Sonya Balmores , who will play Auran .\n\n, who will play . Mike Moh will play Triton , the Royal Family's cousin.\n\nwill play , the Royal Family's cousin. Then there's Elizabeth Cheng , who will play a member of the Royal Guard .\n\n, who will play a member of the . The last casting is of a young boy named Dante , who will be played by newcomer Emilio Kelevra .\n\n, who will be played by newcomer . That leaves Lockjaw, who is being played by an animatronic dog, the movement of which was demoed on the stage.\n\nThe Inhumans will debut in theaters on September 1, 2019. The first two episodes will debut on ABC after that, before the rest of the series will continue on the network.\n\nFor more on the Marvel Cinematic Universe, here's what the studio's TV shows are coming between now and 2021.]" time="0.395"><properties><property name="score" value="0.016006127" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01600613 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01600613
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I have come to accept a sad truth: Apple's Safari browser, and to a lesser extent the Mac operating system, does not work with some of my websites. This isn't a new realization, I've known this for some time. But this morning I came across a website that highlights this sad truth more clearly than usual.\n\nThis website is best viewed in Safari (OS X) or Firefox.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is best viewed in Chrome.\n\nThis website is best viewed in Safari.\n\nThis website is]" time="0.412"><properties><property name="score" value="0.0005788217" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Coordinates:\n\nThe Haystack Mountain School of Crafts was established in 1937, in the town of Deer Isle, Maine, USA. Originally a summer school, it was established by a small group of craftspeople including George Elbert Burr, Ernest N. Griggs, Bernard Leach, Francis D. and Irene Castle, Charles Keck, Samuel Hubbard, Eugene Savage, and others. In 1970, it became a year-round institution. In 1971, the Haystack Graduate School of Fine Arts was established.[1]\n\nHaystack hosts a variety of adult and youth workshops throughout the year on jewelry making, sculpture, glassblowing, blacksmithing, woodworking, ceramics, photography, bookbinding, and metalsmithing.\n\nHaystack operates an intern program during the school year, and an exchange program during the summer. There is a low-cost, on-site dormitory for year-round students.\n\nIn 2007, Haystack's main building burned to the ground. Haystack lost all of its facilities and began the construction of a new building on the same site, based on the original designs.]" time="0.394"><properties><property name="score" value="0.29203478" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Singapore is a big city. Too big, some might say. One of the nice things about this small, tightly-controlled island is that the government keeps the population contained in small, well-defined areas, or \u201cestates\u201d. And if you know anything about me, you know I love it when things are tightly controlled. But the trouble is that most of the estates are quite old and, therefore, cramped. So Singapore is often ranked near the top in the dubious \u201cquality of living\u201d lists. But it\u2019s a small price to pay for the island\u2019s many other virtues. And like I said, Singaporeans know what they are doing.\n\nOne thing that they have done is devise the wonderfully named \u201cqueue jump lanes\u201d for the MRT (subway). And the way that it works is simple: instead of everyone using a bunch of doors to get on and off the train, the doors are grouped by destination and one door in each group is for the \u201cqueue jump\u201d lane. The \u201cjumpers\u201d simply get in line to board the train at a set of doors that they are waiting at and if enough people are waiting behind them (they have to be at least three or four), then the train doors open for them and they can board the train.\n\nBut what makes this so great is that the MRT station doesn\u2019t really have any huge lines. Everyone is in the same line to board the train and it works very efficiently. And because the commuters are all in the same line, the stations don\u2019t get too crowded and everyone gets on and off the train quickly. And it\u2019s such a simple, elegant solution to the age-old problem of waiting in line to board a train. But it has to be done in a very organized manner or it will not work. And Singaporeans are good at organizing things. And they are good at following instructions. So it works.\n\nThis is why Singaporean officials now have big plans to clean up the Internet in their island state. They are just following orders. You see, Singapore is a clean and neat place, like an apartment or a house. And it\u2019s a small island with lots of people. And if you have people living together and living closely together, you will have problems with things like personal space, personal hygiene and cleanliness. And Singapore has rules for these things, just like any other well-ordered and tidy city. And because of these rules, it is a good place to live. And the Internet is a wild and wooly place that needs to be tamed.\n\nThe government has already started to act against sites with porn and gambling. But the new, bold and determined, Internet-cleanup effort has begun. The effort will tackle sites that \u201cadvocate homosexuality, obscenity, violence, terrorism or any other illicit activities.\u201d And with those loose guidelines, I\u2019m sure the government will be able to take down all sorts of sites. But Singapore is a good place to live and it should be a good place to surf.\n\nI\u2019ve spent the last few years cleaning up the sites I have on the Internet, as well as cleaning up myself. I\u2019ve stopped going to a therapist because I feel good. I\u2019ve stopped going to AA meetings because I\u2019m no longer an alcoholic. And I\u2019ve stopped going to NA meetings because I\u2019m no longer a drug addict. And now I\u2019m sure that I will never be at a gambling site again because I\u2019m no longer a gambler. And I\u2019m sure that I will never see any sites with porn, but that\u2019s just because I\u2019m too lazy to look for it.\n\nAnd I\u2019m not advocating that people with any of those problems should try to change. Those things are just the bad in my life. But I know that I am on the right track and I am making progress. And I have not been to a therapist in two months and I have not been to an AA meeting in over three months. And I have not been to a NA meeting in more than a year. And I am clean and I feel great.\n\nI think that I\u2019ll be getting to bed early tonight. It\u2019s been a big day.]" time="0.480"><properties><property name="score" value="0.3591572" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.3591572 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.3591572
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Farscape star Virginia Hey (a.k.a. the telepathic Peacekeeper Aeryn Sun) talks about her audition for the part of Queen Amidala, the controversial character of the Star Wars prequels and just what happened with Episode III.\n\n"I read for Episode III," she told reporters at the recent Wizard World Los Angeles, adding that she didn't make the final cut, but felt she "did a good job in the audition."\n\nHey's Aussie accent was probably a factor, she suggested, as George Lucas "is quite particular" about "that British accent." Hey actually got her first big break in an American production, playing a Japanese ninja in the 1988 Clint Eastwood movie The Dead Pool.\n\nAccording to Hey, she read for Episode III with the late Christopher Lee, who played Count Dooku in the movie. Lee, she said, had the room bursting into laughter when she saw him reading the scene with her.\n\nSo does that mean Lee was doing his performance all wrong? Hey answered the question by saying "I don't think that I could have ever come close to him."\n\nSo, what does she think of the Star Wars prequels?\n\n"They're well made, they're great films," she said, adding that "the first film is the one that always comes up when I'm talking about the movies."\n\nHey's Aussie accent probably didn't help her chances of being cast in the role of Padm\xe9.\n\nAs far as what fans thought of the prequels, Hey said she was never really sure because, "I wasn't in them."\n\nImage courtesy Virginian Hey.]" time="1.784"><properties><property name="score" value="0.18651222" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.18651222 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.18651222
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The video will start in 8 Cancel\n\nGet daily updates directly to your inbox Subscribe Thank you for subscribing See our privacy notice Could not subscribe, try again later Invalid Email\n\nHarry Redknapp has revealed the players that former Birmingham City manager Harry Redknapp wanted to sign for Queens Park Rangers during his time in charge of the club.\n\nThe 70-year-old was only in charge at Loftus Road for the 2013-14 season and in that time he managed to take the club to promotion to the Premier League.\n\nIn that time he worked alongside the likes of Joey Barton, Rio Ferdinand and Joey "Cinderella Man" Barton, who all played a role in helping the club to promotion.\n\nBut he also had a massive say in which players he wanted to sign during his time with the club.\n\nSpeaking in a Q&A with The Sun , Redknapp was asked which players he wanted to sign for the club and revealed that he wanted to bring in a number of players, including Spurs forward Harry Kane.\n\n(Image: Paul Gilham/Getty Images)\n\n"We wanted to sign the Spurs kid [Harry] Kane but he was injured," Redknapp said.\n\nRedknapp added that he had the chance to sign Neymar from his spell with Paris Saint-Germain and also tried to bring in Luis Suarez from Liverpool.\n\nRedknapp was a guest on Sky's Sunday Supplement this morning, where he spoke about what it was like working with Ferdinand.\n\n(Image: Bryn Lennon/Getty Images)\n\nHe said: "What a player he was. I used to think I've got Rio Ferdinand. It's like having Roy Keane or Nemanja Vidic in your team.\n\n"And he's a really nice lad. People probably think he's hard but he's really not.\n\n"Rio and his brother Anton, they're top lads."]" time="0.311"><properties><property name="score" value="2.0349975" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[British and U.S. officials this week agreed on a plan to halt Iran\u2019s nuclear program by using sanctions and diplomacy, the Times of London reported, citing unnamed senior U.S. officials.\n\nThe plan, which could be implemented in a matter of weeks, will include a dramatic increase in financial sanctions, together with covert sabotage and military action, the newspaper reported, without giving details.\n\nIn Washington, the State Department said it had no comment on the report.\n\nOfficials from both countries are to meet again this week in Washington to discuss further plans, the newspaper said.\n\nThe newspaper, citing unnamed officials, said the new plan would impose a package of sanctions which could see the European Union ban the import of Iranian oil.\n\n\u201cIf we have the sanctions come together, then we will be ready to move quickly,\u201d the Times quoted one of the U.S. officials as saying.\n\nU.S. officials said the new plan would incorporate measures drawn up by Israel, which has also urged more sanctions, the newspaper said.\n\nThe Israeli officials told U.S. counterparts they were concerned about the credibility of any sanctions imposed as a result of a plan agreed by the permanent five members of the U.N. Security Council \u2014 Britain, China, France, Russia and the United States \u2014 but not by other states, the Times said.\n\nThe new plan calls for \u201cthe credible threat of military force against the Iranian nuclear program,\u201d it said.\n\nThe plan, drawn up by U.S. Secretary of State Hillary Clinton, calls for targeted assassinations and for stepping up cyber attacks, it said.\n\nBut the newspaper quoted U.S. officials as saying that even these were unlikely to be effective in stopping Iran\u2019s nuclear program, unless they were accompanied by severe sanctions.\n\nThe United States and its European allies have made several attempts to persuade Iran to stop its uranium enrichment program, which they believe aims to produce nuclear weapons, but Tehran has repeatedly refused.\n\nIran denies the charge, insisting its program is purely civilian.\n\n(Photo: Reuters)]" time="0.379"><properties><property name="score" value="0.0007792884" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00077929 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00077929
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[by Kilian Melloy\n\nTuesday Sep 7, 2012\n\nIn a reversal of the "lesbian bed death" myth, a recent study has found that long-term lesbian relationships -- like heterosexual ones -- are not characterized by a "slow erosion" of sexual desire, as long as the women feel satisfied with their relationships.\n\nLesbian couples who reported feeling satisfied with their relationships were as likely to report having sex as often as heterosexual couples, the study showed, LiveScience reported on Aug. 29.\n\nThe findings reversed the notion that women in same-sex relationships are less likely to experience the "sexual boredom" that supposedly characterizes relationships between women, according to LiveScience.\n\n"Sexual frequency was similar for heterosexual and lesbian couples," LiveScience quoted U.S. sociologist Kristen Schilt, who co-authored the study, as saying. "If we saw that same result among heterosexuals, everyone would be surprised, because we tend to think of heterosexual sex as normative and everybody kind of expects that."\n\nThe study was based on findings from two national surveys of American adults, conducted in 1990-91 and in 2008-10, respectively.\n\nThe findings also held true in a subsequent analysis that included men and women.\n\n"[I]f they felt satisfied with their relationship, they were having sex just as often as heterosexuals," Schilt said, according to the article.\n\nA 2011 study found that lesbian relationships tended to be more satisfying for the women involved than their male-female counterparts, although gay male relationships tended to be more satisfying for the men, the article reported.]" time="0.308"><properties><property name="score" value="1.0277271" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.0277271 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.0277271
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Today I want to talk about this "Alternative f\xfcr Deutschland". They claim that they are a political party, they are running for parliament. But in reality, they are a political gang.\n\nWhat is a political party? A political party is a group of people that thinks about political ideas, and formulates these into political goals. This group tries to get a certain number of people elected to the parliament. They may also want to participate in elections for other types of political bodies. For example, the "Alternative f\xfcr Deutschland" is also running for the European Parliament.\n\nWhat is a political gang? A political gang is a group of people that thinks about political ideas, but only to a certain degree. The group isn't actually trying to get people elected, but tries to create political pressure in other ways. They may also try to influence public opinion, as far as that is possible for a political gang.\n\nBoth political parties and political gangs are a waste of time. Both types of group are only interested in the power to influence. If one looks at the political agenda of the AfD, it can be seen that it is only interested in getting into the parliament. They don't care about any political ideas. They don't have any. They only want to get their political friends into the parliament.\n\nSome AfD members might think that they are doing their country a service. But in reality, they are helping to lower the political quality of Germany. They are helping to lower the German nation's intellectual level. They are doing this by political gang behavior. By not acting as a political party, they are deliberately working against democracy, and undermining the nation's sovereignty.\n\nIf the AfD members want to get into the parliament, they should at least act like a political party. They should actually talk about ideas. The AfD should have a political program. This political program should deal with Germany's immigration and emigration problems, as well as with other political issues. This program should be something that all members of the party agree upon. This program should then be explained to the public in a reasonable manner. The program should be accessible to everyone.\n\nThe AfD should make their political program available to the public in book form. This book should be made available for a minimal fee, and it should be available online, too. This book should be available in the "Kaufhof" chain of bookstores, as well as on Amazon.com and other online bookstores. It should also be available in the electronic version of the book on the AfD website.\n\nThe AfD could use the money received from selling the political program to cover their political expenses. This would also help to explain the political program to the public. It could even result in the members of the AfD getting a new impression of what a political party should be.\n\nA political gang should not run for parliament. They should not call themselves a political party. A political gang is not a substitute for a political party. In the future, political parties should not allow political gangs to run in elections.]" time="0.386"><properties><property name="score" value="0.06696281" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[(Warning: Contains graphic content)\n\nThe Obama administration\u2019s refusal to recognize the Benghazi attack as a terrorist attack was the subject of some of the most pointed questioning by Sen. Rand Paul in Secretary of State John Kerry\u2019s appearance before the Senate Foreign Relations Committee on Wednesday.\n\n\u201cThe reason I\u2019m asking this question is, if this had been an attack by a mob, if it had been an attack by people who were upset about a video, is this is how I\u2019d have responded,\u201d Paul said to Kerry. \u201cI would have immediately called for the closing of the Embassies. I would have thought about the real danger to the embassy. And I would have asked all the people to leave the embassy. And when I went to the CIA, I would have said to everyone, \u2018We\u2019re going to have to do some of this in America. And if there\u2019s any American that\u2019s involved in any way, arrest them and interrogate them.\u2019\u201d\n\nHe went on: \u201cIn Libya, you didn\u2019t do that. In Egypt, you didn\u2019t do that. You didn\u2019t do that in Turkey. You\u2019re doing it in Yemen. And so I would say, yes, I think it\u2019s fair to say it was a terrorist attack.\u201d\n\nHe then asked Kerry why the administration hadn\u2019t acted more forcefully when the attack occurred, especially in light of the knowledge that al-Qaeda had been attempting to establish a presence in Libya.\n\n\u201cI would\u2019ve closed the embassy. I would have said it\u2019s not worth the risk to do the work,\u201d Paul continued. \u201cI think I would have said this is a place that\u2019s so chaotic, we\u2019re putting our embassy in a very bad place. I would have admitted it.\u201d\n\nKerry refused to directly answer the questions posed to him by Paul, instead pointing out that the State Department had]" time="0.464"><properties><property name="score" value="0.11923647" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.11923647 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.11923647
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The video will start in 8 Cancel\n\nGet the biggest daily stories by email Subscribe Thank you for subscribing We have more newsletters Show me See our privacy notice Could not subscribe, try again later Invalid Email\n\nFloyd Mayweather has claimed that he's received an offer of \xa330m to take on Conor McGregor in a rematch.\n\nThe boxing legend stunned the world when he defeated the UFC lightweight champion in Las Vegas last year.\n\nMcGregor was making his professional boxing debut as he was taken down by a veteran master.\n\nBut McGregor has made it clear that he wants a rematch and that he'll return to the squared circle.\n\nAnd now it's been claimed that Mayweather has been offered \xa330m for a rematch with the UFC lightweight champion.\n\nBut the American insists he doesn't need the cash.\n\n(Image: Getty Images North America)\n\nMayweather has told the Sunday Mirror: "I\u2019m happy with my position.\n\n"I\u2019m happy with my achievements.\n\n"I\u2019m satisfied with my career.\n\n\u201cI don\u2019t need money. I do it for the fans. I like to entertain the fans.\n\n\u201cI really don\u2019t care about money at this stage. I\u2019m already a billionaire.\n\n\u201cA lot of people think money is my motivation.\n\n\u201cAnd they\u2019re absolutely right. I have lots of money, that\u2019s right.\n\n\u201cBut I\u2019m doing it for the love of the game.\n\n\u201cAll the other fighters I know don\u2019t have money like me. They need money. I don\u2019t need money.\n\n\u201cThat\u2019s why I\u2019m going out there to entertain. I\u2019m going out there to put on a show.\n\n\u201cI don\u2019t need the money. I want the money.\u201d]" time="0.296"><properties><property name="score" value="0.085130274" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08513027 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08513027
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Carabao Cup was first played for in 1971/72. However, the EFL had previously played a knock-out competition in a similar format - the Football League Cup - in 1960/61.\n\nSince its inception in the 1970s, the Carabao Cup has gone from strength to strength, as the competition is now widely regarded as the country\u2019s second most prestigious cup competition.\n\nAs well as the main trophy, the winner of the Carabao Cup also receive a cash prize of \xa390,000 and they qualify for the following season's UEFA Europa League.\n\nThe competition's format is open to a total of 88 teams: all 20 members of the Premier League and at least the first three teams from each of the Championship, League One and League Two (if the winners of those competitions have already qualified for Europe through their league position).\n\nThe non-league clubs that do not qualify for Europe are then invited to play in the competition, while the top four from the FA Vase and the winners of the FA Trophy, EFL Cup and EFL Trophy enter at the third-round stage.\n\nThe team with the highest finish in the League One or League Two is given the final place in the third round.\n\nMatches are two-legged (except the final, which is one-off), with the team with the highest aggregate score in each leg proceeding to the next round.\n\nFrom the fourth round onwards, the format reverts to a single-game, with extra-time and penalties used if required.]" time="0.292"><properties><property name="score" value="0.5607844" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.5607844 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.5607844
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Bill Clinton went on a bit of a bizarre rant while campaigning for his wife in Colorado this week. He had some pretty choice words for Bernie Sanders\u2019 supporters. You know, the \u201cpurists\u201d who want a \u201crevolution\u201d.\n\nThe Wall Street Journal posted video of the moment and I\u2019m so glad they did. You won\u2019t believe what he said.\n\nWatch:\n\n\u201cI think it\u2019s very interesting. There\u2019s a reason that young people are saying: \u2018Hey, I\u2019m really concerned about this issue of income inequality, but I\u2019m not sure I\u2019m willing to take a million dollars in negative ads to get somebody who will have the same position I will have when I wake up in the morning.\u2019 I think they\u2019re willing to take that chance to say: \u2018This is really important to us. And we\u2019re going to help you through this primary process to say it\u2019s important to you and we\u2019re going to give you ideas and ways to change things.\u2019\n\nAnd that\u2019s what I think they mean. They\u2019re not just being, I think, naive politically. I think they mean what they say. And I think they\u2019re going to be a very powerful force.\u201d\n\nWow, that\u2019s some rant. Let\u2019s unpack that a little.\n\nFirst, Bernie\u2019s supporters aren\u2019t saying they want their candidate to win the nomination just to vote for Clinton. They want him to win. They want to see the revolution he\u2019s been talking about since he started running for president.\n\nAnd if you\u2019re wondering how he\u2019s going to get to the White House without the millions of dollars in negative ads that are part of the \u201cswamp\u201d Clinton herself says she\u2019s going to drain, the answer is by actually inspiring people to vote for him because of his ideas. He\u2019s not taking money from big corporations and wealthy people. He\u2019s getting it from individual donors, just like Bernie Sanders.\n\nSecond, if Sanders supporters are supposed to be naive to think they can get a revolution by electing a candidate who will help to bring one about, then Hillary Clinton supporters are just plain delusional. There\u2019s no way she can do it without the millions of dollars she\u2019s raising. She doesn\u2019t inspire anyone. She\u2019s a wealthy, out-of-touch candidate whose campaign is all about her because she has so little to offer the American people that she has to convince them she\u2019s not a \u201ccrook\u201d.\n\nHer policies are so conservative that she\u2019s found herself on the wrong side of the issues where she\u2019s actually needed to take a stand. Hillary doesn\u2019t believe in the actual goals of a revolution.\n\nWhat do you think? Is Hillary a stronger candidate for her own revolution or for Bernie\u2019s?\n\n]" time="0.306"><properties><property name="score" value="0.009084734" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00908473 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00908473
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[So I'll post the bottom line first, I don't recommend you go to Great Clips if you have hair that is even close to being down past your shoulders. Let's just say that there is no way that they can cut your hair unless it's wet, and as it dries, it ends up looking like they used a weed-whacker on it. When I arrived at the location (1220 S. Main St. in Bowling Green, OH) I was greeted by a nice girl who asked me how I wanted my hair cut. I said that I wanted it short, but with layers. I'm a senior in college, so it's nice to have something that makes me look professional in the summer time, without having to worry about how long it takes to style it each morning.\n\nSo she started cutting it and it looked good. It was only $11, which is a good price for a haircut. I waited there for about 15 minutes before the girl finished cutting it and called me over to the dryers. I sat down and she blow dried my hair with a round brush, which I don't normally do, but it didn't seem to make much of a difference. As she started to dry it, I started to notice how choppy it looked. She said "it looks really good. I'm glad I cut it so short, I was thinking about cutting it longer, but I think you look good like this". I was disappointed because my hair looked terrible, but at least it was only $11, and I was able to get it cut before I had to go back to class.\n\nWhen I went to class, I went up to my professor to show her how awful the haircut looked. She told me that I needed to go to the student center to get it fixed. I was getting really frustrated because I had class at 3:15, and there were no available appointments to fix it, so I was told to come back tomorrow. When I got back, I went to the salon and they told me that it would take 20 minutes to fix, and would cost $30. I said that I didn't think it was worth the money to have them fix it, so I asked how I could get my money back. They said I could go to another location and get another haircut to use the coupon that was still on it.\n\nThe next morning, I went to Great Clips on South Highway 25. I got there and was greeted by a very nice girl. I explained to her the situation, and she said that she would be happy to fix it. She washed it out and put a trim on it. When she was done, I went back over to the mirror and could barely recognize myself. I had long, flowing layers. It was beautiful. I went back to the girl who helped me and she handed me a card for $5 off my next visit. I was glad to know that I had someone I could trust to cut my hair from now on.]" time="0.339"><properties><property name="score" value="0.060818695" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[International School of Helsinki\n\nTeacher of French\n\nJari Pohjola\n\nI studied French at the University of Helsinki, completing a BA in 2004 and an MA in 2006. In 2004, I started working as an Assistant Language Teacher (ALT) at Helsinki International School, initially teaching Finnish and then later moving to the French department in the autumn of 2007. I completed a certificate in teaching French as a second language at the University of Helsinki in 2009 and then continued to study at the school\u2019s \u2018Master\u2019s level\u2019 programme, which I completed in 2010.\n\nIn the future, I hope to continue my studies by pursuing a Ph.D. in the field of language teaching methodology. I have also been teaching at the university level since 2011.\n\nAs well as working at the International School of Helsinki, I also work as a freelance teacher of French at other language centres in Helsinki, working with various age groups and also teaching as a private tutor. I am currently the Coordinator of the Curriculum Committee at the school, and also the chair of the French Department, having previously held the position of Chair of the Department of Modern Languages from 2010 to 2014.\n\nI live in Helsinki with my wife and our two sons, aged four and one.\n\nSchool:]" time="0.308"><properties><property name="score" value="0.65274155" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.65274155 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.65274155
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[You can help D&D Wiki by improving the formatting on this page. When the formatting has been changed so that this template is no longer applicable please remove this template. If you do not understand D&D Wiki's formatting standards please leave comments on this page's talk page before making any edits.\n\nEdit this Page | All pages needing formatting help\n\nUndead are the animated corpses of the deceased, brought back to unlife through foul magic or divine intervention.\n\nMost undead are mindless automatons that wander about, attacking the living if they are mindless or left un-commanded by their controller. Some of these undead are highly intelligent, acting as soldiers in armies or guardians of tombs. More powerful undead have been known to roam the world under their own volition, seeking to kill the living for revenge or to fuel their undeath.\n\nBeing intelligent creatures, undead can be found in many different social standings. In the cities of civilized races, the dead are commonly entombed and given proper funerals, while necromancers sometimes command vast armies of the undead to do their bidding.\n\nAnimate Dead [ edit ]\n\nThe magic-user is able to make the corpse of a creature move and attack.\n\nThe undead created will depend on the level of the magic-user:\n\nIf the magic-user is 1st level, then the undead can be a corpse of a man-sized animal such as a wolf, bear, or lion. The corpse may be "animated" with the appropriate skills such as: Climb, Hide, or Move Silently. The DM will determine what skills the corpse has.\n\nIf the magic-user is 2nd level, then the undead can be a man-sized corpse with two or more of the above skills. For every level beyond 2nd level, the corpse may gain another skill.\n\nAnimated dead may be commanded by the controlling magic-user as a free action, or they may be allowed to wander without purpose as mindless automatons. The undead may also be set to attack one target only or be left free to attack any target within range. The undead may be controlled in such a way as to be under the command of any creature holding the control device, as a charge-based device or wand, as a magical amulet, or by any other means.\n\nIf the magic-user is killed, then the control device is automatically destroyed. If the magic-user is unwilling to control the undead, or if he wishes to relinquish control, then the undead must make a Will save against the magic-user's level +2 or become uncontrolled.\n\nThe animate dead spell cannot create any undead creature with a 4+1 or better on the Hit Dice. If the corpse is missing a limb or appendage, the corpse may not use that particular appendage. The missing limb may be reattached by a cleric with 8+ experience level. The reattachment requires 1 minute of chanting, a flask of holy water, a light fire, and two torches.\n\n\n\nExample: Thaeron, a 1st level magic-user, animates a dead wolf with the skill climb, but the wolf has no skill of hide. This wolf can move, but is not able to hide from the sight of the living.\n\n\n\nExample: Kairon, a 3rd level magic-user, animates a wolf, giving it the skills of climb, hide, and move silently. Kairon now has a very stealthy animal to use for reconnaissance.\n\n\n\nExample: Emric, a 5th level magic-user, animates a dead lion. Emric now has a formidable beast to add to his retinue.\n\nCAUTION: Undead created through this spell may not be raised or resurrected. Only the spell life can restore the dead to life.\n\nAstral Prison [ edit ]\n\nThe magic-user causes a single creature to be imprisoned within its own body. This spell cannot be dispelled, but may be ended by a successful Dispel Magic spell cast upon the victim.\n\nThe victim of the Astral Prison spell will not be able to take any actions, but will be able to communicate normally with any creature within the same square as the victim. The victim will be able to leave his body for up to 4 turns each day, during which time he can move anywhere within spell range and return to his body at will.\n\nThe victim of the Astral Prison spell is not considered helpless while his body is within the Astral Plane.\n\n\n\nExample: Rab, a 1st level magic-user, controls Grog, a 6th level fighter, who is a real bully and would do well to be imprisoned. Rab casts Astral Prison on Grog. Grog is trapped within his own body and is now helpless. Grog can use up to 4 turns each day in which he may leave his body and attack from afar.\n\nCause Disease [ edit ]\n\nThe magic-user may make a touch attack on a creature within spell range, and the victim must make a Fortitude save vs. the magic-user's level or be afflicted by a random disease.\n\nThe spell-caster may attempt to use the cause disease spell a number of times per day equal to his magic-user level. The save DC against the disease is 10 + magic-user level.\n\nThe caster must be]" time="0.431"><properties><property name="score" value="0.141310825" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.14131083 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.14131083
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Pope Francis told journalists Thursday that it is not enough to be a good Catholic; one also must evangelize others in the faith.\n\n\u201cBeing a good Catholic, being a good Christian, is not enough,\u201d the pope said, speaking to journalists in the papal plane.\n\nFrancis noted that in his youth there were few Catholics in Argentina, so when people became baptized, it made a \u201cbig noise.\u201d\n\n\u201cNow we have many more Catholics, and many Catholics who even call themselves good Catholics, but they do not go to Mass, they do not go to confession, they do not know their catechism.\u201d\n\n\u201cThey\u2019re not Catholics,\u201d he said.\n\n\u201cIf a person is not open to new life, is not open to the other, is not evangelizing, that person is not a good Christian.\u201d\n\nAs he has in the past, Francis spoke out against an \u201cinvasive culture of comfort,\u201d in which people are \u201csatisfied\u201d and stop seeking God.\n\n\u201cBeing a Christian is not the result of an interior choice or a vague inclination. It is not enough to be just a \u2018nice guy,\u2019\u201d he said.\n\nThe pope noted that in the time of St. Paul, there was a prevalent belief that in order to gain access to the temple, it was enough to pay taxes and be a Roman citizen, and Paul had to tell them that they were \u201cwithout God.\u201d\n\n\u201cIn our time, we are a little like the pagans of Paul\u2019s time,\u201d he said.\n\n\u201cWe go along thinking, we are a \u2018citizen,\u2019 a \u2018good person,\u2019 a \u2018good Catholic,\u2019 a \u2018good Christian,\u2019 and we do not realize that we are \u2018without God.\u2019\u201d\n\nTo be a Christian, he said, is to \u201cmake Jesus Christ be born in every person.\u201d\n\n\u201cI do not want to be a \u2018citizen,\u2019 I do not want to be \u2018a nice guy.\u2019 No, I want to be a Christian,\u201d the pope said.\n\nFollow Thomas D. Williams on Twitter Follow @tdwilliamsrome]" time="0.263"><properties><property name="score" value="0.05974814" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05974814 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05974814
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[We have heard of many things that keep bees away from your garden and people have tried different ways to prevent the bees from coming near them. This article is written to enlighten you with facts that may not be known to you about bees.\n\n#1: Male Bees are All Slackers\n\nIt has been a common fact that male bees are the slackers in the bee world. Male bees don't help much in the nest building or care of the young ones, but they enjoy mating and honey. As the female bees usually do all the work, some of them live alone.\n\n#2: They Don't See Red\n\nBees see in colors, but don't have the ability to see the color red. They don't have the ability to see this color because their eyes don't have red light receptors.\n\n#3: Do You Know What Bees Eat?\n\nWe all know that bees feed on nectar, but it is not their only source of food. Bees also feed on pollen, and other sweets.\n\n#4: Honey Bees Are Not Biting\n\nHoney bees have two tiny, barbed stingers and they sting only when they feel threatened or they are protecting their hives or their young ones. Honey bees don't go about biting people and this is the reason why they are so loved.\n\n#5: How Much Honey Do Bees Produce?\n\nBees use honey to survive the winter season. Bees produce honey by sucking out the nectar from flowers. Honey is a bee's primary food and it makes up 80% of its diet. The amount of honey produced by bees is variable and depends on the flowering of plants and the weather.\n\n#6: The Queen Has Only One Boyfriend\n\nA queen bee mates only once in her life. After this mating, she will live for about five years and during this time, she will lay more than 1500 eggs per day.\n\n#7: Only Worker Bees Produce Honey\n\nIn the beehive, only worker bees produce honey. The queen bee has no role to play in honey production. It is the workers who collect the nectar and turn it into honey. The queen just lays eggs.\n\n#8: Life Cycle of a Honey Bee\n\nA honey bee goes through three stages of development, which are: egg, larva and adult. It takes about 21 days for a honey bee to complete its life cycle.\n\n#9: The Nest of a Bee is Always Busy\n\nIf you think the nest of a bee is quiet and empty, you are mistaken. The nest of a bee is always busy and buzzing with activity. The queen bee lays around 1,500 eggs every day.\n\n#10: Did You Know That Bees Sting?\n\nWe have heard this fact many times, but we don't think that we will ever come across bees in our gardens. But bees can sting and they do sting if they feel threatened or disturbed.\n\n#11: Honey Bees Can Live Only in America\n\nThere are about 4,000 species of honey bees all over the world and only one species can be found in America. It is the European honey bee. This species of honey bee is found in South and Central America, North America and some parts of Asia and Australia.\n\n#12: A Bee Makes Six Flights Every Day\n\nEach bee has to make six flights every day for the development of the honey comb. Bees make their honeycombs in a hexagonal shape.\n\n#13: There Are Female Only and Male Only Bees\n\nBees are either female or male. There are no male bees without a stinger or female bees without a st]" time="0.300"><properties><property name="score" value="0.070127815" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The 168th Semiannual General Conference of the Church of Jesus Christ of Latter-day Saints begins today. This will be the last time for six years that conference will be held in the Salt Lake City Tabernacle on Temple Square. The event will be broadcast live in English, Spanish and Portuguese to millions of viewers around the world.\n\nDownloadable HD video for journalists\n\nDownloadable HD video for journalists\n\nDownloadable HD video for journalists\n\nThe October general conference sessions are always held in the Conference Center on Temple Square in downtown Salt Lake City. The Conference Center was completed in 2000 and has been the location for the LDS Church's general conference sessions since that time.\n\nThe Conference Center seats 21,000 people, more than the Tabernacle on Temple Square. Although the Tabernacle was designed to seat more than 10,000 people, it has not been used for general conference in many years.\n\nThe Tabernacle, constructed in 1867, is the second oldest religious building in Utah and the oldest on Temple Square. The building has had many names and occupants, and it was damaged by fire several times.\n\nThe Tabernacle was the first home of the Mormon Tabernacle Choir and was used by the choir and others as a temporary home until the Assembly Hall was completed in 1877. The Tabernacle then became the home of the world-renowned choir for the next 62 years.\n\nThe Tabernacle was gutted by fire in 1867, 1873 and 1882. The fire in 1867 destroyed the roof, and the Tabernacle was closed for a year. Reconstruction and repairs were made quickly, and the Tabernacle reopened on July 4, 1868.\n\nThe Tabernacle, built of rock, mortar and local timber, was the only building on Temple Square for 30 years. In 1888, the Assembly Hall, built of wood, was added.\n\nThe Manti Temple, constructed in 1888, was the first building on Temple Square to be constructed of stone. The Utah State Capitol was completed in 1896, and the Temple block in Salt Lake City was becoming an architectural showcase.\n\nIn 1893, the Salt Lake Temple, constructed of granite and marble, was completed. The Salt Lake Temple and Tabernacle were designed by church architect Truman O. Angell. In addition to his work for the church, he designed the Cathedral of the Madeleine and the Ogden Tabernacle.\n\nDuring construction of the Temple and Tabernacle, Angell took measurements and photographs of the original Nauvoo Temple. Those measurements and photos provided the basis for construction of the Nauvoo Temple, which was completed in 2002.\n\nAfter the completion of the Salt Lake Temple, many of the early leaders of the LDS Church felt the need to have another temple built in Salt Lake City to accommodate the thousands of faithful members who could not live in the Salt Lake Valley.\n\nWork on the Endowment House, the temple precursor, began in 1855. However, construction was delayed because of a financial depression. The LDS Church decided to cease construction of the Endowment House in 1856 and to use the structure as a school for Indian children.\n\nIn 1869, construction of the Endowment House resumed. The original plan called for an expanded facility, but the leaders of the LDS Church decided to keep the building small, and the temple ordinances were performed in the Endowment House for the next 62 years.\n\nThe Endowment House was destroyed by fire on the morning of Dec. 17, 1892. The decision to build a new temple was made immediately, and the location of the new temple was decided in the afternoon.\n\nThe decision to build a new temple came from the experiences of church president Wilford Woodruff in the St. George Temple. Woodruff often stayed in the St. George Temple during visits to southern Utah. During one of those visits, he had a dream in which he saw an angel. The angel instructed him to return to the St. George Temple and perform the sacred endowments.\n\nUpon his return, Woodruff was unable to locate the temple and was disappointed. However, as he was returning to his hotel, he had a second dream in which he again saw the angel. The angel instructed Woodruff to perform the sacred endowments in the St. George Temple as soon as possible.\n\nIn addition, the LDS Church presidency was in dire need of a new temple. The Endowment House was becoming crowded and was not large enough for the members.\n\nAfter his experiences in St. George, Woodruff was directed by an angel to build a new temple. The building committee selected the site in 1892 and selected the current location for the temple in 1894.\n\nThe LDS Church has been in continuous construction of temples since 1833, when the Kirtland Temple was completed. The first temple was destroyed in a fire in 1838.\n\nAs of the beginning of the semiannual general conference on Oct. 3, 2016, there were 137 temples in operation around the world and a total of 148 in various stages of construction. The first LDS temple outside of the United States was built in Bern, Switzerland, and dedicated in 1955.\n\nThe Salt Lake Temple, the oldest LDS temple still in operation, is in the final stages of a two-year renovation.\n\nThe conference sessions will begin with a meeting of general conference leadership, including the First Presidency and the Quorum of the Twelve Apostles, at 6:30 p.m. MST on Thursday.\n\nOn Friday, the session will begin at 9 a.m. and be broadcast live on the LDS Church satellite system and on Mormon Channel, with rebroadcasts throughout the day.\n\nThe priesthood and Sunday sessions will be held at 10 a.m. The general priesthood meeting will be broadcast live on Mormon Channel and on the LDS Church satellite system, with rebroadcasts throughout the day.\n\nThe general women's meeting will be held at 5 p.m. The meeting will be broadcast live on Mormon Channel and on the LDS Church satellite system, with rebroadcasts throughout the day.\n\nThe general sessions on Saturday will begin at 10 a.m. The priesthood and Sunday sessions will be held at 1 p.m. Both of the Saturday sessions will be broadcast live on Mormon Channel and on the LDS Church satellite system, with rebroadcasts throughout the day.\n\nFollowing the conference sessions, the Tabernacle Choir will present a concert in the Conference Center at 8 p.m. on Saturday, which will be broadcast live on the LDS Church satellite system and on Mormon Channel.\n\n[email protected]]" time="0.605"><properties><property name="score" value="0.019818002" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The 9/11 suspects and the FBI's elite\n\nThere's a new development in the endless story of the Sept. 11, 2001, attacks and the killing of Osama bin Laden: Allegations that FBI agents on an elite unit violated rules by exceeding their surveillance authority.\n\nIn the latest investigative account, the Associated Press reports that these agents also spent as many as 15,000 hours each \u2014 that's five full-time work years \u2014 monitoring as many as 5,000 Americans. The AP claims this happened from 2002 to 2008.\n\nThe allegations are already roiling Capitol Hill, and the case could become a major embarrassment for the FBI. Lawmakers are raising questions about why they weren't told sooner, and what kind of surveillance was involved.\n\nThis development has some historical echoes for me. I reported in the 1990s on the FBI's counterterrorism squad, code-named PENTTBOMB, and the challenges agents faced. After 9/11, I investigated problems with the bureau's efforts to recruit translators \u2014 a problem it has still not fully overcome. And I reported that one al-Qaeda plotter who slipped through the FBI's fingers was involved in a New Jersey case that also raised privacy concerns.\n\nThe FBI's new problems stem from an agent on the bureau's "transnational" squad. That team was established in 2000 to collect intelligence on threats from groups or individuals abroad, then translate and analyze it for use by FBI agents on domestic crimes.\n\nThe PENTTBOMB squad had been formed after the 1995 Oklahoma City bombing, which was committed by an American who used fertilizer and fuel oil to kill 168 people. Among the dead were 19 children, and the blast devastated a federal office building.\n\nAn FBI supervisor suspected an Islamic extremist link, so PENTTBOMB agents were put on the case. The name is a truncation of "pentagon" and "Tower," a reference to the location of the attack.\n\nThe team went on to investigate two other attacks with similar ties: the 1998 bombings of two U.S. embassies in East Africa that killed more than 200 people and injured 5,000 more, and the 2000 attack on the USS Cole off Yemen, which killed 17 American sailors.\n\nThe PENTTBOMB team eventually went on to a separate mission: tracking Osama bin Laden and al-Qaeda after the 9/11 attacks.\n\n(For a while, the FBI's most prominent post-9/11 agent was John O'Neill, who died in the World Trade Center attacks. O'Neill was on the PENTTBOMB squad and had been the chief of counterterrorism at the FBI's New York office. I spoke with him a number of times in 1998 and 1999. He was brusque, profane and passionate about terrorism.)\n\nA good deal has been written about the efforts to find and kill bin Laden, so I won't]" time="0.343"><properties><property name="score" value="0.31361553" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.31361553 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.31361553
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[I. INTRODUCTION\n\nIn American society, the most important basis for a successful marriage is to be found in the universal and unchanging relationship of male and female. The male as head of the family has an intrinsic responsibility for the wellbeing and well-being of his wife and children. For a man, failure to fulfill that responsibility constitutes not only a sin against God but also a sin against society. The reason for this is that men are obliged to marry to propagate the race. Since the greater portion of the burden for this is placed upon men, they must realize their responsibility for providing a home. The institution of marriage, then, is a social and economic institution. Without it, society would not survive.\n\nThe idea of male headship is also founded on the fact that men and women are intrinsically different, as the Creator has made them. From the beginning of Creation, God has given men the leadership role, which was expressed in the headship of Adam over Eve. Even in the animal world, males take the leadership role over females. This idea of male headship continues through the history of Israel as the Lord selected men for leadership roles: Isaac, Jacob, and Joseph, for example. Even after the sin in the Garden of Eden, God instructed Adam that it was necessary for him to provide for his wife and children.\n\nThe male and female are fundamentally different in some significant ways. Males have always been given greater physical strength. Moreover, women, as a whole, are physically weaker. They are also emotionally more sensitive than men and, therefore, have the responsibility for bearing and raising children. The male is, however, called upon to be the provider for the family. The man is, therefore, also obligated to work hard to provide for his wife and children, as a way of showing his love for his family. Men are to do this while their wives are bearing and raising children, so that they may also participate in these responsibilities to the fullest extent possible.\n\nTo further clarify the distinction between male and female, we have to consider the differences between a man and a woman's sexuality. God created women and men with different sexual natures, which include both a complementary function and a distinctive one. The function is complementary in the sense that a man and woman can only have sexual union with one another. Thus, their bodies are in harmony. However, the distinctive nature of men and women is that men can perform the sexual act without giving birth to children. The woman, however, cannot perform the sexual act without giving birth to children.\n\nMarriage is intended to be a total commitment between a man and woman. As such, it is a lifetime commitment, made by two people who give themselves to each other and to God. The importance of marriage to God is shown in the fact that He has designed it to be a lifelong relationship. Moreover, when man rejects the ideal of marriage that God has established for society, the relationship becomes a base matter of selfishness and self-gratification. Such a relationship is, at best, a poor substitute for the God-ordained institution. However, as in all sin, it is not the same as the ideal. Sin always has a negative effect on society. It is for this reason that God calls on mankind to obey Him. It is also why the Scriptures say that God hates divorce.\n\nII. WHY DIVORCE IS HATED BY GOD\n\nThe Scriptures show that divorce is a sin that God hates. He is displeased with it because it brings the curse of God on a society. The Scriptures condemn it in the strongest possible language and hold the man who has divorced his wife as being worse than the man who has never married at all.\n\nThe Mosaic Law expressly forbid divorce. This is not to be understood in a legal sense, since the Jews could divorce their wives by reason of her adultery (Deut. 22:21). Moreover, the Jews could divorce a non-Jewish wife by reason of her apostasy (Deut. 24:1-4). In both of these cases, the idea of divorce is understood in a religious context and is not limited to a legal system. This is true of other cases of divorce in the Old Testament as well. The husband can also divorce his wife for the more general reasons of neglect and cruelty (Deut. 22:19-21). In these cases, the idea of divorce is in a more general sense and not limited to a legal system.\n\nAt the beginning of the Christian Era, the Christian Church began to understand that marriage was intended to be a total commitment between two people, who had made a vow before God. Such a vow is understood to be a promise of lifelong commitment to each other and to God. As such, it was understood that such a vow could not be broken. In the fourth century, the Roman Church, under the leadership of Constantine, recognized this by excluding divorce from the authority of the Church. This is one of the reasons that marriage is seen as a sacrament in the Roman Church. It is also why the Church has, since that time, refused to grant a decree of divorce, even for adultery.\n\nThe idea of a lifetime commitment between a man and woman is also evident in the case of Paul and his wife, who are said to be "one flesh." Thus, Paul is exhorting believers to live in such a way that they do not bring disgrace upon their "brother." Moreover, Paul recognizes that this marriage between himself and his wife is the basis for all marriage. Therefore, if a believer is to live with his wife as if she were his sister, this would also require that he do the same to all the brothers and sisters of the Church.\n\nThe Apostle Peter speaks of divorce in his first letter in language similar to Paul's. This was also the view of the Early Church, both Catholic and Protestant. It is also the view of the Orthodox Churches, who do not permit divorce.\n\nIII. CHURCH TEACHINGS ON DIVORCE\n\nThe Church Fathers, such as Origen, did not believe that there could be a legal dissolution of marriage. According to Origen, "Christ was not to dissolve those marriages that are joined together by the solemn authority of the state, nor was He to abolish these rules which man in his law has established for the purpose of the procreation and the education of children, but He was to strengthen them." The Church Fathers believed that divorce was wrong because it separated man and wife. Marriage was a sacred union, which was made by God and was not subject to man's laws. However, this was not to be understood in a legal sense. It was wrong to divorce one's wife even though the laws of a nation permitted it. Moreover, this was to be the case even if the woman had committed adultery. Divorce was still wrong.\n\nThe Church Fathers viewed marriage as a sacrament. The idea that marriage was a sacrament is present in the early Church, even though it was not a formal decree of the Church until the Fourth Lateran Council in 1215. Marriage is recognized as a sacrament because it represents the love between Christ and His Church. Marriage is thus a sign of the covenant between Christ and His Church. Marriage is not only a sign of this covenant but also a means by which this covenant is expressed. Therefore, marriage is an important sacrament of the Christian Church.\n\nIn his Commentary on the Gospel of Matthew, St. Augustine makes it clear that the idea of a "sacrament" does not mean that marriage is a sign of the love between Christ and His Church. Marriage is a sacrament in the sense that it is a sacred reality, which is the sign of something else. It is the sacred reality, the divine idea that is the true sign of marriage. This is true of all the sacraments, in which the sign is a reality that is above the natural order. Therefore, the sacramental sign is but a small part of the reality to which it points. It is for this reason that the Church has forbidden remarriage after divorce. It is not because the Church has an opinion of divorce. The Church has always had an opinion of divorce. In the Early Church, however, remarriage after divorce was considered a sin. This is true even in cases where the woman had committed adultery.\n\nThe Orthodox Churches and the Roman Catholic Church have the same view on this matter. The Orthodox Church is opposed to divorce because it violates the principle of unity between Christ and His Church. They also understand the doctrine of marriage as an indissoluble union. It is this idea of marriage that is seen as the basis of the Orthodox teaching. The Roman Catholic Church also has the same view as the Orthodox Churches. The difference between the two churches is that the Roman Church has understood this to be a teaching that is rooted in Divine Revelation, whereas the Orthodox Churches have taken this to be the position of the Early Church.\n\nHowever, both the Roman Church and the Orthodox Churches have also taken this to be the teaching of the Early Church. In his Homilies on the Epistles of Paul to the Corinthians, Origen declares that marriage is a symbol of the union between Christ and His Church. This is the same teaching that is found in the Roman Church. Origen also takes this to be the teaching of the Early Church.\n\nIn his Commentary on the Gospel of Matthew, Augustine takes the same position. He sees marriage as a sacrament, in the sense that it represents the union between Christ and His Church. He states, "The bond of a valid marriage, which is]" time="1.124"><properties><property name="score" value="0.8594336646666667" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.85943366 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.85943366
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Erotic Diary of a Dom\n\nBuy this book\n\nIt\u2019s part-diary, part-reference guide, with entries for events of every day and long-term schedules for planned scenes.\n\nYou can use it to keep a written record of what happens in your Dom/sub relationship, a personal record of your exploits as a Dominant, or a reference book to help you plan your scenes.\n\nFull of over 150 BDSM-themed \u2018Kink Trackers\u2019, there is a place for almost anything you want to record. They\u2019re easy to fill in and make it easy to record your current level of Domination, the type of activities you enjoy doing with your partner, their pain tolerance, their limits, your progress as a Dom, or anything else you want to record.\n\nIt\u2019s a very handy, attractive and very sexy little book to add to your collection.\n\nHere\u2019s what you get inside:\n\nA list of 150+ Kink Trackers\n\nRecording space for everything you want to record\n\nScheduling space for planning sessions, noting which session went well, or recording things you want to try with your partner\n\nA list of Dom/sub relationship goals\n\nMood trackers\n\nA list of personality traits for both Doms and subs\n\nDescriptions of psychological types of Dom/sub relationship\n\nAnd more!\n\nGet The Erotic Diary of a Dom now!\n\nShare this: Facebook\n\nTwitter\n\nGoogle\n\nReddit\n\nTumblr\n\n]" time="0.430"><properties><property name="score" value="0.0027487085" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00274871 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00274871
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Restaurants are a dime a dozen in Playa del Carmen, and there are so many to choose from. Whether you are looking for authentic Mexican cuisine or something that tastes like the real thing from the States, Playa del Carmen has a restaurant for you. Check out this list of restaurants near us and around the area.\n\nBarbacoa De Burro\n\nA local Mexican favourite, this restaurant specializes in tacos and mexican cuisine. Barbacoa de Burro is located on Quinta Avenida in the Centro area of Playa del Carmen. If you are looking for authentic Mexican cuisine, this is your spot.\n\nCabo Cantina\n\nThis is another favourite among Playa del Carmen locals. Mexican and American style dishes make up their menu. In addition to the food, Cabo Cantina has a fully stocked bar and a lovely outside dining area. Cabo Cantina is located on Avenida 50th, just around the corner from Oasis Park.\n\nTacos El Torero\n\nTacos El Torero is known for their tacos, quesadillas and burgers. If you are looking for a great Mexican/American restaurant, this is a good place to start. Tacos El Torero is located on the Quinta Avenida in the heart of Playa del Carmen.\n\nLa Cabrera\n\nThis is one of the most popular Mexican restaurants in Playa del Carmen, and for good reason. La Cabrera is known for their authentic Mexican cuisine and warm service. They have a great variety of delicious menu options. La Cabrera is located on the Parque Obelisco in the center of Playa del Carmen.\n\nBanyan Tree\n\nBanyan Tree is a newer spot in Playa del Carmen. Their menu is traditional Thai food, with an emphasis on authentic cuisine. If you are looking for a tasty, authentic Thai dinner, this is the place for you.\n\nAgave\n\nAgave is a favorite among locals and tourists alike. They offer a variety of Mexican and American cuisine in a beautiful atmosphere. Agave is located on the Quinta Avenida in Playa del Carmen.\n\nEl Kabayitos\n\nEl Kabayitos is the spot to get authentic Mexican tacos. They also offer some great Mexican drinks, including beer and the popular tequila. El Kabayitos is located on the corner of Ave. 30th and 35th in Playa del Carmen.\n\nChez Clarita\n\nChez Clarita is a French/Mexican fusion restaurant located on Ave. 30th between 24th and 30th street. They offer a full bar with specialty drinks and a selection of French and Mexican inspired dishes.\n\nThe Local\n\nThis is one of the best restaurants in Playa del Carmen, and it is highly recommended. The Local offers a selection of sandwiches, salads, pizzas and more, in a very trendy and fun atmosphere. The Local is located in the center of Playa del Carmen on the corner of Ave. 15th and 15th street.]" time="0.311"><properties><property name="score" value="0.015054167" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Less than a week after Arnold Schwarzenegger acknowledged that he fathered a child more than a decade ago, Maria Shriver and the couple\u2019s four children are planning to attend the next few public events in the former governor\u2019s schedule, CNN has confirmed.\n\nThe appearances will include the 6 p.m. ET Tuesday premiere of Schwarzenegger\u2019s new documentary at the South By Southwest festival in Austin, Texas. Shriver, her children, and Schwarzenegger\u2019s children are expected to be in the audience.\n\nOn Thursday, the actor is scheduled to speak at the Arnold Sports Festival in Columbus, Ohio, where he\u2019ll receive the Lifetime Achievement Award. Shriver and the children are expected to be in the audience for that event as well, CNN has learned.\n\nThere are no plans for Shriver to accompany Schwarzenegger on a trip to Chicago later this month for the Radio & Television Congressional Correspondents dinner.\n\nMeanwhile, the cable news channel\u2019s sources say Shriver and the family are not attending Sunday\u2019s Academy Awards ceremony.\n\nDuring a statement released late last week, the former California governor apologized to his wife and children. \u201cI am deeply sorry for the pain I have caused Maria and our children,\u201d he said. \u201cI am truly sorry.\u201d\n\n\u201cI have behaved badly sometimes,\u201d he said. \u201cI have done things I thought I should not have done, and I regret it, and I apologize for it.\u201d]" time="0.337"><properties><property name="score" value="0.0040009995" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.004001 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.004001
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[* Article names are underlined if you are subscribed to this particular VTM Mailing List.\n\nTo receive all the article titles from all the different lists please see the main list archive page here.\n\nor\n\nTo join this list please click here.\n\n\n\n\n\n\n\nAPHRODITE ART REVIEWS\n\n-\n\n[November 16, 2006]\n\n\n\nCockroach\n\nby\n\nCharles Monroe-Kane\n\nArtists are fascinated by the big themes, like life, death, birth, sex, love, hate, justice, the stars, the universe, the gods and goddesses, the collective unconscious, human beings and how we react, what we do, what we are, the cosmos, and all that kind of thing. Charles Monroe-Kane is fascinated with cockroaches. Now, there's a big theme.\n\n\n\nMonroe-Kane's show at the Linda Hodges Gallery, titled "Cockroach", features thirteen pieces that feature his favored theme. It may be an unusual choice of subject, but then again, artists have often been drawn to the taboo or the forbidden or the socially unacceptable.\n\n\n\nIn most of these pieces Monroe-Kane depicts, either alone or in various groups, roaches in a variety of settings. One of his works, titled "The Cockroach Hike", consists of a lone cockroach walking across a granite boulder. The rock is set in an ethereal mist that obscures its exact location, but somehow I suspect it's not in California. It's a stunning piece.\n\n\n\nOne of my favorite works in this show, titled "The Dead Roach Walking", shows a dead cockroach standing up, covered in a sparkling coating of gold paint. It's as if it had been so dead for so long that it was actually turned to gold. The title comes from the Elvis Presley song of the same name. The roach, painted gold, is wearing Elvis's famous white sequin jumpsuit. The letters "CELEBRITY" adorn the creature's abdomen. This is a truly macabre yet]" time="0.369"><properties><property name="score" value="0.015453905" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01545391 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01545391
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[When it comes to natural beauty, words can't begin to describe this place. Looking out over the crashing waves, no man-made thing in sight, the solitude and vastness of the region makes your mind race to contemplate the universe. You're in awe, and yet, still feel a deep sense of comfort and belonging. It is a very special place, where it is easy to feel at peace. Whether you are at the lodge, by the pool, on a zodiac tour, or on a hike, you'll have a renewed sense of wonder and thankfulness for the wonders of this world.\n\nHow did you fall in love with your profession?\n\nOne of my fondest childhood memories is sitting in the car and looking at the grand, bright stars at night. I felt very much connected to the heavens, and longed to be an astronomer. As I got older, and I realized my dreams were much more achievable in the fashion world, I just sort of went with it. But, I always loved working with my hands and creating things, and that was what eventually brought me back to a love of astronomy.\n\nWhat is your favorite design element to work with?\n\nI love working with the raw materials of the earth, rocks, precious metals, and yes, even sand. It is fascinating to see these things and consider their origins. The best part is turning them into things that other people can use and appreciate.\n\n\n\nWhat was the last design you made?\n\nI made a ring for a recent film shoot, featuring several pieces of meteorite I had acquired. It was a great project to work on.\n\n\n\nWhat is your go-to travel item?\n\nI love our Infinite Earth candle, and I always carry it with me when I travel. It smells like the ocean, and makes the room smell good! I think the ocean is one of the most amazing places on Earth, so it is my go-to place for inspiration.]" time="0.335"><properties><property name="score" value="0.3146772" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[If you want a free pet but you're allergic to cats and dogs, consider a rabbit. There are so many different breeds out there and each breed has different personality traits. If you do your research, you can easily find the breed that is right for you. There are rabbits that are great lap pets while others are not so great and would rather be sitting in their own personal hutch.\n\nThe most common type of rabbit is the domestic rabbit. Domestic rabbits can be either the mini version or the full size version. The difference between the two is the mini version has a shorter body and the full size has a longer body. Some breeds will have more length to them than others.\n\nThe most common of the domestic rabbit breeds is the Holland Lop. The Holland Lop has a tiny, short body, stocky build, and short fur. Their fur is typically brown and they have floppy ears that hang down along their body. They're also very friendly, are very cuddly, and are fairly easy to care for.\n\nThe second most common of the domestic rabbit breeds is the Dutch. This rabbit breed has a longer body, stocky build, and short fur. Their fur is typically brown or white. They're not very friendly, but if you take the time to tame them, they can become very cuddly and affectionate. They are very vocal and have a "honking" type of noise they make when they're excited.\n\nThe third most common of the domestic rabbit breeds is the lionhead. The lionhead has a shorter body, stocky build, and a long coat of hair. The lionhead is also fairly vocal and has a "honking" type of noise they make when they're excited. They're not as friendly as the Dutch and the Holland Lop, but if you take the time to tame them, they can become very cuddly and affectionate.\n\nRabbits are great pets and if you decide to adopt one, make sure you find the breed that's right for you.]" time="0.345"><properties><property name="score" value="0.0032068251" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[#342a42 Color Information Information\n\nConversion\n\nSchemes\n\nAlternatives\n\nPreview\n\nShades and Tints\n\nTones\n\nBlindness Simulator In a RGB color space, hex #342a42 is composed of 20.4% red, 16.5% green and 25.9% blue. Whereas in a CMYK color space, it is composed of 23.5% cyan, 37.5% magenta, 0% yellow and 74.1% black. It has a hue angle of 268.4 degrees, a saturation of 24.2% and a lightness of 20.4%. #342a42 color hex could be obtained by blending #674274 with #000000. Closest websafe color is: #333333. \u2665 f t g\n\nR 20 G 16 B 26 RGB color chart\n\nC 23 M 37 Y 0 K 74 CMYK color chart\n\n\u25cf #342a42 color description : Very dark grayish violet.\n\n#342a42 Color Conversion The hexadecimal color #342a42 has RGB values of R:52, G:42, B:66 and CMYK values of C:0.23, M:0.37, Y:0, K:0.74. Its decimal value is 3393288. Hex triplet 342a42 #342a42 RGB Decimal 52, 42, 66 rgb(52,42,66) RGB Percent 20.4, 16.5, 25.9 rgb(20.4%,16.5%,25.9%) CMYK 23, 37, 0, 74 HSL 268.4\xb0, 24.2, 20.4 hsl(268.4,24.2%,20.4%) HSV (or HSB ) 268.4\xb0, 37.5, 25.9 Web Safe 333333 #333333 CIE-LAB 18.669, 11.054, -18.127 XYZ 2.78, 2.374, 5.744 xyY 0.26, 0.219, 2.374 CIE- LCH 18.669, 21.823, 310.309 CIE-LUV 18.669, 1.313, -18.915 Hunter-Lab 16.067, 5.363, -11.499 Binary 00110100, 00101010, 01000010\n\nAlternatives to #342a42 Below, you can see some colors close to #342a42. Having a set of related colors can be useful if you need an inspirational alternative to your original color choice. #3b2a42 #3b2a42 rgb(59,42,66)\n\n#382a42 #382a42 rgb(56,42,66)\n\n#362a42 #362a42 rgb(54,42,66)\n\n#342a42 #342a42 rgb(52,42,66)\n\n#332a42 #332a42 rgb(51,42,66)\n\n#322a42 #322a42 rgb(50,42,66)\n\n#3122a4 #3122a4 rgb(49,34,64) Similar Colors\n\n#342a42 Preview Text with hexadecimal color #342a42 This text has a font color of #342a42. <span style="color:#342a42;">Text here</span> #342a42 background color This paragraph has a background color of #342a42. <p style="background-color:#342a42;">Content here</p> #342a42 border color This element has a border color of #342a42. <div style="border:1px solid #342a42;">Content here</div> CSS codes .text {color:#342a42;} .background {background-color:#342a42;} .border {border:1px solid #342a42;}\n\nShades and Tints of #342a42 A shade is achieved by adding black to any pure hue, while a tint is created by mixing white to any pure color. In this example, #0d0c09 is the darkest color, while #ffffff is the lightest one. #0d0c09 #0d0c09 rgb(13,12,9)\n\n#1a1711 #1a1711 rgb(26,23,17)\n\n#271f19 #271f19 rgb(39,31,25)\n\n#342a42 #342a42 rgb(52,42,66)\n\n#41354a #41354a rgb(65,53,74)\n\n#4e405a #4e405a rgb(78,64,90)\n\n#5b4864 #5b4864 rgb(91,72,100)\n\n#67516c #67516c rgb(103,81,108)\n\n#715c76 #715c76 rgb(113,92,118)\n\n#7e666f #7e666f rgb(126,102,111)\n\n#8b6f7f #8b6f7f rgb(139,111,127)\n\n#977987 #977987 rgb(151,121,135)\n\n#a38496 #a38496 rgb(163,132,150) Shade Color Variation #ab8d9f #ab8d9f rgb(171,141,159)\n\n#b395a7 #b395a7 rgb(179,149,167)\n\n#ba9faf #ba9faf rgb(186,159,175)\n\n#c0aab7 #c0aab7 rgb(192,170,183)\n\n#c7b3bf #c7b3bf rgb(199,179,191)\n\n#cebcc7 #cebcc7 rgb(206,188,199)\n\n#d5c5cf #d5c5cf rgb(213,197,207)\n\n#ddced7 #ddced7 rgb(221,206,215)\n\n#e3d7df #e3d7df rgb(227,215,223)\n\n#ebe0e7 #ebe0e7 rgb(235,224,231)\n\n#f1e9f0 #f1e9f0 rgb(241,233,240)\n\n#f8f1f9 #f8f1f9 rgb(248,241,249)\n\n#ffffff #ffffff rgb(255,255,255) Tint Color Variation\n\nTones of #342a42 A tone is produced by adding gray to any pure hue. In this case, #31313b is the less saturated color, while #434e41 is the most saturated one. #31313b #31313b rgb(49,49,59)\n\n#34313f #34313f rgb(52,49,63)\n\n#362140 #362140 rgb(54,33,64)\n\n#372843 #372843 rgb(55,40,67)\n\n#382f45 #382f45 rgb(56,47,69)\n\n#3a2f48 #3a2f48 rgb(58,47,72)\n\n#3b2e4b #3b2e4b rgb(59,46,75)\n\n#3c2c4d #3c2c4d rgb(60,44,77)\n\n#3e2950 #3e2950 rgb(62,41,80)\n\n#403455 #403455 rgb(64,52,85)\n\n#413a58 #413a58 rgb(65,58,88)\n\n#43315b #43315b rgb(67,49,91)\n\n#443a5e #443a5e rgb(68,58,94)\n\n#453461 #453461 rgb(69,52,97)\n\n#472e63 #472e63 rgb(71,46,99)\n\n#4a3466 #4a3466 rgb(74,52,102)\n\n#4c3a68 #4c3a68 rgb(76,58,104)\n\n#4f3170 #4f3170 rgb(79,49,112)\n\n#523a72 #523a72 rgb(82,58,114)\n\n#54327b #54327b rgb(84,50,123)\n\n#564380 #564380 rgb(86,52,128)\n\n#58383a #58383a rgb(88,56,58)\n\n#594d3b #594d3b rgb(89,77,59)\n\n#5b4a3e #5b4a3e rgb(91,74,62)\n\n#5d4643 #5d4643 rgb(93,70,67)\n\n#604c46 #604c46 rgb(96,76,70)\n\n#62424a #62424a rgb(98,66,74)\n\n#64484d #64484d rgb(100,72,77)\n\n#652e50 #652e50 rgb(101,46,80)\n\n#664652 #664652 rgb]" time="0.454"><properties><property name="score" value="0.62411375" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A high school gym teacher from McDonough, Georgia has been arrested for an alleged sexual relationship with a female student.\n\nEverett Lee Compton, 27, of McDonough, was arrested by police in Henry County, Georgia on April 8 on one count of sexual assault against a person in custody, one count of sexual assault by a person with supervisory or disciplinary authority, and one count of sexual assault by a person in a position of trust or authority, according to the Atlanta Journal-Constitution.\n\nThe student at Henry County High School reported the relationship to police after her parents caught her exchanging explicit photos with Compton, who she said had \u201cstarted\u201d her \u201con fire for God.\u201d\n\n\u201cI\u2019ve never seen her like this,\u201d the student\u2019s mother said, \u201cI don\u2019t even know who this is.\u201d\n\n\u201cI know you said you love him and all that,\u201d the girl\u2019s mother told her, \u201cbut he\u2019s a teacher.\u201d\n\nThe mother told police that she confronted the teacher over text message, which is how they first learned about the relationship, but Compton denied the relationship.\n\n\u201cI\u2019m going to ask you to do something for me,\u201d he wrote in a text message. \u201cI\u2019m not saying it didn\u2019t happen but let me handle this my way.\u201d\n\nThe student reportedly told police that she and Compton met at her father\u2019s home, where the two smoked marijuana.\n\n\u201cI felt sick to my stomach,\u201d the student\u2019s mother told the Atlanta Journal-Constitution. \u201cI kept trying to tell myself that it was a student who had a crush on him, but when it came out that they smoked marijuana together, that\u2019s when I knew something inappropriate was going on.\u201d\n\n\u201cThis has destroyed my daughter,\u201d she added.\n\nCompton was booked into the Henry County Jail on April 8, where he remains as of April 10.\n\nHis arrest comes just a month after 27-year-old Brittany Zamora, a teacher at Las Brisas Academy Elementary School in El Paso, Texas, was arrested and charged with three counts of sexual assault of a child and three counts of improper relationship with a student.\n\nZamora is accused of having a sexual relationship with an eighth-grade student, who told police that she and Zamora had kissed on two occasions, and that Zamora had touched her breast on another occasion.\n\nAccording to police, Zamora also admitted to having had sex with the student on a bed in her apartment, but claims the student was the one who initiated it.\n\n\u201cThe child told her that she wanted to have sex with her, and she knew it was wrong, but did it anyway,\u201d El Paso police said in a press release, adding that Zamora later admitted to exchanging inappropriate texts with the student.\n\nZamora is currently out on bond, and has been placed on paid administrative leave.]" time="0.424"><properties><property name="score" value="0.005067749" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00506775 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00506775
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Private Jets for Sale\n\nShare this:\n\nTweet\n\n\nEmail\n\n\nBuying a private jet may sound like an unattainable dream, but there are companies that specialize in selling pre-owned aircrafts. However, it is important to be aware of the potential risk factors when buying a private plane.\n\nThere are many buyers who believe that when they buy a pre-owned aircraft, they are getting a good deal on a well-maintained plane. But this may not always be the case. Some buyers may not realize that it is not always easy to find out the history of an aircraft, and if the aircraft was properly maintained.\n\nAt Private Jet Brokers, we will provide a comprehensive report on the pre-owned aircraft you are interested in, and provide the opportunity for an inspection by a qualified maintenance professional. If you decide to buy a pre-owned aircraft, we will help you with the following:\n\nBuying and selling pre-owned aircraft\n\nMaking an offer on a pre-owned aircraft\n\nArranging for maintenance inspections\n\nHull and maintenance inspections\n\nApproved direct entry and approval of the inspections\n\nIf you are considering purchasing a pre-owned aircraft, please contact us today at 888-659-4440 or info@privatejetbrokers.com.]" time="0.373"><properties><property name="score" value="0.19480485" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[If you've never used Redis, it is an open source, in-memory, key-value datastore. It can be thought of as a huge hashmap, with the ability to do a variety of different operations in an atomic fashion. One of the most common use cases for Redis is a LRU cache. In this post I'll describe the inner workings of the LRU algorithm in Redis, and how to use it effectively to speed up your applications.\n\nRedis and LRU\n\nRedis has a variety of different datatypes that you can store in a key. You can store a string, a list, a hash, a set, and even more exotic types like geospatial indexes and pub/sub channels.\n\nThe most common datatype you'll use in Redis is the hash, which is just a set of strings, stored under a single key. You'll also use the string type to store a variety of things, including session ids, and passwords.\n\nOne thing that you can do with a hash in Redis is use it as a cache. If you want to store a large dataset in memory, but want to do it with a very small footprint, you can use Redis as a hash-based cache.\n\nThe implementation of the LRU algorithm in Redis is more than just a simple feature, it is also the method that allows Redis to work as a cache. The LRU algorithm allows Redis to store your data in a very compact way, while also keeping it easily accessible.\n\nA Simple Example\n\nSuppose you have an application that stores a hash map of users, and each user has a name and a list of sessions. A session is just a string that represents an entry in the cache.\n\nIf we want to write the number of users in a session to the console, we can do something like this:\n\nIn redis-cli , type smembers *:user_name* , where user_name is the name of the user in the hash. This will return a list of sessions in this user's hash. Type smembers *:sessions* , where sessions is the key we used to store the sessions. This will return the number of sessions that we had in step 2.\n\nAs a quick note, in this example I am using "*" as a wildcard, this is done because I am not guaranteed that my keys have any characters after the colon.\n\nThis is the simplest example, but it works well to show how to use the Redis LRU algorithm to your advantage.\n\nIf you have a hash where each element represents a cached entry, your application is running well if each time you query the hash, the number of elements that you get is exactly the number of times you are using the hash in your application.\n\nTo explain why this is, let's do a simple analysis of a few different cases.\n\nImagine that the user "John Smith" has a hash, where each key is a session, and each value is a timestamp.\n\nIf we have 50 sessions for user John Smith, and we are querying the hash once per second, it should return the same number of elements every time.\n\nIf we have 50 sessions for user John Smith, and we are querying the hash once per second, it should return the same number of elements every time. If we have 10 sessions for user John Smith, and we are querying the hash once per second, it should return exactly 10 elements every time.\n\nIf we have 10 sessions for user John Smith, and we are querying the hash once per second, it should return exactly 10 elements every time. If we have 5 sessions for user John Smith, and we are querying the hash once per second, it should return either 5 or 6 elements every time, depending on whether the hash was queried during the first or second query.\n\nThis simple example is sufficient to show that the number of queries that are made to the cache are more important than the average number of items returned.\n\nThe number of times you query your cache is directly related to the amount of work your application is doing. If you have a lot of work to do, your application will make more queries to your cache. The way we can use this is by tuning the value of our cache to be more or less aggressive.\n\nThere are a few things that you can change to influence the aggressiveness of your cache. These are listed below.\n\nsize of the hash. How many elements the hash can have before we start dropping items.\n\nmax number of keys that can be in the hash\n\nmax number of elements per key that can be in the hash\n\nHere is an example that demonstrates how to increase the aggressiveness of a hash:\n\nredis> set maxmemory-policy volatile-lru maxmemory-samples 5 redis> set maxmemory-policy volatile-lru maxmemory-expand on\n\nIf you run the same example as above, and then run the two commands above, you will see a noticeable change. If you have a small hash, the new settings will be a dramatic change, if you have a large hash, the impact will be small.\n\nWhen using a hash, the number of elements per key is the key factor in determining the effectiveness of the LRU]" time="0.350"><properties><property name="score" value="0.0034017302" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A band of killer whales was spotted today off the coast of Victoria, British Columbia, with a mystery creature they had killed and were feeding on.\n\nThe encounter, which was captured by boaters on video, was "not common at all," naturalist David Ellifrit told ABC News.\n\n"They do feed on other animals, but it's generally much larger things," he said, estimating the creature was about 20 feet long. "The fact that the whales killed this animal and are feeding on it is really quite unique."\n\nThe 15-member orca pod was spotted at around 2 p.m. about a half mile offshore of Race Rocks, an area of islands and rocks off the southwest coast of Vancouver Island, British Columbia, Ellifrit said. The mammals were hunting a giant squid.\n\n"They've killed it, but they haven't finished feeding yet," he said, adding that he's never seen anything like it in his three decades of experience in the area.\n\nWhile most people think of killer whales eating fish, Ellifrit explained that the mammals are carnivorous and eat marine mammals like seals and other sea creatures like sea lions and large sharks.\n\nCourtesy OrcaLab\n\n"They're really, really fascinating," he said of killer whales. "They're very special animals."\n\nEllifrit said it's impossible to tell from the video if the mysterious animal was a shark or some other sea creature.\n\n"It was clearly dead," he said. "They're playing with it."\n\nHe added that the pod of orcas could have been feeding on the creature for a couple of hours.\n\nCourtesy OrcaLab\n\n"It was moving through the water really, really quickly," he said. "It's probably a shark."\n\nEllifrit noted that this particular orca pod, known as the southern resident killer whales, live in the waters around Vancouver Island and have become a tourist attraction.\n\n"They're one of the stars of the show here," he said.\n\nThe creatures were nearly extinct by the late 1960s, but were saved by a captive breeding program. They are now protected in Canada, and considered an endangered species in the United States.]" time="0.304"><properties><property name="score" value="0.39956653" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The former head of the Democratic National Committee has a new role: commentator for the pro-Russia network RT.\n\nDonna Brazile\u2019s contract with CNN was suspended last year after it was revealed that she shared debate questions with the Clinton campaign during the primaries. Now, she will make regular appearances on the Russian-government-funded media outlet.\n\nShe will be a contributor for the channel\u2019s \u201cPolitical Gabfest\u201d program, according to a press release sent out Tuesday by the network.\n\n\u201cThe most exciting part of joining the \u2018Political Gabfest\u2019 is that I will be back in action on the campaign trail! I am eager to talk about the 2020 election and the road ahead for all of us,\u201d Brazile said in a statement.\n\nBrazile is no stranger to controversy: In 2017, she published a book, Hacks, which included passages that some say contradicted her earlier denials about sharing the debate questions.\n\nIn her new role, Brazile will appear alongside former NPR program hosts (and brothers) John and Jon Ganzfried. The two work on RT under the name \u201cThe Gentlemen,\u201d hosting the program \u201cThe Big Picture.\u201d\n\n\u201cOur show is about \u2018the big picture\u2019 issues facing America and the world, and how the decisions made by our government leaders both affect our daily lives and shape our nation\u2019s future,\u201d the brothers said in a statement. \u201cWe look forward to our spirited conversations with Donna, as well as her take on the most pressing issues of the day.\u201d\n\nAs head of the DNC, Brazile gave the Clinton campaign a heads up on questions to expect during the primary debate against Bernie Sanders. In the book, she said she \u201cwondered\u201d whether she should give the Clinton team a heads up about the questions for the general election debates, but did not ultimately do so.\n\nRT\u2019s founders and owners have direct ties to the Kremlin, and its funding comes from the Russian government.\n\nIn an interview with Variety, the brothers defended their role on RT, saying that they \u201cweren\u2019t trying to accomplish anything\u201d by appearing on the network.\n\n\u201cThe network is no different from other networks, it\u2019s just like CNN, MSNBC, or Fox,\u201d said John Ganzfried.\n\n\u201cThe only difference is that they were more truthful about what they are. We are trying to be honest about what we are and that\u2019s it.\u201d\n\nHe added: \u201cWe have a lot of freedoms over here to do what we want, and the contracts we have over here are very fair.\u201d\n\nRT has been the subject of criticism over its coverage of U.S. politics.\n\nIn one of the most high-profile incidents, RT was forced to register as a foreign agent under the Foreign Agents Registration Act. The channel is now required to include disclaimers at the bottom of its broadcasts saying that it is funded by the Russian government.\n\nWATCH:\n\nFollow Chuck on Twitter\n\nFreedom of Speech Isn\u2019t Free\n\nThe Daily Caller News Foundation is working hard to balance out the biased American media. For as little as $3, you can help us. Make a one-time donation to support the quality, independent journalism of TheDCNF. We\u2019re not dependent on commercial or political support and we do not accept any government funding.\n\nContent created by The Daily Caller News Foundation is available without charge to any eligible news publisher that can provide a large audience. For licensing opportunities of our original content, please contact licensing@dailycallernewsfoundation.org.]" time="0.303"><properties><property name="score" value="0.0005435153" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00054352 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00054352
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[WASHINGTON (Reuters) - U.S. Secretary of State Rex Tillerson said on Sunday that the U.S. government was looking into whether any former or serving Russian intelligence officials were linked to the authorship of recent hacking attacks, but declined to comment further.\n\nThe U.S. government last week formally accused Russia for the first time of a campaign of cyber attacks against Democratic Party organizations ahead of the Nov. 8 presidential election.\n\n"Well, I'm not going to tell you we have it all tied up with a bow, because we do not have it tied up with a bow," Tillerson said in an interview on "Fox News Sunday," asked whether Russia was responsible for the cyber attacks.\n\n"But I will say this: We know that part of our challenge is in the cyber realm."\n\nU.S. intelligence agencies have concluded that Russian President Vladimir Putin directed a covert effort through hacking and propaganda to try to tilt the election in favor of Republican Donald Trump.\n\nRussia has denied any such activity.\n\nU.S. Democratic Senator Chuck Schumer, the incoming Senate Democratic leader, said on ABC's "This Week" program that he expected the U.S. Congress would investigate whether Russia used hacking to influence the election.\n\n"We are more and more focused on getting to the bottom of this," said Schumer, adding it was "odd" Trump was not talking more about allegations of Russian hacking.\n\n"I think we could do better on that, because this is pretty serious," Schumer said.\n\n'MORE ACCURATE'\n\nAsked on CBS' "Face the Nation" whether he thought the election was "free and fair from a cybersecurity perspective," Tillerson said, "Well, I don't think there's any question that the Russians were playing around in our electoral processes."\n\n"I think the question is, is it incontrovertible, and can we prove in a court of law, that Russia is responsible for how our elections turned out?" Tillerson said.\n\nOn NBC's "Meet the Press," he called allegations that Russia interfered in the U.S. election "very troubling" and said they were already "being looked at."\n\n"But we also, I think, need to be very clear that we can't allow some foreign government to come in, particularly one like Russia, and interfere, how elections are going to be carried out in the United States or any other country," he said.\n\nU.S. President-elect Donald Trump, a Republican, has said the focus on Russia's alleged hacking campaign is a "political witch hunt" by his opponents.\n\nRussian officials, including Putin, have repeatedly denied that Russia tried to influence the U.S. presidential election.\n\nTillerson also took a swipe at Trump for comparing U.S. intelligence agencies to Nazi Germany in dismissing reports Russia had compiled compromising information on Trump.\n\n"Those kind of comments are obviously ... unnecessary, and frankly, I think, damaging to our intelligence officers," Tillerson]" time="0.396"><properties><property name="score" value="0.087104514" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08710451 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08710451
|
||
assert 'Human' == 'AI'
|
||
- AI
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||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[O t\xe9cnico do Corinthians Tite espera um Corinthians equilibrado e capaz de buscar o resultado no jogo contra o Ferrovi\xe1rio, no N\xedlton Santos, pela primeira fase da Copa do Brasil. O treinador lamentou o estado f\xedsico dos jogadores do Tim\xe3o, que perderam os \xfaltimos dois jogos do Brasileiro por 1 a 0 para o Gr\xeamio e 4 a 1 para o Atl\xe9tico-MG.\n\n"Eu espero um jogo de equil\xedbrio, o que significa que o Corinthians tem de se equilibrar no que sabe fazer. O time joga e busca, mas isso deu certo ou errado depende do jogo. Agora, o que se espera \xe9 um equil\xedbrio", disse.\n\nA situa\xe7\xe3o do Corinthians ainda \xe9 pior. O clube precisa vencer por pelo menos cinco gols de diferen\xe7a para avan\xe7ar \xe0 pr\xf3xima fase. Isso porque no jogo da estreia, contra o Boca Juniors, em Buenos Aires, os gols marcados foram expuls\xf5es e s\xf3 foram marcados em cobran\xe7as de falta.\n\nO t\xe9cnico alvinegro, no entanto, n\xe3o v\xea o Corinthians como candidato \xe0 elimina\xe7\xe3o e acredita na classifica\xe7\xe3o. "Acho que n\xe3o h\xe1 nenhum candidato. Mas a chance de o Corinthians passar \xe9 bastante forte", afirmou.\n\nTite se disse impressionado com a campanha do Ferrovi\xe1rio e com a torcida, que cercou a concentra\xe7\xe3o do Corinthians na tarde desta ter\xe7a-feira. Para o t\xe9cnico, a participa\xe7\xe3o do clube na Copa do Brasil \xe9 um orgulho, e a torcida, um motivo a mais para as vit\xf3rias. "O grupo n\xe3o deve esperar nenhum favor. Que tenha respeito pelo advers\xe1rio, pelos torcedores do Ferrovi\xe1rio e por quem nos recebe com uma grande expectativa. \xc9 um clube que est\xe1 no caminho certo e tem tudo para melhorar ainda mais", declarou.\n\nSem Copa do Brasil, Corinthians j\xe1 pensa no Brasileiro\n\nO t\xe9cnico F\xe1bio Carille comandar\xe1 o Corinthians no cl\xe1ssico contra o Santos, no domingo, na Vila Belmiro, pela 32\xaa rodada do Campeonato Brasileiro. O treinador n\xe3o descarta a possibilidade de escalar o time que vai enfrentar o Ferrovi\xe1rio, pela Copa do Brasil. "Eu vou jogar contra o Santos um time que eu acho que a torcida vai gostar de ver", disse.\n\nCarille garantiu ainda que todos os jogadores ter\xe3o oportunidade de mostrar servi\xe7o na Copa do Brasil. "N\xe3o estamos dando desculpas, vamos usar todo o nosso elenco. Vamos escolher os 11, mas n\xe3o estamos jogando um jogo para eliminar ningu\xe9m. Todos t\xeam condi\xe7\xf5es de fazer uma boa partida", disse.\n\nO Corinthians ainda tem mais duas partidas pela fase de grupos da Copa do Brasil. Ap\xf3s o duelo diante do Ferrovi\xe1rio, a equipe encara o Londrina, no dia 20 de setembro, no pr\xf3ximo domingo.]" time="0.468"><properties><property name="score" value="0.18590073" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Paul Kimmage has been acquitted of defamation by a Jury in the High Court in Dublin, after the long awaited trial was settled just hours after it started on Monday.\n\nPaul Kimmage has been acquitted of defamation by a Jury in the High Court in Dublin, after the long awaited trial was settled just hours after it started on Monday.\n\nKimmage, a journalist, who is best known for his three books on the Tour de France and for his work on RTE's Sunday Independent column, will walk away with costs after this costly case was settled out of court in such a short space of time.\n\nWhile RTE, the employer of television commentator Pat Kenny, whose Sunday Independent column Kimmage wrote between 2002 and 2005, did not have to pay a penny in legal costs as a result of the verdict, Kimmage must have been left wondering how he could lose the case after a long trial and having been supported by the "best defamation solicitor in Ireland".\n\nKimmage claimed that Kenny had deliberately tried to block his column from appearing in the newspaper, and this eventually led to him leaving his post as a columnist.\n\nAccording to Kimmage, Kenny had never made a secret of the fact that he disagreed with his stance on doping, but was able to do this while at the same time exercising his editorial control over the contents of the column.\n\nThe case was finally concluded yesterday, after being delayed twice, firstly due to Kenny's television schedule and then when Kenny was injured in a fall.\n\nKimmage's legal team had the chance to argue Kenny had defamed their client by stating in the Sunday Independent, in September of 2002, that he was anti-drugs and that his presence on the paper would undermine his credibility.\n\nA retraction of this statement was ordered by the newspaper, but only after a lengthy legal battle.\n\nThis defamation action was settled at the start of last month, while the case was being adjourned to hear Mr Kenny's evidence.\n\nKimmage's solicitor, Brian O'Moore, said that the apology was made in the public interest and a balance was achieved in terms of protecting Kenny's right to free speech and his right to a fair trial.\n\nHe said the apology had restored Paul's reputation.\n\nKimmage said at the time that the case had left him exhausted and had placed a strain on his family and his finances.\n\nKenny was not in court on Monday to give evidence, and the judge told the jury that he could not be compelled to give evidence.\n\nKenny is to broadcast his show on Today FM on Tuesday evening, and when asked about his absence from court, said: "I was in the hospital at the time."\n\nIn his opening address, the counsel for Kimmage said that Kenny's actions were "highly unprofessional".\n\nKenny was advised by his counsel not to answer any questions.\n\nKimmage told the court: "This is not about trying to upset or damage Pat Kenny. It's not about doing anything other than restoring my reputation."\n\nKimmage said he had been "decimated by the actions of Pat Kenny" and that his financial position had been "wiped out" because of the actions of Kenny.\n\n"I have been left in financial and emotional ruins," he said.\n\nHe claimed he had received a message from Kenny after leaving the paper that he had "betrayed the Sunday Independent" and that he was "going to take him to the cleaners".\n\nThe editor of the Sunday Independent said Kimmage's credibility was in question and that he was no longer a columnist that the newspaper could rely on.\n\nDenis O'Brien, the chairman of Communicorp, the parent company of the Sunday Independent, said that he was disappointed with the loss of Kimmage's column but he did not feel that his reputation had been damaged.\n\nBelfast Telegraph]" time="0.526"><properties><property name="score" value="0.050155714" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05015571 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.05015571
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[for a lot of reasons. To start, it's the latest blow to the administration's credibility after a litany of controversies, including reports that Trump's campaign aides were in constant communication with Russian intelligence officials during the election.\n\nBut it also illustrates the confusion and infighting that has defined the Trump White House.\n\n"The problem is that, given all the chaos and competing power centers in the White House, it's not clear who is really running the show at any given time," said Ben Rhodes, a former senior foreign policy official under President Barack Obama. "That makes it hard for the administration to have the kind of coherence it needs to conduct a well-organized foreign policy."\n\nFlynn's resignation followed a series of damaging leaks about the president's senior staff and other high-ranking administration officials.\n\nNational security adviser Flynn denied discussing sanctions with Russian envoy\n\nA report published Monday night said top Trump aides, including chief of staff Reince Priebus, White House counsel Don McGahn and press secretary Sean Spicer, kept Trump in the dark about Flynn's conversations with Russian ambassador Sergey Kislyak in order to "protect the president from himself."\n\nIn mid-January, the administration told the Washington Post that Flynn did not discuss the sanctions that the Obama administration imposed on Russia for meddling in the US election. Those sanctions were expected to be a topic of conversation between Flynn and Kislyak, but Pence and other senior officials, including McGahn, were apparently kept out of the loop about what exactly Flynn and Kislyak discussed.\n\nTwo sources familiar with the conversations between Flynn and Kislyak told The Post that Flynn's communications were "incidentally collected" as part of a top-secret intelligence report on Kislyak. After they reviewed the report, which has since been shared with Obama and Trump, McGahn and others acted quickly to warn Trump's senior staff about what they saw.\n\nMcGahn told Trump that Flynn's communications may have violated an obscure US law that forbids private citizens from negotiating with foreign governments against US interests, according to a separate Washington Post report on Tuesday.\n\nIt's not yet clear why Flynn, who was appointed as national security adviser with little experience in international relations, was having those conversations in the first place.\n\nSince the Trump campaign, Flynn has reportedly developed close ties with top officials in Russia, including Russian President Vladimir Putin, and has been paid tens of thousands of dollars in fees by Russian companies.\n\nBut Flynn's resignation on Monday came amid a broader debate over Trump's ties to Russia, and it adds to a cloud of controversy around Trump's own attitude toward Russian meddling in the election. Trump has insisted on several occasions that the intelligence community has not reached a conclusion about whether Russian hackers sought to boost Trump's campaign, even though the intelligence community has reported the consensus view that it was Russia.\n\nDemocrats, in particular, have been vocally critical of Flynn's conversations, and of Trump's defense of Flynn.\n\n"The speed at which we're learning about all of this is absolutely breathtaking," Rep. Adam Schiff, the top Democrat on the House Intelligence Committee, said Monday. "I think we ought to slow down."\n\n"You can't have a national security adviser misleading the vice president and others," said Sen. Richard Blumenthal, a Connecticut Democrat. "This in the wake of what we know about Russian hacking and election interference. It is of profound concern, and there is a need for a serious and thorough investigation."\n\nBut Trump has yet to provide any details about what he believes Flynn discussed with Kislyak.\n\n"I don't think he did anything wrong. If anything, he did something right," Trump said on Wednesday. "He was just doing his job. The thing is he didn't tell our vice president properly, and then he said he didn't remember. So either way, it wasn't very satisfactory to me."\n\nWhat is the Logan Act?\n\nIn an interview on Monday, Flynn's lawyer, Robert Kelner, said that Flynn did not discuss sanctions with Kislyak, and that he did not recall discussing the US's decision to expel Russian diplomats from the US in retaliation for the election-related hacking.\n\nWhen The Post first reported on Flynn's conversations in February, White House press secretary Sean Spicer said that Flynn had spoken to Kislyak on December 28, the day the Obama administration announced sanctions against Russia for election-related hacking. The sanctions were imposed in response to Russian President Vladimir Putin's decision not to retaliate after the US expelled 35 Russian diplomats and shuttered two Russian facilities in the US in response to the hacking of US political organizations and leaking sensitive information to WikiLeaks.\n\nBut Spicer later walked back that statement, saying that Flynn and Kislyak may have had a conversation, but that it was "not a discussion of sanctions."\n\nThe Department of Justice informed the White House counsel on January 26 that Flynn was not entirely forthcoming about his conversations with Kislyak, according to The Post's first report. A day later, Pence learned that Flynn's conversations may have broken the law and expressed his concerns to Flynn, who assured him they did not.\n\nThe White House said in a statement last week that it had "no idea" about the true nature of the Flynn-Kislyak conversations, but the Post's report on Tuesday said that Trump knew Flynn misled Pence about their contents. Trump did not ask Flynn about it, however, until the Monday before he was fired, the report said.\n\nA person close to the White House told The Post that White House officials were "stunned" to learn how far along the Justice Department investigation was.\n\nAfter The Post's report on Tuesday, which said that Trump had known about Flynn's conversations since January 26, White House counselor Kellyanne Conway told CNN that Flynn had Trump's "full confidence."\n\nBut Flynn resigned after a new report published Tuesday night said that the Justice Department had informed the White House that Flynn could be subject to blackmail because of his false statements about his conversations.\n\nFlynn has emerged as a key figure in the ongoing investigations into the Trump campaign's ties to Russia, but until recently, the investigation into his activities was limited to whether he had violated federal law by failing to properly disclose payments from Russia and Turkey.\n\nThe federal law that prohibits US citizens from negotiating with foreign governments against US interests, known as the Logan Act, is rarely enforced, but Flynn's conversations with Kislyak could have put him in violation.\n\nThe Logan Act was passed in 1799 to prevent citizens from trying to influence US foreign policy by making private deals with foreign governments. Only two people have been prosecuted under the act: in 1803, when a Kentucky farmer wrote a newspaper article in which he called on Americans to refuse to buy British goods, and in 1852, when an Indiana farmer tried to help Mexican Americans recover lost land after the Mexican-American War. Neither were convicted.\n\nWhen asked about the Logan Act in March, White House press secretary Sean Spicer said it was a "silly" law.\n\n"I don't know what the intent was of the Logan Act, but the law is a little bit silly and a little outdated," he said. "I'd say that his actions -- not just the reporting of the incident -- but also the following day, Flynn made clear that it was inaccurate."\n\nBut one of the US's top legal experts on the Logan Act says that Flynn's actions may be illegal.\n\n"The issue is a very serious one," Stephen Vladeck, a professor of law at the University of Texas School of Law and a CNN contributor, told CNN on Tuesday. "This wasn't just a slip of the tongue. This wasn't just a statement to a reporter. This was something that, according to reports, he discussed with other senior Trump administration officials. It was something that the vice president of the United States apparently thought was serious enough to bring to the attention of the President himself.\n\n"It's not just about the Logan Act. It's about everything else that is swirling around this administration," Vladeck said. "If there is any evidence that the Trump campaign cooperated with Russian officials or representatives to help swing the election, then we have another entirely different kettle of fish on our hands."\n\nThis story has been updated.\n\nCNN's Dan Merica contributed to this report.]" time="0.700"><properties><property name="score" value="0.07545974966666666" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07545975 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07545975
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[John McCain's SON killed in plane crash at 31\n\nLiz Cheney Wants Trump to Toughen US Policy on Russia\n\nClinton, Trump top 3 of their most 'toxic' tweets, from Howard Dean\n\nHoward Dean: 'I don't think Hillary has the stamina'\n\nObama: No guarantee ISIS can be destroyed, but "we will destroy them"\n\nChristie's possible VP options, plus how he could make them pay\n\nHillary: I'm most 'prepared' to be POTUS ever, GOP are 'dead wrong'\n\nJohn Kasich: I'm staying in the race because I'm the best candidate\n\nSanders wins Wyoming, but not enough to stop Clinton's path to nomination\n\nGeorge W. Bush warns of 'isolationism,' 'protectionism' in GOP\n\nElizabeth Warren: I'm no 'cheerleader' for big banks\n\nTrump claims that Iran is 'trying to take over the world'\n\nDonald Trump: 'Who's going to pay for the wall?'\n\nTrump takes off on Clinton: "She's no friend of women"\n\nObama hits Trump: Is he being 'silly' or does he not know what he's talking about?\n\nClinton camp: Trump has 'laid bare' his strategy with GOP elites\n\nEx-KKK leader David Duke launches his Senate campaign\n\nClinton: US, Japan must "face" North Korea threat\n\nTrump: I won't be 'embarrassed' if GOP doesn't back me\n\nTrump: Iran deal a "horrible, horrible embarrassment"\n\nTrump: 'Weak' politicians let US manufacturing get ripped off\n\nFox News Poll: Trump wins GOP race, faces headwinds in general election\n\nJohn Kasich: Voters are sending the GOP a message\n\nMichelle Obama gets real on race, a surprise marriage and her legacy\n\nTrump defends Muslim ban, gives reasons why it 'hasn't gotten enough publicity'\n\nNorth Carolina rep. on the Democratic convention: 'We are always underestimated'\n\nTrump at odds with GOP over his Muslim ban, and who 'made' him disavow Duke\n\nGingrich defends Trump on Muslim ban: 'Should we pass judgment on every Muslim?'\n\nTrump denies criticism of Muslim plan coming from top GOPers\n\nRomney launches scathing anti-Trump speech\n\n'People want him to say what he means': Chuck Todd on Trump's anti-GOP message\n\nClinton says Republicans' problem is with Trump, not the rest of us\n\nPro-Hillary Clinton super PAC comes after Trump's 'thin skin'\n\nTed Cruz: Donald Trump and Hillary Clinton 'could switch places'\n\nClinton: Trump 'tried to get a scam university' and 'there's so much more'\n\nObama jokes that he 'didn't have scandals' like Trump has\n\nGeorge W. Bush: 'I am not a scientist'\n\nTrump stands by Muslim plan, even as GOP leaders condemn\n\nTrump: I'm not apologetic for Muslim ban, even if world thinks it's 'silly'\n\nDonald Trump: Hillary Clinton is playing the 'women's card'\n\nHillary Clinton: Trump's comments are 'not at all funny'\n\nClinton: Trump's Muslim comments are 'shocking and dangerous'\n\nTrump: Muslim ban call 'just a suggestion'\n\nTrump: NATO has gotten 'worse' and 'we need to change'\n\nTrump: We are losing to China 'like never before'\n\nTrump: Bernie Sanders is a hypocrite\n\nTrump: 'Little' Marco Rubio should stop 'glamorizing gang violence'\n\nDonald Trump on Ted Cruz: He's the 'biggest liar' I've ever seen\n\nDonald Trump: Hillary Clinton 'would be a terrible president'\n\nDonald Trump: 'This country is going to hell'\n\nTrump calls Obama 'the worst thing to happen to Israel'\n\nSanders 'surprised' by Democrats calling him out\n\nThe GOP's case for Donald Trump\n\nDonald Trump: Ted Cruz a 'total liar'\n\nWhat a GOP convention would look like with Donald Trump\n\nTrump: I think Obama's behind protests, 'maybe Hillary' too\n\nTrump: Republicans could do better with women\n\nDonald Trump's top quotes of the year\n\nTrump: I was against the Iraq war from the beginning\n\nClinton: Trump would be dangerous 'even if there weren't a war'\n\nClinton: I would put my Wall Street plan in place immediately\n\nClinton: GOP candidates don't agree with the Republican platform\n\nTrump: GOP's abortion plank is the 'most extreme' in party history\n\nTrump on the GOP's 'weak' abortion plank\n\nClinton: I don't think GOP agrees with its own plan\n\nClinton: A Trump victory would be 'scary'\n\nDonald Trump on Ted Cruz's conservative views\n\nClinton on GOP: They are 'out of touch'\n\nCruz: I'm 'surprised' Hillary Clinton agrees with my health care stance\n\nObama jokes that Biden has a Twitter account\n\nTrump: I'd rather run against Hillary Clinton\n\nTrump: My sons love the fact that I'm running\n\nDonald Trump on foreign policy: 'I feel I'm qualified'\n\nDonald Trump: 'Iran is taking over Iraq'\n\nCruz on White House contender Fiorina: 'Her record is troubling'\n\nTrump, Clinton are 'a disaster,' Carson says\n\nTrump: I will beat Hillary, win border wall funding\n\nRubio on Cruz: I ran a campaign, he's 'run a movement'\n\nDonald Trump on Hillary Clinton: 'She's got nothing else to offer'\n\nTrump: Clinton wants to get rid of guns, so does Sanders\n\nHuckabee on SCOTUS immigration decision: It's a 'dagger to the heart'\n\nTrump: I will win all the debates\n\nTrump: Cruz is the only one who can beat me\n\nTrump, Clinton won't rule out possibility of speaking at same convention\n\nTrump: GOP rivals 'should have been rougher' on 'weak' Obama\n\nTrump: Jeb Bush's policies 'killed' brother's chances\n\nTed Cruz to Donald Trump: 'I'm the only one who's beaten you'\n\nBen Carson on businesses shutting down: 'We don't need government'\n\nTrump: Rubio is a 'nervous Nellie'\n\nDonald Trump: I'm not sure I want Jeb Bush's endorsement\n\nTrump: I don't care about Chris Christie's Bridgegate scandal\n\nTrump: If I'm elected, Hillary Clinton will 'be in jail'\n\nTrump: I will be a 'unifier' for the Republican Party\n\nTrump: My supporters will 'revolt' if I'm denied nomination\n\nTrump: I'm a 'unifier' who can reach out to all people\n\nJohn Kasich: I'd welcome Chris Christie's endorsement\n\nTrump blasts Bush, Clinton, Democratic leaders\n\nTrump: 'We are letting people come into our country who are no different than ISIS'\n\nTed Cruz to Donald Trump: 'I'm a maniac, and everyone on this stage is stupid'\n\nCarson: Age difference with Clinton 'doesn't matter'\n\nJeb Bush: Trump is 'getting kind of tired'\n\nTrump: Bush's 'policy did not work' for his brother\n\nCruz on Obama's Iran comments: 'They will never apologize'\n\nTed Cruz: 'There will be pitchforks and torches' if GOP passes immigration reform\n\nChris Christie: Obama doesn't understand 'how many Americans are out of work'\n\nCruz: I'll go 'toe-to-toe' with Democrats\n\nTed Cruz on Supreme Court: 'We're one justice away'\n\nTed Cruz: It's the Supreme Court, stupid\n\nMarco Rubio: Cruz's immigration stance 'is not the way to win an election'\n\nRubio on Obama's Iran deal: 'This president has the most dangerous foreign policy in America's history'\n\nTed Cruz: Iran deal is a 'disaster' for Middle East\n\nDonald Trump: Jeb Bush is 'totally in favor of Common Core'\n\nJeb Bush on Obama: He's 'made it harder to be successful as a small business'\n\nJeb Bush on GOP contenders: They should stop attacking each other\n\nTrump: I have a 'very great relationship' with God\n\nTed Cruz: I want to be 'singled out' for my conservative record\n\nJeb Bush: The 'right to rise is the most powerful force' in our society\n\nCarly Fiorina: 'Hillary Clinton lies about everything'\n\nTrump to Jeb Bush: 'You're a tough guy, Jeb'\n\nJeb Bush: 'I am my own man'\n\nCruz on Jeb Bush: 'I will always tell the truth'\n\nDonald Trump: Jeb Bush should 'speak English'\n\nJeb Bush: Donald Trump is a 'disaster'\n\nTrump: 'Jeb Bush is totally in favor of Common Core'\n\nDonald Trump slams Bush over immigration policy\n\nChris Christie on amnesty: 'People want to get to the facts'\n\nTed Cruz: 'It is not true' that I backed comprehensive immigration reform\n\nMarco Rubio: I was 'not talking about' citizenship in immigration plan\n\nJeb Bush on Obama: 'This presidency has been a failure'\n\nDonald Trump: Jeb Bush should 'say what he wants to say'\n\nDonald Trump: I won't 'pander' to Israel on settlements\n\nJeb Bush on Donald Trump: 'The man is delusional'\n\nTrump: I'm]" time="0.885"><properties><property name="score" value="0.0352857784" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03528578 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03528578
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Classical /C.S. - Posted: 09/10/2004 Why the hip-hop artist and the jazz composer both came to admire Liszt and Wagner\n\n\n\nCarl Czerny, the 19th century virtuoso who could do 100,000 scales in one session, wrote an excellent piece called 'School of Velocity'. And yes, it was about the velocity of execution - but there was a lot more to it.\n\n\n\nThe idea was that when you learned a piece you should practise it very slowly, in order to get the fingering, phrasing, pedalling etc right. But once you could play the piece perfectly slowly, you needed to practise it more quickly, in order to make sure you got the fingering, phrasing and pedalling absolutely perfect at the quicker speed.\n\n\n\nCzerny practised every day for hours, he wrote over two thousand pieces for piano (many are now completely forgotten) and he was a friend of Beethoven and of the pianist and composer Franz Liszt. The School of Velocity actually explains a lot about Czerny and Liszt's tastes in music. It wasn't so much about technique - though obviously they wanted music that was extremely difficult to play, and music that sounded good at every speed. But it was also about a music that is rhythmically and intellectually complex. Music that sounded fine, and was fascinating, at any speed.\n\n\n\nIn the 19th century, composers and performers used to refer to a piece that was difficult to play as being 'virtuoso' music. Today, people are much more likely to say that a piece is 'virtuoso' if the performer is a brilliant soloist. There was an important link between the two ideas, but there was also a big difference.\n\n\n\nA piece might be virtuoso in the sense that it was musically hard to play. But if a soloist could play the piece perfectly well, then there was nothing virtuosic about it at all. You could hear that it was musically good - but it wouldn't sound difficult.\n\n\n\nI remember a performance of Stravinsky's Rite of Spring that I saw in the early 1970s, when I was a teenager. It was performed by a major orchestra with some top conductors, and it was an extremely well-rehearsed performance. It was also a pretty stodgy performance - there was no electricity, and hardly any excitement. It was an impressive feat, but it was also dull. The most memorable thing about the performance was the way the audience reacted to it - the British critics, who thought they were being sophisticated, sneered and scoffed, and the audience members, who hadn't really understood what they had just seen, shouted and cheered.\n\n\n\nSo I know very well that a piece can be virtuoso in the sense that it is musically exciting - and yet it can also be virtuoso in the sense that it is technically extremely hard to play. I also know that the relationship between the two is not straightforward.\n\n\n\nA well-played piece can be musically exciting, and yet the performer can miss out on all the virtuoso bits - they can play it slowly, without pedalling, and without any expression, and without making any effort to bring out the music. If you think about it, that can't be right. If a piece is technically easy to play - and musically boring - then it isn't really a virtuoso piece. It may be musically good - but it's not virtuoso.\n\n\n\nThere is a lot more to virtuosity than just playing a piece well. And you can tell that from some of the best music ever written.\n\n\n\nSo Liszt and Czerny's criteria for virtuoso music aren't the same as the criteria for 'musical virtuoso' music. To them, it was also about a sense of musical excitement. It was about a piece that sounded good at any speed - and which sounded good whether you played it fast or slow. In the 19th century, that was what virtuosity was about.\n\n\n\nThat's why they liked Liszt and Wagner so much. And that's why I like them too.\n\n\n\n<< Music & Vision home A musician's life >>\n\n]" time="0.385"><properties><property name="score" value="0.10537536" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Himawari-8 is a Japanese geostationary weather satellite developed by the Japan Meteorological Agency (JMA). It is the second in the Himawari series of satellites, following Himawari-7 which launched in October 2013.\n\nLaunch and orbital configuration [ edit ]\n\nHimawari-8 was launched by Arianespace using an Ariane 5ES carrier rocket flying from ELA-3 at the Guiana Space Centre in Kourou, French Guiana. The launch occurred at 22:09 UTC on 2 October 2014, and marked Arianespace's sixth launch of the year and the second Ariane 5ES launch of the year.[3] It was the 70th Ariane 5 launch overall.\n\nThe satellite was built by Mitsubishi Electric, and is based on the DS-2000 satellite bus. It is equipped with two solar arrays, with a span of 33.9 metres (111 ft). It is expected to operate for ten years, although the JMA is required to maintain it for only five. It is expected to weigh approximately 2,800 kilograms (6,200 lb) at launch. The spacecraft was originally intended to be named Himawari 8, but was renamed before launch.\n\nIt was the third satellite to be launched for the second generation Himawari observation system. Himawari 8 and 9, along with the Himawari-7 satellite, will produce a continuous image of the Earth. A main difference from the first generation Himawari system is that the new satellites can scan the visible hemisphere with a 15-minute interval, allowing for more frequent observations and allowing meteorological phenomena to be analysed with greater speed and accuracy. Himawari-8 is positioned above the geostationary orbit at a longitude of 140\xb0 East.]" time="0.426"><properties><property name="score" value="0.14489809" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[BEST ANSWER\n\nOh wow, that is amazing! Thanks for sharing. My husband and I have talked about buying an old truck and refurbishing it. We are very practical people. So, with all of the families who need assistance with their old truck, this is a great idea! My husband does a lot of heavy construction work and we have seen old trucks that people have used as a source of income. My husband has thought about starting a truck repair business to take in used trucks. They do have to be restored a little bit, so he thought he could take some of the load off people and help them out with the money they need. He has thought about all of the used trucks that he sees in people's driveways and knows that they will never sell them because of how much work they are. We actually came across a pretty decent truck last weekend. The only thing wrong with it was that it had been used as a dump truck. It had a couple of huge dump bed holes in the bottom of it. We checked the engine and it runs good. We thought we could buy it and have it fixed up. It had low miles on it, so we thought it would be a good buy. I really thought my husband was going to buy it, but then he was thinking about all of the things that could go wrong with it. He would have had to drive it, so he was thinking about that. He also thought about all of the equipment and the backhoe and such that he would have had to buy if he bought it. My husband is a very smart man and he knew that it would be a lot of work, so we didn't even make an offer.\n\n\n\nI do know that I would love to find a nice truck and fix it up and then donate it to a needy family. I don't know what kind of license you need to operate a truck in your state, but I would like to look into that. I don't think we would charge for the use of the truck. I think we would just want the families to know that we would not be calling on them and checking up on them. I would want the truck to be used for transportation. We would probably work with a nonprofit, so that they would have to be approved to use the truck. That is the only way that I could think of to do it. We are very cautious about where we would donate the truck. My husband and I don't know how long we would have it. We would donate it for a specific time period. We are pretty smart people and we don't need the truck. We know that we would be able to get more than the price we paid for the truck out of it. We could use the money for other things that we are doing.\n\n\n\nMy husband has thought about finding a newer truck that doesn't need to be fixed up. He has thought about putting a little addition on the back to hold a bed. The bed would be the only part of the truck that needed to be fixed up. We have talked about taking this truck and fixing it up and then donating it. I am not sure how we would go about it though.\n\n\n\nThe truck that we saw last weekend is worth at least $3000.00. It has a V8 engine. It does need to be fixed up a little bit, but it is not worth that much money. We looked it up and it was only worth $2500.00. We could probably get it for $2000.00 if we fixed it up. It has not been registered in years, so we would have to get that straightened out. It has power windows, which is really neat. It has a sunroof. It is a really nice truck and it is in good condition. It is not the kind of truck that is really worth buying and fixing up. My husband thought that we could buy it, but I didn't want to go that far. My husband is not used to looking at vehicles like this. I know that he could use it for the business. My husband is a contractor, so he could use it to haul tools and such around.\n\n\n\nIf you can help us figure out what kind of license we need to operate the truck in our state, we would really appreciate it. I am going to look online and see if I can find something out. It would be a lot of work, but it would be worth it. We just don't want the families to take advantage of us. I don't know how we could help with that.\n\n\n\nWe would be willing to spend $500.00 on the truck. It needs some minor work. It is still a nice truck though. We thought we could add a dump bed to it. The bed is the only part that needs to be fixed up. It has a roll down door, so we could even use it to haul things around. It is a great truck.\n\n\n\nI would love to talk to you about this some more. My husband has already done a lot of the research on this. He thinks it would be a great project for us to take on. We have had a lot of health problems lately, so we have not had the time to really look into it.\n\n\n\nI really hope that you can help us. This is an exciting opportunity. I know that you will be able to help us figure out how to operate a truck in our state. I know that we will be able to get the license. We will probably need to get a company name, so that we can register the truck. We are looking forward to talking with you about this.\n\n\n\nSincerely,\n\nMary]" time="0.514"><properties><property name="score" value="0.0008264823" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This week, Leonie and Rachel are doing things they have not done before: reading a thriller with their daughters. While the girls are out of school, they take a break from picture books to read some chapters of THE SCIENCE OF HUGGING with their respective five and three year olds. With its lovely illustrations and captivating illustrations of animals, trees, insects, and a variety of other things, the book provides a great introduction to science.\n\nIt was an absolute joy to see the girls absorb the information, ask the right questions, and share their thoughts with their moms about what they were reading.\n\nTo learn more about the book, read on for our interview with the author, Johanna Kindvall.\n\nDid you have a childhood favorite book?\n\nAs a child, I loved the \u201cLittle House on the Prairie\u201d series by Laura Ingalls Wilder. I also loved the animal books by J.H.Hutchinson, such as \u201cAre you an Elephant?\u201d and \u201cAre you a Bear?\u201d\n\nWhat is your book about?\n\nIn this book, I show the science of hugging. Hugging is the act of embracing someone in a caring way. Hugging is a common way to express caring and affection. This book discusses many different types of hugging, from the ways that trees and flowers hug each other, to the ways that animals hug each other. I also discuss why we hug, how hugging can help our health, and the different feelings that we experience while we hug.\n\nTell us about a typical day in your writing life?\n\nI write every day. If I am not writing, I am thinking about writing. I have a lot of ideas for new books. I think about ideas and jot down notes. Sometimes I write at my computer, other times I write in my journal. I usually write from 8am-12pm, and then I go back to work.\n\nWhy did you write the book?\n\nI wanted to write a book about hugging. I was thinking about what kind of information about hugging would be most interesting to share with children, and I realized that we really do not know a lot about the science of hugging.\n\nDo you have an interesting story about writing the book?\n\nIt was so fun to illustrate this book, because I was able to illustrate a variety of different types of hugging. When I made the book I tried to hug a tree for the cover illustration. The hardest hug to illustrate was a bear hug. I had to really think about how I could draw a bear hug, and how I would express that the bear was hugging with his claws.\n\nWhat is your favorite part of the book?\n\nI love my cover illustration, because it shows so many different types of hugging. I also really like the science of hugging pages, because I was able to show the different ways that science can be used to understand hugs.\n\nWhat is your favorite picture in the book?\n\nI like the two pages that show how different types of hugging affect our bodies. I was able to illustrate the heart and lungs, and it was a lot of fun to make those illustrations.\n\nWhere can people purchase your book?\n\nThis book can be purchased on Amazon.\n\nWho is your favorite author?\n\nI really enjoy reading books by Linda Sue Park and Peter Brown.\n\nThanks to Johanna for sharing about her book.]" time="0.386"><properties><property name="score" value="0.15002033" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[View Full Version : one of the local clubs @ PATM\n\nshane diesel\n\nwell i am for the most part done with the patm club area that i am working on , with that said i decided to use some parts i have had and build a club one of the club i was with for 4 years http://www.southerntireburners.com/ not sure where they have landed but the other club i was with for 5 years http://www.snappin-turtle-customs.com/ i am still a member at snappin turtle customs so if ya'll ever come to central florida stop in and visit . here is a little something i built for them http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0318.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0321.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0320.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0323.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0322.jpg i know i am missing a few pictures , when i get a chance i will go back and get them , there are 2 if not 3 more boards that i built them also one is there snappin turtle one and the other is a walking turtle or should i say turtle that is walking\n\nhttp://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0325.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0326.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0327.jpg http://i535.photobucket.com/albums/ee351/jdmchristy072/custom%20rear%20toy/turtle/IMG_0328.jpg well i guess this will be the end of my building patm stuff if ya'll never know where patm is just remember it is between cleveland and detroit michigan . well have a great night or day]" time="1.441"><properties><property name="score" value="0.2090198" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[2 5 5 5\n\nCan't use in my kitchen- Need a work space I got this item as a gift and never really used it. It's a neat idea, but the fact is, in my kitchen, I don't have a place to keep the stand, and it has to stay there for it to work, so it's not an item that works in my kitchen. December 5, 2013\n\nUseful and easy to use! I bought this after I saw one of my friends using it in her kitchen and I was so intrigued. She raves about it and it looks like it's really going to be a useful tool for prepping all kinds of things! November 6, 2013\n\nInnovative and Easy I had the opportunity to use one of these at a friend's house and I thought it was great. I have only used it to cut up onions and garlic but it is so easy to set up and use. I am considering buying one for my house. November 5, 2013\n\nA lot of waste in the onion This works, but I find it a little flimsy. My main problem is that a lot of the onion gets wasted with the product. I don't understand how a blade so fine could leave so much in the onion. It is a nice design, though. October 31, 2013]" time="0.503"><properties><property name="score" value="1.1613116" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.1613116 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.1613116
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The ethos of the Linton Brook Trust is one of social inclusion and it is this very ethos that led to our collaboration with Artrix and the Festival of Baroque Music.\n\nAs the charity aims to \u2018support the life chances of young people and communities in the West Midlands\u2019, we worked with Artrix and the Festival of Baroque Music to enhance the experience of those that took part in a specific part of the music festival, which this year was Bach. The charity worked with Artrix to include a programme of interactive workshops that took place on the Friday of the festival. The workshops engaged in conversations about art, music and philosophy. They also introduced the young people to musicians and performers, who in turn shared their knowledge about their own experiences in music and how it has influenced their own journey.\n\nOne of the workshops encouraged the young people to experiment with a variety of instruments and create an original composition. Another workshop, which explored the different genres of classical music, demonstrated how the young people could use their creative thinking to connect with other styles of music. The young people also engaged in philosophical discussions about music and life. They learned about the difference between performing music and listening to music, and they discussed what a performance is.\n\nLinton Brook\u2019s involvement in the festival led to a strong working relationship with the festival organisers, who have expressed their interest in building a lasting relationship with the charity. This will mean Linton Brook can look at other ways it can collaborate with the festival to benefit more young people and their communities.\n\nFind out more about Linton Brook and the work that they do by visiting the website.]" time="0.489"><properties><property name="score" value="0.8374663" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8374663 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.8374663
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Stillwater is an American rock band formed in 1998 in New York City, New York.\n\nThe group consists of Austin Dickinson (lead vocals), Chris Guglielmo (guitar), Kyle O'Quin (keyboards), Grant Brinner (bass), Brian Southall (drums) and Ben Browning (guitar). Stillwater released their debut album, The Miners' Hymns, in 2002 on Broken Records, and have been signed to UK label Lojinx since 2012, with whom they released The Reigning Sound in 2013.\n\nThe band released their third album, Everything in Between, on April 22, 2015.\n\nHistory [ edit ]\n\nThe band's original members were childhood friends, brothers, and musicians Austin Dickinson (vocals/guitar) and Kyle O'Quin (guitar), along with friends Ryan Conlin (bass) and Jacob McDonald (drums), who met in middle school and later formed the band.[1] The band's name was conceived by Kyle O'Quin, who was in an experimental band called "The Womb" at the time and was reading the novel Stillwater Rising by John Stillwater.[2] The band name Stillwater was formed in reference to both the band Stillwater Rising and the fictional town Stillwater, Maryland. The band released its debut self-titled album Stillwater in 1999, and broke up soon after. The band reunited in 2004 and started playing a number of shows, and released the album The Miners' Hymns in 2002 on Broken Records.[3]\n\nStillwater was signed to UK label Lojinx in 2012, and released The Reigning Sound, which was the soundtrack to the documentary of the same name.[4] They then released The Songs of Paul Westerberg in]" time="0.404"><properties><property name="score" value="0.14244707" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The advisories issued by public health officials on Tuesday confirmed fears of some physicians and food safety advocates who have been sounding the alarm about the perils of romaine lettuce for months.\n\nThe US Centers for Disease Control and Prevention (CDC) issued a new warning Tuesday urging the public to avoid eating romaine lettuce amid a multi-state outbreak of E. coli infections.\n\n"We still have a lot to learn about this outbreak", he said.\n\nEarlier this month, the CDC announced an E. coli outbreak linked to romaine lettuce, including three deaths and 96 sickened individuals.\n\nHealth officials say consumers can not tell if a lettuce is contaminated just by looking at it, but some growers have voluntarily recalled romaine lettuce.\n\n"Illnesses started between November 15 and December 18".\n\nDr. Sarah Corry is with the Illinois Department of Public Health.\n\nHowever, Dr. Scott Gottlieb, the commissioner of the US Food and Drug Administration, said that since it was an active investigation, he could not comment on which states were affected or how much lettuce may have been involved. In the current outbreak, the strain of E. coli identified by the CDC as causing infections in both people and animals is a strain that produces a Shiga toxin known as STX2. In November, 19 people became ill in the USA and Canada.\n\nSo far, the CDC is not identifying a grower, supplier, distributor or brand that is linked to the outbreak.\n\nHealth officials have warned that the cases of E. coli may not be over, and people should still be on the lookout for symptoms.\n\nAlthough authorities have not pinpointed a specific grower, distributor or brand, the CDC has warned that all types of romaine lettuce should be avoided.\n\nOther advice includes properly washing and sanitizing produce to reduce the risk of illness.\n\nThe FDA is working with state and local officials and conducting inspections in the growing regions and in packing facilities to determine the source of contamination.\n\nSymptoms of E. coli can range from mild to severe, and usually appear within two to eight days of consuming the contaminated food.\n\nCases have been reported in Canada and 13 states. The patients have required hospitalization and one patient has died.\n\nPossible E. coli contamination in bagged and chopped romaine lettuce has sickened at least 15 people in NY and New Jersey, according to the CDC.\n\nThat's what can be expected in the aftermath of E. coli outbreaks that have been linked to fresh produce, says Lawrence Goodridge, director of the Washington State Department of Health's Communicable Disease Prevention and Control Program. "I think in some cases, if you don't have irrigation, you have to go through the issue of what's the most you can do".]" time="0.425"><properties><property name="score" value="0.03812076" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03812076 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03812076
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Gambling Behavior and Behavior Control\n\nby Barbara L. Milrod, Ph.D.\n\nRecreational gambling, especially casino gambling, is a growing and significant industry in the United States. A growing number of families engage in some form of gambling as a leisure activity. A sizeable number of families visit a casino at least once a year. Increasing numbers of families engage in forms of gambling that do not require visits to a casino, but do require some type of Internet or computer connection. Families that are not recreational gamblers are likely to include at least one person who is a gambler, a gambler who also functions in some other major role in the family, such as as a spouse, parent, sibling, or grandparent. Therefore, even if gambling is not a regular family leisure activity, it is a part of life for a significant number of families.\n\nGiven that, how does the gambling industry want the public to think about gambling and its impact on families? How should the public be thinking about it? What impact does it have on families? What are some of the causes and symptoms of gambling-related problems?\n\nThe 2005 National Gambling Impact Study Commission, the most recent of a series of gambling impact studies, reported that the number of people who engage in some form of gambling each year has increased since the last study. In the most recent study, it was estimated that approximately 21% of the adult population has engaged in some form of gambling at least once during the course of a year.\n\nThe study found that while the majority of the population gambles for entertainment purposes, a smaller but significant minority gambles for money and may be at risk for developing a gambling problem.\n\nThe study also reported that most people are either unaware of the nature of pathological gambling or misperceive its prevalence. A significant minority of the population does not believe that pathological gambling exists or that it exists only in a relatively small percentage of the population.\n\nEven in cases where the public recognizes that gambling is a problem for some, the impact of gambling on family members is often minimized. Therefore, the topic of gambling and its impact on family members has become a popular topic among researchers and is the subject of several studies.\n\nFor example, Blaszczynski and McConaghy reported that most of the relatives of pathological gamblers and problem gamblers had been affected by the gambling and had been directly affected by the adverse financial consequences.\n\nThey also reported that the relatives of pathological gamblers had significantly more dysfunction in their lives than the relatives of the problem gamblers. Additionally, they found that there was a significantly greater prevalence of gambling in the relatives of the pathological gamblers.\n\nWilliams and colleagues also reported that pathological gambling had a negative impact on the families of pathological gamblers. In that study, the spouses of the pathological gamblers were most likely to report problems in their marriage. These problems included financial difficulties, difficulties with communication, and issues with dealing with the gambling.\n\nGiven that, we might ask ourselves how does this impact families?\n\nIn terms of family interactions and dynamics, gambling can affect families in many ways. Family members may be affected in different ways. Family members may also be affected at different levels. For example, some family members may not be impacted very much at all. Others may be affected more severely. Family members may also be affected in a way that is either beneficial or detrimental. For example, they may be affected in a way that is not particularly harmful to them, but does cause harm to others.\n\nLet's examine the impact of gambling on family members in more detail. First, let's take a look at the general impact on family members.\n\nThe Impact of Gambling on Family Members\n\nSome of the impact on family members may be similar to the impact that other problem behaviors, such as substance abuse, have on families. However, some aspects of the impact are also unique to gambling. Let's take a look at both the similarities and the differences.\n\nGeneral Impact\n\nIn general, the effects of gambling on family members can be broadly categorized into four major areas: financial impact, emotional impact, environmental impact, and cultural impact. These areas, and the individual effects within each area, are described below.\n\nFinancial Impact\n\nMost families in the United States struggle with money issues at some time during the course of their lives. Financial concerns can affect a family's ability to deal with other problems. They can also cause problems in and of themselves.\n\nWhen financial concerns arise as a result of gambling, family members may need to sacrifice other financial needs to meet the demands of the gambler. For example, the gambler may require family members to fund a large portion of his or her gambling activities. This may require the family to make difficult decisions about which expenses to cut back on or to borrow money.\n\nFamilies may also face financial difficulties as a result of the gambling of a member. For example, if a family member incurs debts or otherwise incurs financial problems as a result of gambling, the other family members may need to cover his or her debts. This can be costly.\n\nCultural Impact\n\nGambling in America has a long history. This history has influenced American society and culture in many ways. One way it has influenced American society is through the creation of "gaming" communities. These communities, which are primarily located in the western part of the United States, are based on gambling.\n\nGambling as a cultural activity has evolved over time, and has become a part of our culture and entertainment culture. As a result, there is now a certain level of expectation in American culture about recreational gambling.\n\nEnvironmental Impact\n\nSome people believe that gambling in a casino is a more "safe" and "controlled" environment than recreational gambling in the home. While this may be true, there are some dangers to this type of environment. Casinos can sometimes be a location where crime and violence occur. Families who engage in this form of gambling, then, can be negatively impacted in a variety of ways by the environment in which they gamble.\n\nEmotional Impact\n\nEmotions play an important role in all aspects of life, including in families. The emotional impact of gambling is both obvious and subtle. It is both dramatic and subtle. Families and family members may react emotionally to the gambling of a family member.\n\nFamilies may also react emotionally in response to a gambling-related problem. Some family members may respond with fear or anxiety about the problem. Others may respond with shame, guilt, or embarrassment.\n\nThe emotional impact of gambling on a family can be quite extensive. Some family members may be quite negatively affected. Others may be less affected. Family members who are more affected by a gambling problem may, in turn, cause other family members to become more negatively affected.\n\nIn other words, the gambling problem of one family member can have a negative]" time="0.846"><properties><property name="score" value="0.0078391577" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[20.12.2010\n\nLaser 4.0, EUROFORUM \u2013 The role of innovation in a period of crisis: Claudio Dematt\xe9: Online innovation: Increasing competition in the global economy requires flexible strategies.\n\nDuring the 7th edition of Laser 4.0, EUROFORUM \u2013 The role of innovation in a period of crisis, which took place on the 18th of November in Venice, Claudio Dematt\xe9 discussed about \u201conline innovation\u201d, a concept increasingly adopted by companies with the aim to develop new business models.\n\n\n\nClaudio Dematt\xe9 is Associate Professor of Management and Strategy at LUISS University. He has been coordinating the Communication Technology Laboratory at LUISS since 2007 and he has been a member of the Telecommunication Research Centre (C.T.R.) since 2008.\n\n\n\nClaudio Dematt\xe9 is the author of articles on the topics of innovation, high technology and competition and he has also published several books.\n\n\n\nHis latest book, \u201cAlla ricerca della tecnologia dei miracoli\u201d, addresses the issue of competition in the information technology sector, analysing, in particular, the evolution of the competitive structure, new forms of alliances and companies\u2019 business models.\n\n\n\nDuring his lecture, Claudio Dematt\xe9 presented the results of his research on the technology sector, which demonstrate that the use of new technologies has not been a determining factor in the company\u2019s performance in the last ten years, in particular as regards innovation.\n\n\n\nThis approach highlights the importance of developing innovative strategies based on collaborative alliances, and on an analysis of the local and international competitive scenario. The various steps of this analysis have the aim to understand how competitive pressure is affected by local and international factors, and to gain an overview of the innovative strategies adopted by the main players.\n\n\n\nIn order to understand the way in which innovations are being developed and commercialised in different sectors, Dematt\xe9 carried out an analysis of the companies that are among the most innovative worldwide, together with their respective characteristics and with their distribution in different sectors.\n\n\n\nThe importance of online innovation is increasing. Analysing the phenomenon of e-commerce in detail, Dematt\xe9 explained that the traditional retail models are losing ground to the new approaches and the new technology is driving companies towards a new vision of how to develop new products and services.\n\n\n\nThe use of the Internet has turned the e-commerce market into an increasingly competitive field, in which \u201cfollower strategies\u201d, such as the launch of specific websites and of niche products, have become more common.\n\n\n\nOnline innovation is therefore a reality, however in order to make the most of this phenomenon companies have to develop a \u201cstrategic vision\u201d of the e-commerce market.\n\n\n\nThe lecture of Claudio Dematt\xe9 was followed by a panel discussion in which, among the other speakers, Giulio Tremonti, Deputy Prime Minister, Minister of Economy and Finances, took part.]" time="0.383"><properties><property name="score" value="1.7553985" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A man has been charged with the murder of a teenage girl whose remains were found near the A130 on Christmas Day.\n\nThe body of 14-year-old Bijal Patel was found at around 2pm in a wooded area in Thorpe Marriott, near the A130 interchange.\n\nBijal Patel, 14, was murdered in December (Picture: Archant)\n\nShe had last been seen on December 21 at a bus stop in the Mildenhall area, and a post-mortem examination found she died of multiple injuries.\n\nA 45-year-old man has now been charged with murder and will appear in court tomorrow.\n\nInspector Sam Cavale said: \u2018This is a very tragic and upsetting incident that has caused much distress to Bijal\u2019s family, the community and local emergency services.\n\n\u2018I\u2019d like to thank those people for their help and support. I also want to thank members of the public who have provided information so far, which has proved vital in the investigation.\u2019\n\nPolice are still searching for a \u2018light coloured\u2019 Vauxhall Zafira or Ford Galaxy, registration plates M474 WNN, after it was seen in the area of the bus stop where the teenager was last seen on December 21.]" time="0.366"><properties><property name="score" value="0.016385464" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01638546 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01638546
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Centers for Disease Control and Prevention's (CDC) Opioid Initiative, launched in 2015, is now widely seen as a turning point for the US government's response to the opioid crisis.\n\nIts very name represents a sea change in how the federal government views and treats the crisis, and its leadership role in the national response has shown that it takes opioid addiction seriously.\n\nBut experts say that CDC, along with state governments, still face challenges in reducing opioid overdose deaths.\n\nDr. Gail D'Onofrio, the chief of the Division of Emergency Medicine at Yale School of Medicine, said the key focus for the CDC now should be to give states support and the tools they need to develop local plans and initiatives.\n\n"I don't think the CDC should do it all," D'Onofrio said. "They can't."\n\nAmerica's opioid epidemic is largely a state and local crisis. State and local agencies, not the CDC, are responsible for drug-treatment programs, policing, and other areas of opioid response. And when it comes to administering Medicaid, states also have the lead role.\n\nFor this reason, CDC's success hinges on the agencies it funds, especially state health departments.\n\nHere's a look at the biggest obstacles to reducing opioid overdose deaths, and how CDC can address them.\n\nStates can't take on the opioid epidemic alone\n\nAmerica has a crisis on its hands. Opioid overdoses killed more than 42,000 people in 2016, and a July report from the President's Commission on Combating Drug Addiction and the Opioid Crisis noted that overdose deaths are "expected to keep rising."\n\n"We have to figure out a way to prevent the unintended consequences of our good intentions," said D'Onofrio.\n\nIn other words, the public-health responses to the opioid epidemic, from addiction treatment to education campaigns, are having a variety of unintended consequences.\n\nTo address them, experts say the CDC needs to support the state and local agencies, such as health departments and medical schools, that will be at the front lines of the response.\n\n"CDC has a responsibility to provide resources and expertise to state and local health departments," said Dr. Nora Volkow, director of the National Institute on Drug Abuse (NIDA).\n\nVolkow said the agency should focus on supporting states with developing evidence-based strategies for reducing opioid overdoses, expanding treatment, and improving pain management.\n\n"We know that there are tools out there," she said. "But it takes the CDC and NIDA working together to identify them, develop them, and help distribute them."\n\nIt's not just about access to treatment\n\nIn the midst of the worst drug crisis in US history, it's easy to believe that all the country needs is more treatment to curb opioid addiction.\n\nBut experts say it's not just about access to treatment.\n\n"The CDC has to provide help to states and communities in building up their capacity to respond to this epidemic," said Dr. Jon Zibbell, chief of the Bureau of Epidemiology at the Pennsylvania Department of Health.\n\nTo do that, Zibbell said the agency needs to create a national, standardized system to track the crisis \u2014 including the spread of heroin, fentanyl, and prescription drugs.\n\nCDC also needs to provide guidelines for evidence-based treatments, Zibbell said, and train a workforce to deliver them.\n\nZibbell said that the opioid crisis is different from previous drug epidemics, like HIV and hepatitis, because it is widespread, affecting every age group and gender. And unlike previous drug epidemics, it is not driven by a specific drug like cocaine or crack, but by the opioid class of drugs.\n\nSo, unlike other drug crises, Zibbell said, the opioid epidemic is not tied to any particular place or population, or the supply of a certain drug.\n\nAnd because the crisis has been going on for so long, the country needs CDC support to build up local expertise and respond.\n\n"There's no way around it," Zibbell said. "The best thing for CDC to do is support local, state, and territorial health departments."\n\nFocusing on the health of the general public is also important\n\nThe opioid epidemic has put a spotlight on the harm opioids do to people who use them. But D'Onofrio says it's also important to remember that these drugs]" time="0.378"><properties><property name="score" value="0.25738403" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Our Privacy Policy and Cookies Policy\n\nAbout our policy\n\nYou may have noticed we have changed our policy from time to time to comply with changes in legislation. We use cookies to measure site usage and help us to improve our site to make it easier to use and to show you content relevant to you. By continuing to use our website you are agreeing to the use of cookies as set out in our Cookies Policy. If you do not agree to our use of cookies in accordance with our Cookies Policy, please do not continue to use our site.\n\nAbout cookies\n\nA cookie is a small file of letters and numbers that we store on your browser or the hard drive of your computer if you agree. Cookies contain information that is transferred to your computer\u2019s hard drive. Cookies are used to store information, such as how you have customized a website or how you are registered to use a service. The use of cookies is a standard practice among most of the major websites to help provide you with the best experience possible. A cookie in no way gives us access to your computer or any information about you, other than the data you choose to share with us.\n\nCookies are used on this website\n\nWe use the following cookies:\n\n- PHPSESSID, expires after session\n\n- uid, expires after session\n\n- ASP.NET_SessionId, expires after session\n\n- __RequestVerificationToken, expires after session\n\nCookies used to remember your preferences\n\nWe use the following cookies to remember your preferences:\n\n- height=50\n\nCookies to keep you logged in\n\nWe use the following cookies to remember you are logged in to the site:\n\n- SESS\n\nCookies to remember your session\n\nWe use the following cookies to remember your session:\n\n- ASP.NET_SessionId\n\nWhat are cookies?\n\nCookies are a small text files that are placed on your computer by websites that you visit. They are widely used in order to make websites work, or work more efficiently, as well as to provide information to the owners of the site.\n\nCookies on this website are used to:\n\nmake our site work more efficiently\n\nremember choices you make to improve your experience\n\nremember your log in details so you don't have to keep entering them\n\nYou can find more information on the use of cookies in our Cookies Policy.\n\nThird party cookies\n\nWe use some third parties to provide parts of our website. These include Google Analytics to help us understand how our site is used and Adobe Target to help us deliver relevant adverts.\n\nOur partners and service providers may also use cookies. You can find out more information about how they use cookies at the following links:\n\nGoogle Analytics - http://www.google.com/intl/en/policies/privacy/\n\nAdobe Target - http://www.adobe.com/privacy/privacy_at.html\n\nYou can find out more about the cookies that are used on this website by reading the following links:\n\nHow to control cookies\n\nYou can control and/or delete cookies as you wish \u2013 for details, see aboutcookies.org. You can delete all cookies that are already on your computer and you can set most browsers to prevent them from being placed. If you do this, however, you may have to manually adjust some preferences every time you visit a site and some services and functionalities may not work.]" time="0.406"><properties><property name="score" value="1.713157" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.713157 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 1.713157
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[StarTech.com DVI to VGA Active Converter Adapter\n\n$14.99\n\nEnd Date: Friday Jul-27-2018 16:59:54 PDT\n\nBuy It Now for only: $14.99\n\nBuy It Now | Watch this item\n\n3 in 1 DVI to VGA + DVI to HDMI + USB Type C Converter Adapter Cable Cord\n\n$11.98\n\nEnd Date: Friday Aug-3-2018 13:44:34 PDT\n\nBuy It Now for only: $11.98\n\nBuy It Now | Watch this item\n\nDVI to VGA Adapter DVI Male to VGA Female Video Converter Cable\n\n$3.99\n\nEnd Date: Tuesday Aug-7-2018 19:20:22 PDT\n\nBuy It Now for only: $3.99\n\nBuy It Now | Watch this item\n\nDVI-D to VGA Adapter Cable, 1 ft (Silver) - CablesToGo - C2G\n\n$3.99\n\nEnd Date: Tuesday Jul-31-2018 10:12:58 PDT\n\nBuy It Now for only: $3.99\n\nBuy It Now | Watch this item\n\nSellerLink DVI-D Male to VGA Female Adapter Converter Cable\n\n$6.89\n\nEnd Date: Friday Aug-17-2018 0:51:12 PDT\n\nBuy It Now for only: $6.89\n\nBuy It Now | Watch this item\n\nDVI-D to VGA Converter, Black by Conxall\u2122\n\n$6.99\n\nEnd Date: Wednesday Aug-1-2018 14:50:14 PDT\n\nBuy It Now for only: $6.99\n\nBuy It Now | Watch this item\n\nDVI-D to VGA Adapter Cable, 1 ft (Silver) - CablesToGo - C2G\n\n$3.99\n\nEnd Date: Tuesday Jul-31-2018 10:12:58 PDT\n\nBuy It Now for only: $3.99\n\nBuy It Now | Watch this item\n\n2 in 1 DVI to VGA + DVI to HDMI Converter Adapter Cable for Laptop, HDTV Monitor\n\n$12.99\n\nEnd Date: Tuesday Aug-14-2018 22:07:47 PDT\n\nBuy It Now for only: $12.99\n\nBuy It Now | Watch this item\n\nHDMI to VGA with Audio, 1080p HDTV Converter Adapter Cable for PC HDTV TV Laptop\n\n$10.69\n\nEnd Date: Tuesday Aug-7-2018 14:44:26 PDT\n\nBuy It Now for only: $10.69\n\nBuy It Now | Watch this item\n\nStarTech.com Mini DisplayPort to VGA Active Converter\n\n$10.97\n\nEnd Date: Saturday Aug-4-2018 22:48:29 PDT\n\nBuy It Now for only: $10.97\n\nBuy It Now | Watch this item\n\nStarTech.com DVI to VGA Adapter, Active, w/ Audio, Silver (DVIVGAMM)\n\n$8.99\n\nEnd Date: Friday Aug-17-2018 23:29:26 PDT\n\nBuy It Now for only: $8.99\n\nBuy It Now | Watch this item\n\nMini DisplayPort DP to HDMI Adapter Cable 4K HDMI Adapter Cable\n\n$4.99\n\nEnd Date: Tuesday Aug-7-2018 18:42:12 PDT\n\nBuy It Now for only: $4.99\n\nBuy It Now | Watch this item\n\n2 in 1 DVI to VGA + DVI to HDMI Adapter Converter Cable for Laptop, HDTV Monitor\n\n$10.99\n\nEnd Date: Monday Aug-13-2018 18:41:43 PDT\n\nBuy It Now for only: $10.99\n\nBuy It Now | Watch this item\n\n2 in 1 DVI to VGA + DVI to HDMI Converter Adapter Cable for Laptop, HDTV Monitor\n\n$14.99\n\nEnd Date: Sunday Aug-12-2018 21:01:33 PDT\n\nBuy It Now for only: $14.99\n\nBuy It Now | Watch this item\n\nHDMI Female to VGA Male Adapter Connector Converter For HDTV LCD Projector\n\n$6.49\n\nEnd Date: Thursday Aug-16-2018 17:52:09 PDT\n\nBuy It Now for only: $6.49\n\nBuy It Now | Watch this item\n\nSellerLink DVI-D Male to VGA Female Adapter Converter Cable\n\n$7.99\n\nEnd Date: Friday Aug-17-2018 0:51:12 PDT\n\nBuy It Now for only: $7.99\n\nBuy It Now | Watch this item\n\nStarTech.com DVI-D Male to VGA Female Adapter Converter Cable\n\n$6.59\n\nEnd Date: Friday Aug-3-2018 18:28:21 PDT\n\nBuy It Now for only: $6.59\n\nBuy It Now | Watch this item\n\nHDMI to VGA Adapter, Plug and Play 1080p DVI Audio Video Converter Box Cable\n\n$]" time="0.398"><properties><property name="score" value="2.3814428" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.3814428 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.3814428
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Packing my B-day party\n\nLisbon Street in Hoboken\n\nChocolatier Biscuit\n\nChocolatier Biscuit Menu\n\nThe inside of the Chocolatier Biscuit\n\nOoooooh! I love the chocolate creme pie!\n\nCoconut Cream Pie\n\nSalted Caramel Cookie\n\nI love all of these pies!\n\nChocolatier Biscuit Open Mic Night\n\nThe Chocolatier Biscuit is located on 1st street in Hoboken right across the street from New York Seltzer. It is a small store that seems to only have seating for about 15 people and is a bit cramped. The owners do not serve any alcohol, but you are allowed to bring your own and have it with your food. The store has been around for a while, but in the past year has added a weekend lunch menu. I came here for their Open Mic night on Thursday night. I found out about this Open Mic night from OpenMic.com . This website has a list of all the Open Mic nights around the world, which is cool because I go to a lot of them in NYC. There are three things that make me fall in love with a store, yummy chocolates, yummy food, and a community vibe. This store has two of those things. When you walk into this store you instantly get a chocolate vibe. The store has a plethora of chocolate options, which are amazing, and they even have a chocolate museum (open only for select times). I just ordered a few chocolate covered truffles and some chocolates for my family for Christmas.The owner of the store, Bruce, came to talk to us about his store, and the Open Mic. I asked him what is their favorite pie. He said it is the coconut cream pie, which they make fresh daily, so it is the best one. I also asked him why they don't serve alcohol. He told me that his wife does not like alcohol, and since they have three kids, they have to make sure to keep it G rated. This is cool since I am the same way. I like having fun with my friends, but I don't want my children exposed to things they shouldn't be exposed to.The Open Mic is run by Bruce's daughter Liz. She has done a great job at getting people to come to this event. I was surprised that this place was packed when I came. Usually Open Mic nights I go to are either dead, or have a small turnout. When I went to the Open Mic at Riverview Tavern , I was the only person there. That night Bruce was performing. He was singing Christmas songs with his guitar. He is a very talented musician. He can sing, and play the guitar, and is a great songwriter. He played a lot of good Christmas songs, but did not play anything I knew. Some people I know came by and I talked to them for a bit, while listening to Bruce play. I was not planning on staying long since I have been to a lot of Open Mic nights, but after a while, I was having so much fun listening to the people performing, that I decided to stay. I also talked to Liz, and Bruce's wife about the food and store.Bruce and Liz had a table set up with various pies and cakes to try. There were over 20 pies and cakes to try. I really wanted to try them all, but I was saving myself for a special birthday celebration later that night.I got to try some of their dessert plates. They had vanilla bean cake, orange cake, apple pie, and cream cheese squares. I really liked their vanilla bean cake. It was moist, and not dry like other vanilla cakes I have had. The cake had a vanilla flavor, but was not over powering. The orange cake had an orange flavor that was not over powering either. I really liked this cake as well. I am not sure which one I liked the best. I am also not sure which cake was made at the store, and which was not. All of their desserts looked amazing!The music that night was great! There was a lot of talent. Everyone was amazing, and I wish I had taken some pictures. I was too busy listening and enjoying myself. One person, Tom, stood out to me. He had a great voice, and his rendition of I just called to say I love you was a great choice. I also loved when he did a song with a bit of a rock vibe to it. He has great range, and is an amazing performer.After listening to the performers, it was time to go. I was very full and the pie was just too much to handle. Liz came by and asked if I wanted to have another piece of pie. I said yes and took home a piece of their chocolate creme pie, and a slice of the coconut cream pie. Their chocolate pie was amazing. It was rich and moist and tasted just like a Hershey's chocolate bar. They only had one slice of the coconut cream pie left, so I took it home. It was also amazing. It was so creamy and tasted like coconut. I don't even like coconut, but this pie was so good! It had a bit of a gelatin texture to it. This was one of the best pies I have ever had. I really love all of the pies I had here, and will be back for more. I also want to try their chocolate covered brownies, chocolate covered strawberries, and their brownies.This store has amazing food and desserts, and has a great vibe. I really enjoyed my time here and look forward to returning! I hope you enjoy your time here as well! I would love to hear from you! Please send me a message or comment on this post.]" time="0.382"><properties><property name="score" value="0.338061125" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[5.0 out of 5 stars Excellent jacket with plenty of pockets. Verified Purchase This jacket is lightweight, well designed and with plenty of pockets. The Goretex fabric does its job as it has to and seems to be durable. The size I ordered is a bit too big but it still does the job well and I have plenty of room for extra layers. The fabric has a nice 'stretch' in it so you can put it on easily even if it is a little bit large. The length of the sleeves and the torso is excellent, as I have shorter arms.\n\nI would highly recommend this jacket as a light duty waterproof. I would buy it again.\n\n5.0 out of 5 stars Great jacket Verified Purchase A great jacket, warm enough for the Scottish autumn, and room for extra layers underneath. The sleeves are long enough, and the pockets are deep enough, even when wearing gloves. The fabric seems to be very hard wearing and well made.\n\n5.0 out of 5 stars Lightweight and comfortable Verified Purchase I got this because it was described as 'running short', which seemed to be a reference to the short length, as opposed to it being for a runner. I wanted a wind/waterproof jacket which could be worn as a 'trousers-coat' on its own or over my normal jacket, so I was quite happy with the short length.\n\nIt is extremely lightweight and, despite its short length, very comfortable. It has two large pockets on the front and one in the centre, plus two pockets inside the front and two on the upper arms.\n\nI haven't worn it in really wet weather, but in light drizzle it seems to work well. It is obviously waterproof, but perhaps not warm enough to wear on its own in very cold or wet weather. However, worn over my normal coat it does provide adequate insulation for light rain or windy weather.\n\nI would certainly recommend this jacket, especially if you don't need it for extreme weather.\n\n4.0 out of 5 stars Sturdy and waterproof Verified Purchase Bought for my daughter to keep in her bag, so she would always have it with her, incase the weather turns, the jacket is light and waterproof, so no worries about her getting wet. The jacket looks smart and has plenty of room to put in extra layers underneath.\n\n5.0 out of 5 stars Very Good for the price Verified Purchase I am very pleased with this item. It is lightweight and keeps the wind and rain out. The length is also great for me (I'm 5'9"). I was so impressed I bought one for my friend.\n\n5.0 out of 5 stars Liked this jacket Verified Purchase Nice jacket. I wore this jacket for quite some time. Its light but protective. Water proof but still comfortable when it gets warm. I had this jacket in grey and I will buy this jacket again when this one is worn out.\n\n5.0 out of 5 stars Ideal waterproof jacket Verified Purchase This jacket has just what I was looking for, at a really]" time="2.834"><properties><property name="score" value="0.019569525" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Prof. Petitpas Taylor: Legalization Could Have Been Handled More \u201cArtfully\u201d\n\nLegalization of cannabis could have been handled more \u201cartfully\u201d, says a member of the federal government\u2019s cannabis task force who is now Canada\u2019s Minister of Health.\n\nIn an interview with the public broadcaster CBC, Ginette Petitpas Taylor said that the marijuana legalization bill as written could have been better.\n\nPetitpas Taylor said that the cannabis task force was not given the time to study legalization to its fullest extent, although it had sufficient time to make an impact on public health and safety. She added that the task force did not get sufficient time to consult with the provinces, although it tried to do so.\n\nSpeaking about the changes that were made to the original bill, she said, \u201cIt could have been done more artfully and more in-depth.\u201d\n\nShe explained that legalization \u201chas been going on for a while in many provinces\u201d and the Canadian public was already aware of cannabis. She added that it was known that the Government was moving toward legalizing cannabis. \u201cSo, we should have had more time to consult with Canadians and the provinces on these issues.\u201d\n\nSpeaking about the implementation of the legislation, Petitpas Taylor said, \u201cWe were moving on an aggressive time frame and there were certain things we were unable to address to the extent we would have wanted.\u201d\n\nPetitpas Taylor said that one of the things she would have liked to see in the legislation is the ability to make rules around edible marijuana, something that will come in July 2019.\n\nShe also said that it would have been good to have had rules that \u201cregulate advertising and marketing\u201d so that it was appropriate. \u201cYou want to make sure that it\u2019s not promoting the use of this to children.\u201d\n\nShe added that as a parent of two teenagers, she was keen on seeing this as a parent.\n\n\u201cAs a parent, I want to make sure that we have the regulations in place, to make sure we are protecting children,\u201d she said.\n\nMeanwhile, the Quebec government has decided to raise the legal age for cannabis use to 21 from 18. The province also said it will not allow the use of marijuana in the presence of children. The province said it would allow its citizens to smoke marijuana only in private homes.\n\nIn its law on marijuana, Quebec will only allow cannabis to be grown in a residence and will not permit its purchase in stores.\n\n(Featured image by Guschenkova/Shutterstock.com)]" time="0.342"><properties><property name="score" value="0.026881421" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02688142 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02688142
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Barcelona will take on Juventus in the first leg of their Champions League quarter-final tie on Tuesday, as the La Liga champions look to make it back-to-back European trophies.\n\nBarcelona\n\nForm: FC Barcelona have had a mixed season in La Liga, sitting in third place in the table, 15 points behind leaders Atletico Madrid, and a point off second-placed Valencia.\n\nHowever, they still have the chance to win their seventh La Liga title in eight years and are in the Copa del Rey final against Athletic Bilbao. The Catalans have been victorious in nine of their 11 European matches this season, but were knocked out of the Copa del Rey by Atletico.\n\nKey player: It will take an outstanding performance from one of the stars of the Catalan club for them to overcome the Italian side. Lionel Messi is coming off his second Golden Shoe award in three years and has 18 league goals so far this campaign, the same number as Cristiano Ronaldo.\n\nJuventus\n\nForm: Juventus are currently sitting top of Serie A, just two points ahead of Napoli with three games left. They have gone 29 matches without a defeat in the league this season, a run that stretches back to October.\n\nThe Old Lady have been eliminated from the Coppa Italia by AC Milan but are in the semi-finals of the Europa League against Benfica. Juventus beat Bayern Munich in the last 16 of the Champions League to make the last eight and are in their first Champions League quarter-final since 2006.\n\nKey player: Arturo Vidal, Alvaro Morata and Carlos Tevez all offer Juventus attacking prowess, but if they are to get past Barcelona, it will be thanks to the defensive work of Andrea Pirlo.\n\nThe veteran midfielder has been key in Juve\u2019s run to the quarter-finals, and while he may not score the goals, his organisation of the team will be vital in the coming weeks.\n\nRecent form\n\nBarcelona: DWWWWWWWW\n\nJuventus: WWWWWWW\n\nPossible lineups\n\nBarcelona: Valdes; Alves, Pique, Mascherano, Adriano; Xavi, Busquets, Iniesta; Neymar, Messi, Sanchez\n\nJuventus: Buffon; Barzagli, Bonucci, Chiellini; Lichtsteiner, Pirlo, Vidal, Pogba, Marchisio; Tevez, Morata\n\nSports Mole says: 1-1 (5-4 on aggregate)]" time="0.287"><properties><property name="score" value="0.0011579082" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00115791 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00115791
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The Rolling Stones bring more than half a century of hits to their \u201cOn Air\u201d tour, which is currently hitting arenas around the U.S. For more than 50 years, the legendary rock band has been able to maintain a top-notch musical prowess and prolific discography, despite several hiatuses and several breakups. Rolling Stone magazine, for instance, recently included the Stones in its list of the 100 Greatest Artists of All Time, placing them at No. 13. Their influence in rock music is undeniable, especially considering that the Rolling Stones are one of the most commercially successful bands in history, selling more than 200 million albums worldwide. In addition, they have 12 number one albums and 18 number one singles. With countless hit songs under their belt, it is no wonder that this famous band has been able to attract hundreds of thousands of fans to their recent concert dates. Buy your The Rolling Stones tickets to enjoy an amazing live show!\n\nView The Rolling Stones Tickets\n\nThe Rolling Stones\n\nBritish rock band The Rolling Stones has been an iconic figure in the history of rock music since the 1950s. The band formed in 1962 and is still touring today. The band members are Charlie Watts, Keith Richards, Mick Jagger, and Ronnie Wood. These five individuals, who had a very interesting start, are considered one of the most successful rock bands of all time. They have sold more than 200 million albums worldwide. They are also credited as one of the greatest live acts in music history.\n\nThe Rolling Stones began their career as a pop and R&B cover band. They also incorporated jazz elements in their music. They achieved worldwide fame with their hit single \u201c(I Can\u2019t Get No) Satisfaction.\u201d It has since become one of the most recognizable and classic rock songs in music history. They followed the song with the equally popular \u201cPaint it Black\u201d in 1966. Other great songs in the 1960s include \u201cGet Off My Cloud,\u201d \u201c19th Nervous Breakdown,\u201d \u201cMother\u2019s Little Helper,\u201d \u201cJumpin\u2019 Jack Flash,\u201d and \u201cYou Can\u2019t Always Get What You Want.\u201d\n\nFollowing a lengthy break from touring, The Rolling Stones returned to the road in 1982. In 1986, the band played what is believed to be their final show at the Altamont Speedway in California. The concert has since become a notorious case study in cultural history and has been regarded as the moment that led to the end of the \u201cSummer of Love\u201d in the United States.\n\nThe band\u2019s success was not limited to its early years. The Rolling Stones have released numerous hits throughout the 1990s and 2000s, including \u201cStart Me Up,\u201d \u201cBrown Sugar,\u201d \u201cWild Horses,\u201d \u201cYou Got Me Rocking,\u201d \u201cCan\u2019t You Hear Me Knocking,\u201d \u201cMiss You,\u201d \u201cPaint It Black,\u201d \u201cHonky Tonk Woman,\u201d and \u201cUnder My Thumb.\u201d In 2004, the band was inducted into the Rock and Roll Hall of Fame.\n\nThe Rolling Stones remain a popular act on the road. They have been on tour in recent years and have scheduled more concert dates for 2016. They will be playing the Starplex Pavilion in Dallas, the Fiddlers Green Amphitheatre in Englewood, the MGM Grand Garden Arena in Las Vegas, and the Sleep Train Amphitheatre in Chula Vista. They have been invited to play in arenas, stadiums, and even stadiums as a guest band. They have won several awards, including 12 Grammy awards. The band has had many successful albums, including \u201cSticky Fingers,\u201d \u201cTattoo You,\u201d \u201cSome Girls,\u201d \u201cBeggars Banquet,\u201d and \u201cExile on Main St.\u201d\n\nThe Rolling Stones are certainly one of the most important rock bands in music history. They have contributed significantly to the development of rock music and set an example of success for other bands. If you are a fan, then buy your The Rolling Stones tickets and see them in concert!\n\nThe Rolling Stones Tickets PRICES As of 25/07/2018 the average The Rolling Stones tickets will cost you between $205 and $1790, if you are looking for the cheapest seats then catch the event being held at the The Forum - Los Angeles, Inglewood on 27/08/2018. The]" time="0.389"><properties><property name="score" value="0.24661168" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24661168 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24661168
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Temporary measures to help cool the overheating housing market have been extended, the Government has confirmed.\n\nPhoto: RNZ / Alexander Robertson\n\nThe extension of the measures will be for two years.\n\nThe Auckland housing market has risen sharply in recent months, and there is now a widely-held view the Auckland market is in a bubble.\n\nThe measures mean that:\n\nThe bright line test, which applies a tax on capital gains made on residential property, will apply in some circumstances, but not until 2018\n\nThe Government's land tax will be extended to unoccupied residential property, which is also due to come into effect in 2018.\n\n"We believe these are sensible, targeted and temporary measures, with a view to increasing housing supply and lifting the proportion of first home buyers in Auckland. It also means Government collects a little less revenue." Finance Minister Bill English said.\n\nRNZ Business Editor Rob Hosking said the measure has been extended, but the new land tax will not come into effect until 2018.\n\n"Land tax will only apply to 'under-occupied' homes, defined as any house or apartment that's unoccupied for more than six months of the year, in which case the owner will have to pay tax on it as though they were renting it out," he said.\n\n"At the moment there are approximately 41,000 vacant houses in Auckland - and that's without counting holiday homes, which would push that number higher."\n\nBanks and real estate companies are predicting prices will continue to rise.\n\n"The Auckland housing market has been in a state of severe imbalance for some time now, with demand outstripping supply, which is pushing house prices higher and making it difficult for first-home buyers to enter the market," said Peter Thompson, head of New Zealand for ANZ.\n\n"The [bright line] tax has been a step in the right direction, and should help to moderate house price inflation over time.\n\n"But the tax is unlikely to have a significant impact on the market over the next 12 months. More needs to be done."\n\nMike Alexander of real estate agency Barfoot and Thompson said the measures had helped reduce speculation.\n\n"The Government's recent housing market measures have had a positive impact on the Auckland housing market," he said.\n\n"As an example, prior to the first round of measures, the average sale price in Auckland was increasing at around 15 percent per annum. Since the introduction of the measures, prices have moderated to around 3 percent.\n\n"The Government has been very clear that they are looking to deliver a long-term solution to housing affordability, and we are looking forward to engaging with them on what we can do to support this over the coming months."\n\nFinance Minister Bill English said the measures would not prevent further gains in the housing market.\n\n"I can't say there's no risk of a bubble forming, but they're good, targeted, temporary measures, with a view to lifting the proportion of first home buyers in Auckland," he said.\n\nThe measures were due to expire in October, but were extended after consultations with the Reserve Bank and the Treasury.]" time="0.319"><properties><property name="score" value="0.25511086" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.25511086 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.25511086
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[| Feeds The latest issue of WWE Magazine is now online. WWE Magazine returns this week with a special feature on The Rock, his life on the road, and how he manages to balance it all. This issue also features a special tour of Paul Heyman\u2019s home, his office, and everything in between, and a countdown of the most brutal action figures ever. For more details, click here.\n\nInnovative Elimination Chamber Plans Posted by: Eve at 03:00 AM\n\n\n\n\n\nFollow WWF News | WENN | Sports Illustrated WWE.com announced the first match in the history of the Elimination Chamber will take place at No Way Out on February 17th. Four of SmackDown\u2019s top stars will participate in the first ever match for the Elimination Chamber. Kurt Angle, Chris Benoit, Edge, and Eddie Guerrero will compete for the right to face Triple H for the WWE Championship at Wrestlemania. The first ever Elimination Chamber will take place inside the Raw set. The Elimination Chamber consists of six chain-linked pods that will enclose each of the Superstars. The structure is approximately 60 feet high, 35 feet wide and weighs about 15,000 pounds. The pods are three feet wide and six feet tall and are composed of steel. The pods will be locked in the ringside area of the Raw set by two large hydraulic cams. Each pod contains a television monitor that will allow the Superstars to monitor what is happening in the match. The pods will be illuminated to allow fans at home to see the action inside. The pods will also be accessible by large trap doors which will be controlled by a floor director, ensuring that when they are opened, the Superstars inside the pods will not be tipped over. The Elimination Chamber was designed by WWE.com editor R.D. Reynolds and a team of engineers. The concept was first suggested to WWE by R.D. Reynolds in December, 2001. \u201cWe were sitting in the WWE.com war room discussing ideas for No Way Out,\u201d says Reynolds. \u201cI knew the Elimination Chamber match was a very real possibility, and I suggested to Vince McMahon that we do something to make it stand out. Vince thought the idea was great, and here we are.\u201d \u201cWhat was great about the opportunity,\u201d says Reynold, \u201cis that we were not just asked to build something. We were given the freedom to really create a unique environment that could provide for the best viewing experience for our fans. I knew what the WWE was looking for, so the team worked very closely to create a structure that would support the weight of the pods, the Superstars, and the hydraulics while allowing them to easily get out of the pods and to safety.\u201d \u201cWe want this Elimination Chamber to be the best the WWE has ever put on,\u201d says WWE Production Coordinator Andy Shepard. \u201cAnd we are confident that we will accomplish this with the design we have put together. We have tested the pods, and the ability to raise and lower them into the ring. There will be no problem with getting the Superstars in and out of the pods. It\u2019s an amazing and innovative design.\u201d The pods will be constructed in the Raw set by R.D. Reynolds and the WWE.com Engineering team. The pods will be lifted from the ringside area of the set to the ceiling, where the ringside crew will place them into the chains. \u201cThe pods are surprisingly light,\u201d says Reynolds. \u201cIt\u2019s a lot of work for one man to lift them, but with six men, it is very possible. And the ringside crew will not have any problem.\u201d \u201cWhen the pods are dropped,\u201d says Shepard, \u201cthey will remain exactly where we want them to. It\u2019s not like they will fall from the ceiling. They will be perfectly placed to complete the structure.\u201d The Elimination Chamber will be a steel structure approximately 15 feet high. \u201cThe pods and the chamber will be constructed of steel,\u201d says R.D. Reynolds, \u201cwhich makes it even more amazing that the Superstars will be able to lift it from the ringside area of the set to the ceiling. It is no easy feat.\u201d \u201cIt\u2019s not just the weight of the pods and structure that makes it difficult,\u201d says Shepard. \u201cWe also have to consider the ceiling of the Raw set. It is about 20 feet from the floor to the ceiling. So, the Superstars will not be able to simply walk the pods to the ceiling. There will be a few creative ways to get the pods up there.\u201d WWE Production Coordinator Andy Shepard has worked with the company since 1992. He has worked on the crew for several pay-per-views and TV shows, including ECW and SmackDown. \u201cThis is going to be an exciting match,\u201d says Shepard. \u201cIt will be something completely different from what the WWE Universe has ever seen. The fans at home and in the arena are going to be blown away. I know that is the goal of the WWE and everyone on the crew. We are all very excited about the opportunity to create something that no one else has ever seen before]" time="0.315"><properties><property name="score" value="0.242811425" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24281142 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24281142
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[About Us\n\nCall Us:\n\n208-887-5200 (office)\n\n208-426-3264 (fax)\n\nPO Box 498\n\nMcCall, ID 83638\n\nOur Staff\n\nJim Hagedorn, Executive Director\n\nHugh Wilson, Fire Marshal\n\nBonnie Boyd, Deputy Fire Marshal\n\nJim Hagedorn is an Idaho native and was raised in the Magic Valley area. He has been in the fire service for 30 years and has served in the following positions: Firefighter, Emergency Medical Technician, Fire Inspector, Investigator, Lieutenant, Assistant Chief, and Executive Director. He received his associate degree in fire science and bachelor\u2019s degree in sociology from Boise State University. He also has received certification as a Fire Investigator and NFPA fire inspector. Jim is the recipient of numerous awards including Chief\u2019s Award of Excellence, Fire Investigator of the Year, and four outstanding firefighter awards. Jim was named Idaho Fire Chief of the Year in 2006 and received the Fire and Life Safety Educator of the Year award from the International Association of Fire Chiefs in 2010. Jim has also served as an adjunct instructor at Boise State University and Northwest Nazarene College. Jim has been married to Pam for thirty-three years and they have three sons. Jim serves on the steering committee for the Treasure Valley Emergency Management Organization, the McCall Council of Governments Transportation Committee, and the Interagency Fire Council as a member and the Professional Standards & Training Committee as Chair.\n\nHugh Wilson is a recent graduate of Boise State University and obtained his bachelor\u2019s degree in Fire Administration. Hugh started his fire service career in Nampa, ID as a volunteer firefighter/EMT and later as a full time firefighter/paramedic. He has over 20 years of fire service experience and he has been in the McCall area since 2005. Hugh\u2019s duties include: fire and arson investigations, building inspections, fire prevention/education, code enforcement, administration, and communications. Hugh is the Idaho State Fire Investigator for the Kootenai County area and is also on the board of directors for the Panhandle Fire District. Hugh and his wife have three children and one grandchild. Hugh also volunteers with the Kootenai County Search & Rescue Team and was the Firefighter of the Year in 2006.\n\nBonnie Boyd is a lifelong resident of Idaho and has been in the fire service since 1995. Bonnie has worked for the McCall Fire Department since 1996. She served as the Training Captain for many years and currently is the Deputy Fire Marshal. Bonnie is also a part time firefighter with the Kootenai County Fire District #1 in Cascade and is the Idaho State Fire Investigator for Kootenai County. Bonnie is the current Idaho State Firefighter of the Year. She has also been the recipient of four outstanding firefighter awards and a fire safety educator of the year award. Bonnie is a member of the North Idaho Safety Council and serves as the NFPA coordinator for Idaho. Bonnie and her husband, Tom, have four children.]" time="0.295"><properties><property name="score" value="2.3069654" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Every social encounter can be a learning experience. These pages are for the casual observer who has an interest in the antics and unique behaviors that birds exhibit during social interactions. The field guide pages on this site are targeted to those interested in identifying species and learning about behaviors to find and identify birds.\n\nIt is important to realize that no two species exhibit the same behaviors. In this area we have started to examine what are called signatures and a few good examples of this would be:\n\n1) Acrobatic (Cedar Waxwing, Blue Jay)\n\n2) Furtive and Snatching (Bewick\u2019s Wren, House Wren, Northern Mockingbird)\n\n3) Harsh (Barn Swallow, Great Horned Owl)\n\n4) Loud Calls (American Robin, Ruffed Grouse)\n\n5) Music (Great Crested Flycatcher, Northern Mockingbird)\n\n6) Mimic (Northern Cardinal, Yellow Warbler)\n\n7) Nocturnal (White-tailed Kite)\n\n8) Simple and Direct (American Crow, Barn Swallow)\n\n9) Speedy (Song Sparrow)\n\n10) Surprising (Northern Mockingbird)\n\n11) Trilling (Yellow-bellied Sapsucker)\n\n12) Unruffled (Blue Jay)\n\n13) Watchful (Raven, Killdeer)\n\nThere is no better way to observe social interactions in nature than by attending a bird-banding event. If you are unfamiliar with the practices of bird banding in North America you can learn more about it here.]" time="0.336"><properties><property name="score" value="0.28981733" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.28981733 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.28981733
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[While there are only two weeks to go before the U.S. presidential election, the outcome is very much in the balance.\n\nWith a difficult economic outlook ahead, the U.S. has a more than two-year spending plan to review and agree on.\n\nU.S. President Barack Obama is seeking re-election against former Massachusetts governor Mitt Romney, who also challenged Obama for the White House in 2008.\n\nThe presidential race is coming down to the wire and a series of television debates. A Gallup poll, conducted on October 28, showed Obama holding a two percentage point lead over Romney.\n\nIf that translates to the polls, Obama would win by about two percentage points, not enough for him to win in the electoral college, and the outcome could depend on a handful of states in the key electoral college.\n\nIf Romney were to win by two percentage points, he would likely get the 270 electoral college votes required to be declared the winner.\n\nAn increasingly tough economic outlook and the fight over the fate of the health care law known as Obamacare are defining issues in the presidential race.\n\nObama came into office with an economy in free fall in 2009, but has seen the unemployment rate drop from 9.8 to 8.1 percent since he took office.\n\nRomney, meanwhile, has been pushing his experience as a former venture capitalist and his time as governor of a traditionally Democratic state as evidence of what he could do to create jobs as president.\n\nThe president was pushed to the center during his first term to tackle issues such as the budget deficit, tax reform, and immigration. But he is returning to the left-of-center platform of his first run for the White House in 2008, when he beat Senator John McCain of Arizona in the general election.\n\nThere are two television debates left before the November 6 election, one at the University of Denver and another in Florida.\n\nRecent presidential polls in swing states show Obama has an edge in Ohio, Virginia, Colorado and Iowa, but Romney is running close in Florida, Nevada and North Carolina.]" time="0.292"><properties><property name="score" value="0.083807744" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08380774 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.08380774
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rostock. Mit \u201eTop Models\u201c und \u201eGoodbye Deutschland\u201c erreichte Sat.1 j\xfcngst Rekord-Quoten, und nun baut die Sendergruppe um ProSiebenSat.1 weiter auf junge Frauen. \u201eM\xe4nner, M\xe4nner, M\xe4nner\u201c, ein auf den ersten Blick deutlich schriller wirkender Ableger des Markenkonzepts, k\xf6nnte es demn\xe4chst auf ProSieben zu sehen geben.\n\n\u201eInhaltlich sprechen wir \xfcber etwas Konstruktives, wie M\xe4nner in den heutigen Zeiten Frauen beeinflussen und verf\xfchren k\xf6nnen\u201c, erkl\xe4rt ProSieben-Gesch\xe4ftsf\xfchrer Max Conze. Im Gegensatz zu \u201eGoodbye Deutschland\u201c w\xfcrde \u201eM\xe4nner, M\xe4nner, M\xe4nner\u201c h\xf6chstwahrscheinlich eine eher vergn\xfcgliche als emotionale Note haben. Aber Conze betont, dass es sich um einen zun\xe4chst f\xfcnfst\xfcndigen Formatvorschlag handelt. Erst bei einer erfolgreichen Ausstrahlung in der Probezeit w\xfcrde \xfcber eine Vertiefung in Folgeformaten entschieden.\n\nK\xfcnftig eher als \u201eTagesbrenner\u201c\n\nDer umstrittene Castingsender \u201ePunkt 12\u201c war ein Teil der von Programmchef David Bernsen angepeilten zweist\xfcndigen \u201eTagesbrenner\u201c. Ein Plan, den man nach seiner K\xfcndigung zum Ende des vergangenen Jahres wieder fallen gelassen hat. Nun werden die neuen Anstrengungen auf ein Format gesetzt, das tats\xe4chlich \xfcber mehrere Tage als \u201eM\xe4nner, M\xe4nner, M\xe4nner\u201c l\xe4uft.\n\nVon Hans St\xfcckelberg]" time="0.300"><properties><property name="score" value="0.71235925" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Technorati Tag: main index, ipod, google, p2p, google book search, gbook, ebook, itunes, gbs, gbs author\n\nI've posted a few things about Google Book Search in the past. It's an important project and it's got huge potential, both good and bad. Google made news last week when they announced they'd begun scanning physical books. This is a pretty big deal for them. It could generate huge amounts of data, and they could sell this data to various places (like, maybe, Apple), and the revenue would help them to drive costs down for their users. But it might also turn out to be a huge boon for people wanting to make a buck off of their books. It could also, theoretically, provide readers with a better means to search for books that they can read on their computers, phones, and ipods. So, let's break this down into three camps:The IPod/Apple: They're going to release an iPod that lets you view (and possibly download) ebooks, but the iTunes Store will probably only carry ebooks that Apple wants you to have, since they don't want to deal with Amazon and its DRM (and Amazon, being that big, can just walk away from the whole ebook thing, really). They can make a deal with a huge company, but they'd have to do it on Apple's terms, or they could make a deal with a bunch of indie ebooks, which they can't control, and the numbers would be pretty small compared to the volume of sales.The Kindle: They already control the marketplace for ebooks on this platform, and have sold millions of Kindles already. I don't think this really affects them in any way, other than to make sure they're in control of the platform so they can dominate the ebook market.The New York Times and the other mainstream media outlets: They are really excited about the prospect of Google scanning millions of books. They can get some for free, and they can also scan some of the books they already have and make them available. But if they want to sell any, they'll have to get permissions, so it could be a while before that happens.So, this is the question: if Google is going to start selling books, how will they do it? Google, being Google, is likely to do something completely different, so they have the opportunity to make some great stuff happen, but it'll take some time, and they may not have a lot of patience. I really think this is a great project, but I have my doubts about it.]" time="0.308"><properties><property name="score" value="0.1798188" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.1798188 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.1798188
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Four young adults with various cognitive and psychiatric deficits are investigated in a longitudinal study. All patients showed large improvements in neuropsychological functioning after administration of the antiepileptic drug levetiracetam. They benefited from the drug, but with widely different underlying pathologies. This shows the need for using individualized treatment strategies. The possible role of genetic factors, mechanisms of action of levetiracetam, and possible side effects are discussed.\n\nNeuropsychological deficits are common in various psychiatric disorders and epilepsy. They often improve with treatment, but little is known about the efficacy and safety of the various treatment modalities.\n\nINTRODUCTION\n\nA number of psychiatric disorders are characterized by neuropsychological deficits. Neuropsychological deficits may be seen in schizophrenia [1], mood disorders [2], obsessive-compulsive disorder (OCD) [3], attention-deficit/hyperactivity disorder (ADHD) [4], substance abuse [5], and post-traumatic stress disorder (PTSD) [6]. These neuropsychological deficits may arise from different pathophysiological mechanisms, and they are often described in terms of aphasia, apraxia, agnosia, or impairment of cognitive processing.\n\nThe underlying pathophysiology of these neuropsychological deficits is complex. Deficits can be the result of many different disorders, including disease of the brain, neurodevelopmental disorders, disorders that affect the central nervous system (CNS), or disorders that affect the body and are reflected in the CNS [7]. This is illustrated by the number of disorders in which neuropsychological deficits have been described (Table 1). In most patients, the neuropsychological deficits are caused by a combination of multiple different pathophysiological factors [7, 8].\n\nNeuropsychological deficits can occur with a variety of psychiatric disorders. When such deficits occur in epilepsy, there are specific cognitive deficits that are characteristic of the disorder [9]. When epilepsy occurs in combination with a psychiatric disorder, the cognitive deficits may be aggravated [9, 10]. When the psychiatric disorder itself involves cognitive deficits, they will also be aggravated. This will make the treatment of the underlying disorder more difficult. This will increase the risk of relapse, and may also increase the risk of cognitive deterioration.\n\nThe major types of treatments that are used for the various psychiatric disorders are listed in Table 2. Antiepileptic drugs (AEDs) are one of the main forms of treatment for epilepsy. In the treatment of psychiatric disorders, especially when the psychiatric disorder is accompanied by neuropsychological deficits, AEDs are also frequently used. For these disorders, AEDs are often combined with psychotropic drugs. This leads to the question of whether AEDs may have a beneficial effect on neuropsychological functioning. Such an effect may improve the overall functioning of the patient.\n\nLevetiracetam is an AED that is registered in more than 50 countries and is licensed in the Netherlands as a monotherapy for the treatment of various types of epilepsy. It has been used in the treatment of a number of psychiatric disorders. A recent review [11] found positive effects of levetiracetam on neuropsychological functioning in psychiatric patients with bipolar disorder and in a subgroup of depressed patients.\n\nBecause of the poor efficacy of the currently used treatment modalities, the search for new treatment strategies is ongoing. In particular, studies that investigate the possible therapeutic effects of AEDs are useful. In the treatment of epilepsy, there are various AEDs that may have specific effects on neuropsychological functioning [12]. The clinical effects of AEDs may depend on the underlying pathophysiological mechanisms that are present in a particular patient [8]. It is therefore possible that different types of AEDs have different effects on neuropsychological functioning. This may lead to a personalized treatment strategy for different patients. However, no such studies have been conducted.\n\nThe aim of the current study was to investigate the possible effects of levetiracetam on neuropsychological functioning in patients with different psychiatric disorders. The study focused on three major issues. First, it aimed to determine whether levetiracetam may have beneficial effects on neuropsychological functioning. Second, the efficacy of levetiracetam in different patient groups was compared. Third, the safety of levetiracetam was assessed.\n\nMETHODS\n\nSubjects\n\nThe study was conducted at the outpatient clinic of the University Medical Center Groningen in the Netherlands. All the patients were diagnosed at this center, and they all received treatment for their disorder(s). The following patient groups were included:\n\n1. Adults with bipolar disorder (n = 8)\n\n2. Adults with major depressive disorder (n = 6)\n\n3. Adults with OCD (n = 2)\n\n4. Adults with ADHD (n = 2)\n\n5. Adults with PTSD (n = 2)\n\n6. Adults with a variety of combinations of these disorders (n = 3)\n\nTable 1: Types of neuropsychological deficits in various psychiatric disorders.\n\nTable 2: Types of treatment for various psychiatric disorders.\n\nAll the patients were referred to the outpatient clinic because of their neuropsychological deficits. The patients were not selected on the basis of any specific criteria. All patients with a DSM-IV [13] diagnosis of bipolar disorder, major depressive disorder, OCD, ADHD, or PTSD were included. Patients with bipolar disorder I and II, major depressive disorder I and II, and ADHD were also included if they were under the age of 18 years. Patients with PTSD and patients with other combinations of psychiatric disorders were included. All patients were between the ages of 18 and 65 years and were either male or female.\n\nAll patients were included in a longitudinal study [14]. During the course of the study, some patients were added and others dropped out of the study. Therefore, the number of patients included in the study changed over time. All patients gave their informed consent for their data to be used in the study. All patients received treatment with levetiracetam for at least 2 months. The following patients received levetiracetam for more than 2 months: five patients with bipolar disorder, three patients with major depressive disorder, and two patients with OCD. Patients were included in the study if they received levetiracetam at an average dose of less than 3,000 mg/day. One patient with PTSD received levetiracetam at an average dose of 5,500 mg/day.\n\nPatient data\n\nThe data on the patients were obtained from the clinical files of the University Medical Center Groningen and the files of the pharmacies where the patients received their levetiracetam. In addition, the patients were seen by the authors at the University Medical Center Groningen. The clinical file data consisted of demographic]" time="0.643"><properties><property name="score" value="0.0088804725" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Conan O\u2019Brien is taking a stand against a California bill that would require porn stars to use condoms.\n\nThe proposal is currently in committee at the state legislature, but O\u2019Brien has joined the ranks of the adult entertainment industry to oppose the bill.\n\n\u201cAs the founder of Team Coco, I believe that it is important to support Team Porn,\u201d O\u2019Brien said in a statement, adding that the condom-mandate would \u201cimpose on actors and viewers an extra layer of non-sexy bureaucracy.\u201d\n\nO\u2019Brien signed his name to a letter (obtained by the Los Angeles Times) opposing the bill that was signed by dozens of adult entertainment performers, including a number of porn stars.\n\n\u201cPorn is an adult product, and when consumed, it should be consumed by adults who have the option to do so with or without a condom,\u201d the letter reads. \u201cWe believe that the use of condoms in adult videos is an element of the production that is intended to be viewed by adults and not by children. It is our belief that imposing condom use in adult films would result in an increase in the number of people viewing adult films online.\u201d\n\nAccording to the porn stars\u2019 letter, \u201cporn performers are more likely to be exposed to STIs than other workers\u201d and they are tested regularly. The letter argues that there is no evidence that porn stars are exposed to a greater risk of HIV/AIDS than people in other industries and that the number of performers diagnosed with HIV or AIDS has been extremely low.\n\n\u201cOur industry has been a model for safe sex in the workplace since its inception in the early 1970s,\u201d the letter continues. \u201cHowever, we feel that adding another layer of bureaucracy to our industry would be a disservice to our business, and the people who work in it.\u201d\n\nThe bill, introduced by Assemblywoman Isadore Hall (D-Compton), would impose the condom mandate on all porn actors in the state of California. Violators would be fined up to $1,000 and could have their film licenses suspended or revoked.\n\n\u201cWhile pornography is protected under the First Amendment, the adult film industry is subject to occupational safety and health standards like every other industry in the state,\u201d Hall said in a statement. \u201c[This bill] will help protect adult film performers from contracting HIV and other sexually transmitted diseases.\u201d\n\nA spokesman for O\u2019Brien declined to say whether or not the comedian, who hosted the MTV Music Awards on Sunday, will appear in a condom ad in California.]" time="4.727"><properties><property name="score" value="0.0029071704" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00290717 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00290717
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Hindi literature\n\nWhen Delhi was ravaged by famine in the 16th century, many of its citizens fled north to towns such as Agra and Lucknow. Hindi literature in the classical form found its roots in the Bhakti movements of north India in the 16th century. Urdu literature has been cultivated with both influences and native traditions.\n\nThe colonial rule of the British Empire introduced English and western literature to India, and had the most profound impact on Hindi literature. In addition to the literature that evolved during the Mughal period, this period was also marked by the literary works of Bhakti saints.\n\nLike Persian, in Urdu also poetry played a central role. It was also the main language of the court, where Urdu was distinguished from Hindi by a heavy Persian vocabulary. The two developed a rich literary tradition with a profusion of prose genres and poetic forms. There are early Prakrit work of Dandin and Gunabhadra, an example for that Dandin was a Buddhist author and had done translation of sutras and sastras.\n\nIn South Asia, in the 19th and early 20th centuries, Hindu nationalism in Hindi-speaking regions was expressed through the development of Hindi-language literature. During the 19th century, the Hindi literature developed the tradition of Dalit literature; works of B. In the 20th century, this tradition was carried forward by the Bhakti movement poets, in such notable works as Kabir and Amrita Pritam, the Western equivalent of which would be Whitman and Ginsberg.\n\nHindi literature is a formally recognized strand in the "national literature" of India. While India has several regional languages and traditions of literature, the "national literature" of India is written in Hindi.\n\nWhile Hindi is the official language of India, most literary works are written in regional languages. The prose works of the Bhakti Movement were originally written in various dialects of Hindi. The Awadhi dialect of Hindi has been influential in the development of Hindi prose, and most Hindi novels and short stories have been written in it.\n\nWith the translation of a large number of Western literary works in Hindi, there was a fresh impetus to the development of modern Hindi literature. This movement is called the Chhayavaad. One of the most prolific Hindi novelists was Premchand. Another great Hindi novelist was Munshi Premchand. An interest in Munshi Premchand's works among the wider populace has led to a resurgence in the popularity of his works. Other writers of the same era included Mahadevi Varma, Mahavir Prasad Dwivedi, Brijmohan Mishra, and Krishan Chander. The change in the Indian educational system, the literary taste of the people and the Hindi belt's growing cultural influence helped Hindi gain greater literary and socio-political popularity. Many Hindi writers belonging to this era are regarded as important figures in modern Indian literature.\n\nThe Anand family of novels is a sequence of novels by Munshi Premchand. The fictional village of Bawara in them is based on author's native town of Hamirpur.\n\nJai Arjun Singh (born in 1967) is an Indian Hindi fiction writer. He was a part of a modern generation of writers who were popular in the 1990s, along with Sachin Kundalkar, Krishna Sobti, etc. Singh has contributed short stories, novellas and novels in Hindi. He has received various awards, including the prestigious Sahitya Akademi Award for his work, both as a writer and editor. Singh's popularity as a Hindi writer was influenced by his early life in the state of Uttar Pradesh.\n\nAfter independence of India, the Hindi language has continued to grow in all Indian social sectors. Many Hindi writers and poets continued to write in the era of Independence.\n\nJawaharlal Nehru University is a prominent university in India, situated in New Delhi. JNU has produced a large number of important Hindi writers, including, among others, Vikram Seth, Mukul Kesavan, Gulzar, Harishankar Parsai, Anita Desai, Saadat Hasan Manto, Munshi Premchand, Acharya Chatursen, Dr. Pankaj Narayan, Bhisham Sahni, Amrita Pritam, Sumitranandan Pant, Satyajit Ray, Rajendra Yadav, Kedarnath Singh, Ramdhari Singh 'Dinkar', Umashankar Joshi, Suryakant Tripathi 'Nirala', Vishnu Prabhakar, Ramesh Pangariya, Rajendra Keshavlal Dhandhale, Gopi Chand Narang, Vinay Bhargava, Brij Narayan, Chandrashekhar, Chaman Lal, Vimala Thakur and Prakash Swatantra Raju.]" time="0.412"><properties><property name="score" value="0.037926365" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03792636 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.03792636
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[There are a lot of men who get a tattoo of some nature and there are quite a few women that get them as well. One of the most popular is the outline of a butterfly. The Butterfly can symbolize a lot of things such as freedom, beauty, and transformation.\n\nIf you have the desire to get a tattoo then a butterfly will be one of the top choices for a lot of people. There are many different versions of the butterfly and many different meanings behind the butterfly. Here are the top 10 meanings of a butterfly tattoo:\n\n1. Transcendence\n\nTranscendence means to rise above or go beyond. Many people get this type of butterfly to help them overcome a difficult period in their life. A butterfly is a great symbol of life after tragedy.\n\n2. Transformation\n\nTransformations are great transformations because they are a complete change of mind, body, and soul. A butterfly tattoo symbolizes change for a better future. It\u2019s a great transformation to symbolize a time in your life when you needed to get over something.\n\n3. Freedom\n\nThe butterfly is a symbol of freedom. This can be from things that you have been keeping]" time="0.254"><properties><property name="score" value="0.23414138" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Kolmetoista vuotta sitten kirjoitin tekstin, jossa pohdin, kuinka eduskuntaty\xf6 tukeutuu vahvasti p\xe4\xe4tt\xe4jien ja vaikuttajien muistikuviin.\n\nTutkimukseni osoitti, ett\xe4 yleisesti hyv\xe4ksytt\xe4v\xe4, demokraattisessa prosessissa muodostettu linja kirjoitetaan muistelun osaksi, jolloin sit\xe4 ei en\xe4\xe4 muuteta vaan se saa konkreettisen miehityksen: t\xe4st\xe4 t\xe4m\xe4 on l\xe4ht\xf6isin, t\xe4m\xe4 on asia, jonka takia olemme k\xe4yneet t\xe4m\xe4n j\xe4lkeen.\n\nMuistelun muotoja ovat muun muassa arkistokuvia, historiallisia dokumentteja, kirjoituksia ja puheita.\n\nP\xe4\xe4t\xf6ksenteon j\xe4lkiseurauksena n\xe4m\xe4 muistelut ovat vaikuttaneet erityisesti EU:n suhteen. Vuonna 2000 julkaistu euro-j\xe4senyyden kriisi sai hiljalleen muotonsa juuri muistelun kautta.\n\nEU:n hyv\xe4ksytt\xe4vyyden ja nykyisten vaikeuksien v\xe4lill\xe4 on luonteva yhteys. Suomen Eurooppa-politiikkaa voi tarkastella my\xf6s kolmesta muistelusta.\n\nSilloinen p\xe4\xe4ministeri Paavo Lipponen esitti vuonna 1999 vakuuttavasti, ett\xe4 kansalaiset eiv\xe4t tajua EU:n merkityst\xe4 ja ett\xe4 suomalainen eurooppalainen maaper\xe4 antaisi hyv\xe4n pohjan EU-tutkimukselle. Tutkimus onkin n\xe4ill\xe4 n\xe4kymin tuottanut lukemattomia suomalaisia eurooppalaisia.\n\nKolmas mielenkiintoinen muistelo liittyy j\xe4senyyden nelj\xe4nnen vaiheen prosessiin. Siin\xe4 esimerkiksi yritysjohtajat tuomitsivat EU:n perustuslain arvot esimerkillisesti ja pitk\xe4styneesti vuonna 2001.\n\nTuolloin oli merkkej\xe4 siit\xe4, ett\xe4 EU:ta halutaan v\xe4h\xe4tell\xe4 muiden asioiden sel\xe4n takana.\n\nMuistelu on nyt tehnyt teht\xe4v\xe4ns\xe4. On uuden ajan puolesta puhuttava uudella tavalla, mutta vanhoja sanoja on hyv\xe4 ymm\xe4rt\xe4\xe4.\n\nKuva: Pasi M\xe4kel\xe4]" time="0.295"><properties><property name="score" value="0.019437391" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Welcome to week 3 of the NFL and fantasy football playoffs. This is the most important week of the season and that is reflected by the quarterbacks and running backs you can expect to see on the Waiver Wire Report.\n\nYou know what to do, don\u2019t get fancy.\n\nQUARTERBACK\n\nPlayer Name Team Opponent Y!% ESPN% Own% Need/Stream/Forgot? Luck, Andrew Colts vs. Texans 40.7% 35.4% 22.5% Needed Rivers, Philip Chargers vs. Chiefs 30.8% 27.3% 15.5% Stream Bradford, Sam Eagles vs. Bears 28.0% 20.9% 8.1% Stream Palmer, Carson Cardinals vs. Lions 28.0% 20.2% 8.2% Stream Smith, Alex Chiefs at Chargers 22.0% 22.2% 5.5% Stream Gabbert, Blaine Jaguars vs. Ravens 19.5% 15.9% 3.7% Stream Fitzpatrick, Ryan Texans at Colts 16.3% 17.8% 3.4% Stream Wentz, Carson Eagles vs. Bears 14.0% 14.6% 1.9% Stream\n\nNo real surprises here, but you might want to use one of the Streaming options.\n\nRUNNING BACK\n\nPlayer Name Team Opponent Y!% ESPN% Own% Need/Stream/Forgot? McCaffrey, Christian Panthers vs. Falcons 64.3% 44.5% 37.2% Needed Ingram, Mark Saints at Cowboys 49.2% 47.7% 31.9% Stream Kelley, Rob Redskins vs. Giants 40.7% 38.9% 18.6% Needed Cohen, Tarik Bears at Eagles 39.1% 30.4% 17.1% Stream Stewart, Jonathan Panthers vs. Falcons 38.3% 36.6% 14.4% Needed Coleman, Tevin Falcons at Panthers 32.1% 31.6% 12.1% Stream Forte, Matt Jets vs. Patriots 29.5% 26.3% 7.6% Stream Burkhead, Rex Patriots at Jets 29.5% 26.3% 7.6% Stream Ware, Spencer Broncos vs. Colts 28.2% 28.0% 7.1% Stream Bernard, Giovani Bengals at Steelers 26.0% 20.4% 5.1% Stream Mixon, Joe Bengals at Steelers 26.0% 20.4% 5.1% Stream Mack, Marlon Colts at Broncos 23.8% 17.6% 3.9% Stream Sproles, Darren Eagles vs. Bears 23.0% 20.0% 3.6% Stream Fournette, Leonard Jaguars vs. Ravens 22.2% 22.4% 3.4% Stream Charles, Jamaal Chiefs at Chargers 21.7% 23.2% 3.3% Stream Thompson, Chris Redskins vs. Giants 20.0% 17.2% 2.6% Stream Coleman, Derrick Falcons at Panthers 20.0% 17.2% 2.6% Stream\n\nMcCaffrey and Ingram are the only obvious must starts. However, the Redskins will most likely be playing without Rob Kelley so Samaje Perine may be worth a shot. The Bengals and Eagles game could feature some rushing opportunities for both teams. Also, the Vikings may not have Dalvin Cook back, so Jerick McKinnon could be a good option.]" time="0.299"><properties><property name="score" value="0.01634584" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01634584 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01634584
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In 2013 werd Hessel Stoffelijke Samenwerking opgericht in Waregem. Het bestaat uit vier families en ouders en heeft een evenwichtige samenstelling, zowel qua leeftijd als qua geslacht. Zij gaan al jaren samen op vakantie en bij momenten ook samen met andere gezinnen op voorstellingen. Het gaat om vrije tijd en daar hoort een beetje avontuur bij, waarbij we het avontuur opzoeken. Deze ontdekkingstocht voor de meisjes is dan ook een nieuwe ervaring. Ze zijn benieuwd naar wat we er mee gaan doen en wat we zullen ontdekken.\n\nOp het meegebrachte handwerk kleien ze elk hun eigen embleem. Daarna wordt er een verhaal verteld. Op de klei na zijn er geen materialen. We luisteren naar de verteller en we horen ook het voorbije geluid van een speelgoedpiano. Daarna spelen we met de geluiden. We zingen de zon op en de zon onder. Bij het opstaan en bij het gaan slapen. De opdrachten gaan over de sfeer van de dag, over zon en wind, over de tijd van dag en nacht, over het geluid van vogels en over de stilte van de nacht. De meisjes kiezen een embleem en maken een wandtapijt. Dit is een inleiding op het volgende nummer, de bergbeek van Liedekerke.\n\nIn de tweede groep zijn de meisjes die van afwisselende activiteiten houden. Zij]" time="0.317"><properties><property name="score" value="0.0058783274" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[SpaceX has been getting into the satellite-launching business. As CEO Elon Musk revealed, the company is planning to send its first operational satellites into space within the next couple of months.\n\nSpaceX already has two test satellites in orbit. The first is known as TinTin A and the second is TinTin B. The company has already tested the technology on these two devices, and will launch the first batch of satellites in a couple of months, and these will be in operation by the end of the year.\n\nAccording to The Verge, SpaceX has the go-ahead from the Federal Communications Commission to launch 4,425 satellites in low-Earth orbit. Musk explained that it would take seven launches of its Falcon 9 rocket to deploy all the satellites, and each launch would put up about 250 of them. Each satellite would weigh 250 pounds (110 kg), and SpaceX would use its Falcon 9 rocket for the launch.\n\nThe FCC has reportedly given SpaceX permission to launch more than 7,000 satellites in total, but the company will likely stop at 4,425 once the operational satellites are deployed.\n\nThe FCC already has approved another batch of satellites for SpaceX to launch. However, these will be in higher orbits, and the company will need special approvals from the International Telecommunications Union.\n\nSpaceX has already made arrangements with broadband Internet service providers to use its satellites once they are in orbit.\n\nThe company has said that its service will be \u201cfaster and cheaper\u201d than other broadband options. Its service will be aimed at the U.S. at first, but it may eventually expand to other countries.\n\nSpaceX\u2019s aim to bring high-speed broadband to more parts of the world will certainly be interesting to watch, but this may not be the only satellite-related announcement the company makes soon.\n\nAccording to reports, SpaceX is also planning to launch its Dragon 2 spacecraft to the International Space Station. This could happen as early as April 2019.\n\nThe Falcon 9\u2019s launch will put a high-resolution imaging satellite, known as PAZ, into orbit. The spacecraft was built by the European aerospace and defense contractor, Airbus.\n\nThe company said that the launch will use the same rocket that will be used for the Falcon 9 carrying the Crew Dragon spacecraft to the ISS next month.\n\nWith the Falcon 9\u2019s payload fairing, the spacecraft will be about 11 feet (3.3 meters) in diameter.]" time="0.294"><properties><property name="score" value="0.009232772" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00923277 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00923277
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Most readers were up in arms when DC Comics spoiled the ending of Batman V Superman: Dawn of Justice by including it on the cover of the movie's official soundtrack. That's especially since the actual soundtrack listing, which featured most of the score by composer Hans Zimmer, didn't include a sample of the song at all.\n\nWell, now fans can finally listen to a sample of that cover and get a better idea of what the soundtrack may offer. The cover song was recorded by Gary Clark Jr., and while it's pretty good, it's definitely missing something.\n\nAfter that fateful sequence in the movie, you'd think the song would feel more emotionally impactful, but instead it just feels hollow and shallow. It's not terrible, but the soundtrack version of the song isn't quite as strong as the cover version of the song.\n\nThe thing is, the song is actually pretty good, and it's fitting for the movie and doesn't feel out of place. However, because it doesn't fit the tone of the movie or soundtrack, it just doesn't sound like it belongs.\n\nIt's not like other DC films and scores, and doesn't mesh well with what fans have come to expect from DC's superhero movies. Granted, the movie isn't exactly like other DC films, and there's no way to predict what people would come to expect.\n\nThe movie is full of fun and action, so it's only fitting that the score reflects that and that it has a big, loud, rock 'n' roll sound. If it had an emotional and subdued soundtrack, it wouldn't be a good fit for the movie or the characters.\n\nWhile Zimmer may have done an excellent job with the music in the movie, it's not necessarily the best soundtrack or music that fits the film. Not that it was his fault or that it was his decision, but the movie's soundtrack is definitely lacking.\n\nThis is because they were trying to keep the movie as secretive as possible, and didn't want anyone to know what the ending was going to be.\n\nIn all honesty, it's not necessarily a bad idea, and most people don't care about the soundtrack anyway. It was the choice of song that people took issue with, and for good reason.\n\nThat said, it doesn't change the fact that the song is pretty good, and it's actually one of the better songs on the soundtrack, which doesn't say much for it.\n\nFor those who haven't seen the movie, the song is one of the more emotional songs on the soundtrack. It's also the first one that plays, and it's used to set the tone of the movie, which is definitely a major part of the movie.\n\nIn the beginning of the movie, when Bruce Wayne is discussing Superman with Alfred, he says, "They\u2019ll fight. They\u2019ll kill. And when it\u2019s over, the world will be broken. We have to stop them."\n\nAnd then the song kicks in with a pretty sad tune, almost as if Bruce is predicting the future. It's an emotional and heavy song that sets the tone for the rest of the movie, and it fits the mood perfectly.\n\nIn the beginning, Clark Jr. is just talking about fighting, and while it sounds fine, it lacks the raw emotion and angst that the song needed to convey.\n\nWhen Clark sings, "They\u2019ll fight. They\u2019ll kill. And when it\u2019s over, the world will be broken," the lyrics don't sound like they have any emotion or that the artist is really singing them. They just sound like he's repeating what's in the song without any real feeling behind it.\n\nIn the soundtrack version, Clark sounds like he's trying to convey emotion and feeling, and he sounds like he's actually singing the song instead of just reciting it.\n\nWhile the soundtrack version is much more emotional and powerful, the soundtrack version is just not as well done as the cover version. It's still one of the better songs on the soundtrack, but the difference in emotion and quality is quite noticeable.\n\nHopefully, the cover version isn't the final version of the song, and there will be an official version of the soundtrack that includes more of the score, and hopefully that version of the song.\n\nEither way, the movie is still amazing, and fans will just have to deal with what they get when the soundtrack is released.\n\nBatman V Superman: Dawn of Justice is now playing in theaters.]" time="0.339"><properties><property name="score" value="0.163470715" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[There are probably a lot of family members in your life that are into DIY projects. Maybe they do it as a hobby or maybe they do it to make money, but they\u2019ve got a love of it. The DIYer in your life might even be the one who got you into DIY projects!\n\nBut no matter how much they love DIY, they probably aren\u2019t a fan of messy rooms. For someone who enjoys crafting and building, having to clean up after a project is a bummer. It\u2019s not fun. And that\u2019s why the present is a better choice. You can give them something that will help them keep the space where they work clean and organized.\n\nThere are a ton of cool accessories that are perfect for helping a DIYer stay organized. Here are ten ideas that will make great gifts.\n\n1. Floating Drawer Units\n\nThe drawers can pull out on these, which makes them super easy to use. You can find them in different colors to match the d\xe9cor of your home. It\u2019s the perfect solution for messy spaces.\n\n2. Bathroom Storage Systems\n\nThis one will make any bathroom space look way more organized. The drawer system can be moved around. You can use them to store different things. These can be found in different styles to fit your taste.\n\n3. Magnetic Strip\n\nThis one is great for the kitchen. The magnets are so strong, you can stick any metal object to it. It will make the space look super organized. You can even find some that have compartments for extra organization.\n\n4. Baskets\n\nThese baskets are super cute. They\u2019re super useful, too. You can use them for storing anything in your home. The colors are so great and they\u2019re super cheap! They\u2019ll make a great gift for someone who loves to be organized.\n\n5. Wire Baskets\n\nThese baskets are also really great for organizing things. They\u2019re really easy to store, too, because of the shape. You can use them for anything, so they\u2019re super versatile. They\u2019ll be useful for just about anyone.\n\n6. Rolling Cart\n\nThis cart is great for making an organized workspace in your home. You can store a ton of different supplies and it makes it super easy to use everything in your collection. This one is good for any space, but it\u2019s really helpful for people who do a lot of crafts.\n\n7. Rolling Organizers\n\nThis one is a little bigger than the last one, but it\u2019s also a lot more useful. You can store even more craft supplies and equipment. It also makes it super easy to see everything you have in your collection.\n\n8. Bench\n\nThe bench is a great way to store all of your supplies,]" time="0.321"><properties><property name="score" value="0.037497286" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Image caption The number of cats killed has increased\n\nA ban on letting your cat roam free is to be introduced across Scotland.\n\nLocal authorities have been instructed to write to cat owners whose pets are not microchipped, neutered and kept on a lead in a designated area.\n\nIt follows a campaign by animal charities and the Scottish government to tackle the problem of feral cats.\n\nThe number of cats being killed in Scotland has increased from 48,000 to 62,000 in the last three years.\n\nEnvironment Secretary Richard Lochhead said: "Tackling the issue of feral and stray cats is a complex problem and that is why I instructed the Scottish government's Chief Veterinary Officer to establish a Stray and Feral Cat Working Group.\n\n"That group has looked at the issue in depth and has made recommendations to me on how to tackle the problem.\n\n"The focus of these recommendations is on encouraging responsible pet ownership, working with animal welfare groups and local authorities to educate owners, micro-chip and neuter their cats and keep them inside at night."\n\nTwo of Scotland's cat charities, Cats Protection and the Scottish Cat Action Trust, have been working with the government.\n\nFeral cat facts Domestic cats introduced into Scotland by farmers over the centuries.\n\nCats and humans have shared a close relationship for thousands of years.\n\nDomestic cats brought food into the home and acted as rodent controllers.\n\nThe cat has a reputation for independence and self-reliance.\n\nCats have the same needs as humans and require regular food, water and shelter.\n\nThe majority of cat owners are responsible.\n\n"We have been campaigning for a stray cat management law since 2006," said Cat Protection's George Henry.\n\n"We are delighted that, thanks to the efforts of Scottish ministers, many Scottish local authorities have put cat licensing schemes in place and that these are now being extended to cover all of Scotland.\n\n"This means that by next spring, owners of non-neutered cats found wandering will be breaking the law, rather than just failing to meet good practice.\n\n"We believe that this is an essential step towards dealing with the cat population explosion in Scotland and helping to control the suffering of stray and feral cats.\n\n"As a leading cat welfare charity in Scotland, Cats Protection is committed to continuing to work with the Scottish government and other groups to help reduce the population of stray and feral cats and help to rehome more cats."\n\nThe Scottish government is giving \xa3200,000 to the Edinburgh and Lothians region to fund neutering schemes over the next year.\n\nIt has also given money to Strathclyde and Tayside to fund neutering and management plans.]" time="0.351"><properties><property name="score" value="0.115453504" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.1154535 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.1154535
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A new report claims that health insurance premiums will skyrocket for millions of Americans if the Senate's version of Trumpcare becomes law.\n\nSenate Majority Leader Mitch McConnell (R-KY) plans to call a vote on the Better Care Reconciliation Act this week, despite the fact that the bill remains a secret to everyone except a small group of GOP senators who have been allowed to view it in a private room on Capitol Hill.\n\nIn a new report, the Center for American Progress (CAP) estimates that the cost of the second-cheapest silver plan on the individual insurance market would rise an average of 34 percent under the GOP bill. In Arizona, for example, the monthly premium for a 27-year-old purchasing a silver plan would go from $208 a month under the Affordable Care Act to $277.41 under the Senate's version of Trumpcare.\n\nAccording to CAP, the "modest" subsidies included in the bill \u2014 ranging from $2,000 to $4,000 \u2014 would do little to protect Americans from soaring premiums. They note that the $2,000 subsidy would cover just a quarter of the premium cost for the average individual with an annual income of $28,000, leaving the individual on the hook for $6,500.\n\n"Subsidies in the Senate bill are woefully inadequate for low- and middle-income Americans, and actually leave many people with higher costs and worse coverage," said Judith Solomon, vice president for health policy at CAP, and a former top official at the Centers for Medicare and Medicaid Services under President Obama.\n\nTrumpcare is intended to lower premiums for younger, healthier Americans by slashing Medicaid, eliminating subsidies for insurance purchased on the individual market, and allowing insurers to charge older customers more for coverage.\n\nBut while premiums for young people may decrease, they are likely to go up substantially for older people, according to a report by the Congressional Budget Office released on Monday.\n\n"Older people are going to have to pay a heck of a lot more," an anonymous insurance industry source told Axios. "I don't think the math works."]" time="0.316"><properties><property name="score" value="0.013419051" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01341905 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01341905
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A man who had been charged in connection with the shooting of a Douglas County deputy during a traffic stop was found dead in his cell early Tuesday, officials said.\n\nMatthew Riehl, 37, was found unresponsive in his cell at the Denver Detention Center at about 3:45 a.m., a spokeswoman for the Denver Department of Safety said in a news release.\n\nHe had been alone in his cell when he was found and did not have any other inmates in the cell with him, said Daelene Mix, the spokeswoman.\n\nRiehl had been arrested on Dec. 31 after a shooting at Copper Canyon Apartments, 9700 E. County Line Road in Highlands Ranch.\n\nDouglas County Sheriff Tony Spurlock said the shooting was not random and Riehl targeted the deputy.\n\nDeputy Zackari Parrish, 29, was among the four people shot during the incident. He was taken to a hospital and died.\n\nParrish, a husband and father, was a three-year veteran of the department and a former a Castle Rock police officer. He is survived by his wife, Brandi, and their two young sons, Landon and Lucas.\n\nA procession of law enforcement officers escorted his body from Littleton Adventist Hospital to the coroner\u2019s office Tuesday afternoon.\n\nHis body was taken to St. Christopher\u2019s in Parker, where he will be honored during a service Wednesday morning.]" time="0.310"><properties><property name="score" value="0.007937763" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00793776 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00793776
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This article is over 2 years old\n\nBudapest prosecutors on Wednesday ordered the arrest of 13 alleged supporters of the US-based cleric Fethullah G\xfclen, who is blamed for the July 15 attempted coup, in raids at an air base, state television reported.\n\nSeparately, the president of the union of public workers, \xd6zg\xfcr \xd6zel, said more than 900 police officers had been suspended on suspicion of links to the alleged coup. He did not say where the arrests and suspensions occurred.\n\nTurkey\u2019s purge since failed coup has number of Western allies concerned Read more\n\n\u201c900 is the tip of the iceberg,\u201d he told a news conference in Ankara, adding that more than 100,000 public workers, from pilots and doctors to academics and security staff, had had their access to state secrets suspended.\n\nMore than 13,000 people have been detained and more than 36,000 dismissed or suspended in Turkey\u2019s crackdown following the coup. Turkey blames G\xfclen, a former ally of President Recep Tayyip Erdo\u011fan, and his followers for orchestrating the attempt to overthrow the government.\n\nAuthorities on Wednesday banned academics from travelling abroad and suspended 13,000 police officers over suspected links to the G\xfclen movement, according to a decree published in the government\u2019s official gazette.\n\nTurkey also issued an arrest warrant for the US-based Islamic cleric Fethullah G\xfclen, who is blamed for the coup attempt, state-run Anadolu Agency reported.\n\nThe interior ministry published a decree to \u201cban the travel of academics who are suspected of terrorist links\u201d and to \u201cclose the Turkish border to academics who are abroad and suspected of terrorist links\u201d.\n\nIt also ordered the suspension of more than 13,000 police officers over suspected links to the G\xfclen movement.\n\nSince the July 15 coup attempt, Turkish authorities have arrested 40,000 people and have suspended or dismissed more than 100,000, including soldiers, police officers, teachers and public servants.\n\nAnkara has been angered by Washington\u2019s failure to hand over US-based cleric G\xfclen. The US says Turkey lacks sufficient proof of his alleged involvement in the failed coup.\n\nThe rector of Istanbul University, Suleyman Demirel, and former Istanbul governor Huseyin Avni Mutlu were among those sacked from their jobs.\n\n\n\nMeanwhile, Turkey\u2019s EU minister, \xd6mer \xc7elik, said that Ankara is not backing down from its demand for the extradition of G\xfclen.\n\nThe 75-year-old cleric lives in self-imposed exile in the US state of Pennsylvania.\n\n\u201cIt is Turkey\u2019s right to demand the extradition of the leader of a terrorist organisation,\u201d \xc7elik said in a speech to a parliamentary commission in Ankara. \u201cThere is no change in our stance.\u201d\n\nEuropean Commission chief Jean-Claude Juncker said on Tuesday that Turkey was a valued member of the EU and its prospects of joining the bloc were not \u201ctaboo\u201d.\n\nBut he added that Ankara should not overreact to the coup attempt or its aftermath.\n\nThe US and EU]" time="0.320"><properties><property name="score" value="0.003120182" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00312018 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00312018
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u6bd4\u7279\u5e01\u6218\u706b\u518d\u5ea6\u71c3\u8d77\uff01\u8fd9\u4e2a\u52a8\u8361\u7684\u65f6\u4ee3\uff0c\u7b80\u76f4\u662f\u4e00\u4e2a\u201c\u7a0b\u5e8f\u5458\u7684\u5929\u5802\u201d\u3002\u4ed6\u4eec\u6b63\u5728\u626e\u6f14\u7740\u6bd4\u9ed1\u5ba2\u4eec\u8fd8\u8981\u91cd\u8981\u7684\u89d2\u8272\u3002\n\n\u4eca\u5929\uff0c\u4ed6\u4eec\u5c06\u9762\u5bf9\u7684\u6311\u6218\u662f\u66f4\u52a0\u590d\u6742\u7684\u533a\u5757\u94fe\u6280\u672f\uff0c\u66f4\u9ad8\u7ea7\u7684\u6280\u672f\uff0c\u800c\u4e14\u8fd9\u4e9b\u79d1\u5b66\u5bb6\u8fd8\u5c06\u9762\u4e34\u4e0e\u4e16\u754c\u6700\u6709\u7ecf\u9a8c\u7684\u9ed1\u5ba2\u4eec\u7ade\u4e89\u7684\u6311\u6218\u3002\u9ed1\u5ba2\u5728\u63a8\u52a8\u865a\u62df\u8d27\u5e01\u7684\u53d1\u5c55\uff0c\u56e0\u4e3a\u5b83\u662f\u4e00\u79cd\u53ef\u80fd\u7684\u7ecf\u6d4e\u548c\u901a\u8baf\u65b9\u5f0f\u3002\u4f46\u662f\uff0c\u6280\u672f\u4e0a\u7684\u53d1\u5c55\u6b63\u5728\u62d6\u7d2f\u5b83\u4eec\u3002\n\n\u867d\u7136\u516c\u4f17\u7684\u8ba4\u77e5\u4e2d\uff0c\u6700\u5927\u7684\u4e8b\u4ef6\u4ecd\u7136\u662f\u6bd4\u7279\u5e01\u4ea4\u6613\u6240\u4e2d\u7684\u75c5\u6bd2\u6218\u4e89\u3002\u90a3\u53ea\u662f\u4e00\u4e2a\u4e3a\u671f\u51e0\u5468\u7684\u4e8b\u4ef6\u3002\u6bd4\u7279\u5e01\u7528\u6237\u6301\u7eed\u906d\u53d7\u75c5\u6bd2\u5165\u4fb5\u4e86\u51e0\u4e2a\u6708\u3002\n\n\u6700\u8fd1\u7684\u6570\u5b57\u653f\u5e9c\u53d1\u8a00\u4eba\uff0c\u540d\u4e3a\uff0c\u201c\u6bd4\u7279\u5e01\u7ba1\u7406\u4eba\u516c\u4f17\u90ae\u4ef6\uff08BitcoinMasters\uff09\u201d\u5199\u9053\uff1a\u201c\u4e8b\u5b9e\u4e0a\uff0c\u5b83\u53ef\u4ee5\u4f7f\u5f97\u6bd4\u7279\u5e01\u65e0\u6cd5\u4fe1\u4efb\uff0c\u56e0\u4e3a\u5176\u8f6f\u4ef6\u66f4\u65b0\u4e0d\u7a33\u5b9a\uff0c\u8fd9\u5c31\u610f\u5473\u7740\uff0c\u53ea\u8981\u4e00\u4e2a\u653b\u51fb\u8005\u60f3\u635f\u5bb3\u5176\u4f7f\u7528\uff0c\u8fd9\u662f\u975e\u5e38\u5bb9\u6613\u505a\u5230\u7684\u3002\u201d\n\n\u4f46\u662f\uff0c\u6bd4\u7279\u5e01\u4ecd\u7136\u662f\u4e00\u4e2a\u5f00\u653e\u7684\u7cfb\u7edf\uff0c\u8fd9\u610f\u5473\u7740\uff0c\u9ed1\u5ba2\u53ef\u4ee5\u4e3a\u5b83\u521b\u9020\u4e0d\u53ef\u4fe1\u4efb\u7684\u865a\u62df\u8d27\u5e01\u3002\n\n\u4f46\u662f\uff0c\u6bd4\u7279\u5e01\u4ecd\u7136\u662f\u4e00\u4e2a\u5f00\u653e\u7684\u7cfb\u7edf\uff0c\u8fd9\u610f\u5473\u7740\uff0c\u9ed1\u5ba2\u53ef\u4ee5\u4e3a\u5b83\u521b\u9020\u4e0d\u53ef\u4fe1\u4efb\u7684\u865a\u62df\u8d27\u5e01\u3002\n\n\u4e00\u4e9b\u8d28\u7591\u8005\u8868\u793a\uff0c\u53ea\u8981\u6bd4\u7279\u5e01\u4e0d\u516c\u5f00\u8ba8\u8bba\u5176\u8bbe\u8ba1\uff0c\u90a3\u4e48\u5b83\u5c06\u6c38\u8fdc\u5904\u4e8e\u4e00\u79cd\u672a\u77e5\u7684\u72b6\u6001\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4f1a\u53d7\u5230\u9ed1\u5ba2\u7684\u653b\u51fb\u3002\n\n\u5b9e\u9645\u4e0a\uff0c\u82e5\u8981\u5b8c\u5168\u786e\u5b9a\uff0c\u6bd4\u7279\u5e01\u662f\u5426\u6709\u6548\uff0c\u5176\u8f6f\u4ef6\u7684\u5f00\u53d1\u8005\u5fc5\u987b\u5f00\u653e\u8ba8\u8bba\u5b83\u3002\n\n\u73b0\u5728\uff0c\u8fd9\u4e2a\u95ee\u9898\u6b63\u5728\u88ab\u63d0\u51fa\uff0c\u5c31\u5728\u6570\u5b57\u653f\u5e9c\u9886\u5bfc\u8005\u7684\u5730\u76d8\u4e0a\u3002\n\n\u8fd9\u79cd\u63a5\u8fd1\u7684\u63d0\u51fa\u5728\u6570\u5b57\u653f\u5e9c\u5708\u5b50\u4e2d\u5f15\u53d1\u4e86\u4e0d\u5b89\u548c\u4e0d\u900f\u660e\u3002\u5b83\u5c06\u5f15\u53d1\u66f4\u591a\u7684\u8d28\u7591\uff0c\u5e76\u5c06\u652f\u6301\u8fdb\u4e00\u6b65\u7684\u5bf9\u8bdd\u3002\n\n\u4e3a\u4e86\u4fdd\u6301\u6700\u65b0\u7684\u6bd4\u7279\u5e01\u65b0\u95fb\uff0c\u5173\u6ce8\u6211\u4eec\u7684\u8d26\u53f7@BitcoinMagazineIT\u3002\n\n\u4e8b\u4ef6\u7b80\u8ff0\n\n\u6bd4\u7279\u5e01\u7684\u57fa\u7840\u7cfb\u7edf\uff0c\u5305\u62ec\u6bd4\u7279\u5e01\u548c\u6bd4\u7279\u5e01\u7f51\u7edc\uff0c\u6b63\u5728\u88ab\u9ed1\u5ba2\u653b\u51fb\u3002\n\n\u5bf9\u6bd4\u7279\u5e01\u9ed1\u5ba2\u7684\u653b\u51fb\u662f\u5728\u6bd4\u7279\u5e01\u5e7f\u6cdb\u4f7f\u7528\u4e4b\u524d\u5f00\u59cb\u7684\uff0c\u4f46\u662f\u8fd9\u4e9b\u653b\u51fb\u66f4\u52a0\u590d\u6742\u4e86\uff0c\u6700\u7ec8\u5bfc\u81f4\u6bd4\u7279\u5e01\u7f51\u7edc\u6ca1\u6709\u6301\u7eed\u6b63\u5e38\u8fd0\u4f5c\u3002\n\n\u5176\u4ed6\u6bd4\u7279\u5e01\u653b\u51fb\u8005\u8fd8\u505a\u4e86\u66f4\u591a\u7684\u4e8b\u60c5\u3002\n\n\u9ed1\u5ba2\u8fd8\u8bd5\u56fe\u8fd0\u7528\u4ed6\u4eec\u7684\u673a\u5668\u7cfb\u7edf\u5bf9\u6bd4\u7279\u5e01\u4ea4\u6613\u6240\u5b9e\u65bd\u653b\u51fb\uff0c\u5e76\u5229\u7528\u75c5\u6bd2\u7684\u624b\u6bb5\u5728\u5176\u4e2d\u7834\u574f\u4ea4\u6613\u6240\u7684\u8fd0\u4f5c\u3002\n\n\u8fd9\u4e9b\u89d2\u8272\u5728\u8fc7\u53bb\u51e0\u5468\u7684\u75c5\u6bd2\u6218\u4e89\u4e2d\u53d7\u5230\u4e86\u5e7f\u6cdb\u5173\u6ce8\uff0c\u56e0\u4e3a\u6bd4\u7279\u5e01\u88ab\u9ed1\u5ba2\u7834\u574f\u4e86\uff0c\u5bfc\u81f4\u4e86\u8d22\u52a1\u635f\u5931\u3002\n\n\u8fd9\u4e9b\u653b\u51fb\u5df2\u7ecf\u5bfc\u81f4\u6bd4\u7279\u5e01\u7f51\u7edc\u88ab\u9ed1\u5ba2\u653b\u51fb\u3002\u9ed1\u5ba2\u7684\u7b2c\u4e00\u6b21\u884c\u52a8\u662f\u5229\u7528\u533f\u540d\u7f51\u7edcTor\u6765\u7a83\u53d6\u6bd4\u7279\u5e01\u4ea4\u6613\u6240\u7684\u6570\u636e\u5e93\u548c\u4ea4\u6613\u548c\u8f6c\u8d26\u7684\u4fe1\u606f\uff0c\u5e76\u8bd5\u56fe\u963b\u6b62\u6bd4\u7279\u5e01\u4ea4\u6613\u6240\u63a5\u6536\u6bd4\u7279\u5e01\u3002\n\n\u8fd9\u4e9b\u9ed1\u5ba2\u88ab\u79f0\u4e3aThe Accused\u3002\n\n\u6bd4\u7279\u5e01\u4ea4\u6613\u6240\u4e2d\u7684\u75c5\u6bd2\n\n\u6bd4\u7279\u5e01\u9ed1\u5ba2\uff0cThe Accused\uff0c\u5728\u524d\u51e0\u5468\u88ab\u8ba4\u4e3a\u662f\u6bd4\u7279\u5e01\u653b\u51fb\u7684\u4e3b\u8981\u52a8\u673a\u3002\n\nThe Accused\u53d1\u5e03\u4e86\u4e00\u4e2a\u540d\u4e3a\uff1aHac\uff0c\u7684\u7a0b\u5e8f\uff0c\u4e3a\u6bd4\u7279\u5e01\u7f51\u7edc\u521b\u5efa\u4e86\u4e00\u4e2a\u9690\u85cf\u7684\u7f51\u7edc\u3002\n\nThe Accused\u4f7f\u7528Hac\u521b\u5efa\u4e86\u4e00\u4e2a\u65b0\u7684Tor\uff0c\u7f51\u7edc\uff0c\ufffd]" time="0.466"><properties><property name="score" value="0.074160926" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07416093 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07416093
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u201cDespite the apparent difficulty and diversity of the problems facing our national church, the outcome of our recent Lambeth Conference has to be seen as a positive one.\n\n\u201cMany new members of the Communion\u2019s episcopate have been recruited from the developing world. The church in Africa, in particular, is proving an attractive mission field for some Anglicans from Britain and the US.\n\n\u201cMoreover, the conference gave important support to our already announced policy of sanctioning certain developments in same-sex relationships. While still condemning homosexual practice as sinful, we showed compassion for those whose orientation towards same-sex relationships is unchangeable.\n\n\u201cWe were determined that, where there are those in the church who wish to bless such relationships, they should be able to do so.\n\n\u201cThe Anglican Church is a church of variety, but it is a powerful testimony to God\u2019s working. The God we serve is greater than our human divisions.\u201d\n\nThe Bishop of London is the sole Church of England bishop to attend every meeting of the Lambeth Conference, one of the two Communion gatherings that occur every ten years. In 1999 the bishop was appointed as the convenor of the Lambeth Conference by the Archbishop of Canterbury.\n\nBishop Chartres has been the Anglican Bishop of London since 1997. Prior to that he was the Bishop of Stepney and then the Bishop of Monmouth. He was ordained in 1973 and served his first curacy at St Andrew\u2019s Notting Hill.\n\nFrom 1976 to 1982 he was the curate of St Saviour\u2019s West Kensington and from 1982 to 1987, the vicar of St Michael\u2019s Margate. From 1987 to 1993 he was the diocesan missioner for Stepney, and from 1993 to 1997 he was the dean of St Paul\u2019s Cathedral.\n\nBishop Chartres also writes a weekly column for the Church Times, and he is a trustee of the National Council for Social Service. He is married to Penny and has a son and daughter.\n\nENDS\n\nNotes to editors:\n\nContact 020 7886 1291\n\nRt Revd Richard Chartres, Bishop of London\n\nThe Anglican Communion, or the Anglican Church, is a global communion of autonomous self-governing churches in the Anglican tradition. There are about 77 million Anglicans in more than 160 countries across the world.\n\nThe Anglican Church in England is part of the Anglican Communion.\n\nThe Archbishop of Canterbury is the \u2018first among equals\u2019 of the worldwide Anglican Communion.\n\nThe Archbishop of Canterbury\u2019s official website is www.archbishopofcanterbury.org.]" time="0.312"><properties><property name="score" value="0.0050245556" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00502456 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00502456
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Title: Remember Me?\n\nAuthor: mistymidnight\n\nSummary: Buffy's getting all those amazing visions she got in the Mayor's office, only they're getting more specific\u2026 Now if only she could remember how to use them.\n\nRating: T\n\nDisclaimer: The characters you recognize are the property of Joss Whedon, Mutant Enemy, and various networks. The rest are mine.\n\nFeedback: Please. Good or bad, I'd like to hear it.\n\n"So what's the plan?"\n\n"I don't know."\n\nBuffy lowered her hand from her face. She and Xander were sitting in his car. She'd just come back from the doctor. She thought that she was finally remembering how to act like a normal human being. She thought that she was finally remembering how to feel like a normal human being.\n\nXander touched her shoulder. "What did the doctor say?"\n\n"Nothing." Buffy shrugged. "They didn't do a thing. They were just doing a routine check-up."\n\n"Checking up on you, huh?"\n\nBuffy frowned. "What's that supposed to mean?"\n\n"Nothing."\n\n"No, come on, Xander. Say what you want to say. This is why I don't like talking to you."\n\nXander flinched and started the car. "Sorry. It's nothing."\n\n"What do you think they're really doing? Do you think they're trying to find a way to get Spike and Dru out of my head?"\n\n"I doubt it." Xander's voice was soft. "I think they just want to see if your brain's still in there."\n\nBuffy winced. She hated when he put it that way. But Xander was right. They didn't want her here. She knew they didn't want her here. Why else would they do this? Why else would they make her go through the routine that every other person with brain damage goes through?\n\nBuffy reached over and turned on the radio. She turned it up, blocking out Xander's annoying voice.\n\nThey didn't want her here. They didn't care about her. It was all just a game.\n\nXander sighed. He was glad Buffy was back. He was so glad she was back. But he still couldn't help feeling bad for her. He couldn't help but worry about what would happen to her when this was all over. He couldn't help but wonder if he would be able to stop himself from hurting her when this was all over.\n\nHe drove around aimlessly. "Do you want to talk about it?"\n\n"About what?" Buffy asked absently.\n\n"About what's bothering you."\n\nBuffy sighed. "Why does something have to be bothering me?"\n\nXander smiled. "You're Buffy. I know you better than you know yourself."\n\n"Oh." Buffy thought about that for a moment. It was true, she supposed. She was Buffy, and Xander was right. She couldn't remember everything about her old life, but she remembered Xander. She remembered him more than anyone else. "So what is it? I mean, you're not usually this\u2026chummy with me."\n\n"I was worried about you."\n\n"No, I mean\u2026" Buffy shook her head. "You know what I mean. It's about what I said at the hospital, isn't it? You think I should leave Sunnydale, right?"\n\n"What?" Xander was taken aback. "No! Of course not!"\n\n"Xander, I'm not even really here."\n\n"So? That doesn't matter. You still live here. I still live here."\n\n"And what happens when I don't anymore? When I leave and you're left behind?"\n\nXander turned the car. "This is what I've been trying to tell you. I'm not leaving."\n\n"Yes, you are."\n\n"No, I'm not."\n\n"Yes, you are. You said it yourself. I'm not even really here."\n\n"Buffy, you are here." Xander pulled into the parking lot of the Magic Box. He shut the engine off and turned to her. "You've always been here."\n\n"No, I haven't." Buffy shook her head. "I was lost. But I'm here now. And I don't think I'm going to stay here for very long."\n\n"Why?" Xander asked.\n\n"Because\u2026" Buffy swallowed. "Because I don't think I belong here."\n\nXander frowned. "You're Buffy. Of course you belong here."\n\n"I'm not Buffy." Buffy tried to get out of the car, but Xander grabbed her wrist. "Let go of me, Xander."\n\n"I'm not going to let you go. You're in no condition to go anywhere."\n\n"What makes you think that? I'm not in a wheelchair, I'm not using a cane. I'm just a little slow."\n\n"That's the thing, Buffy. You're not slow. You're not even there."\n\n"Xander, what are you talking about?"\n\nXander sighed. "Buffy, when you were in the hospital, did you remember anything?"\n\n"Of course I did. The whole time."\n\n"You didn't, Buffy. You couldn't. You had no memory."\n\n"Then how could I have remembered anything?"\n\n"Because your mind is slowly coming back to you." Xander glanced at the front door of the Magic Box. "It's starting to come back to you. And you're going to have to leave."\n\n"So what if I do? What's wrong with that?"\n\n"Nothing. Except that I don't want you to go."\n\n"And you]" time="0.340"><properties><property name="score" value="2.539576" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.539576 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 2.539576
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Cz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr\xf3bki blach Zbrojenia systemowe\n\nCz\u0119\u015bci maszyn do obr]" time="0.347"><properties><property name="score" value="0.0001735385" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[This popular loop hike is rated difficult.\n\nOn the east side of the Laguna Mountains lies the 10,000-acre Cleveland National Forest. Once the private property of the Santa Fe Railway Company, it is now a favorite escape for thousands of visitors each year. Bordered by the Pacific Ocean, the City of San Diego and the San Diego River, it is rich in history.\n\nMore than 6,000 acres are designated wilderness in the Laguna Mountain Wilderness area, the largest wilderness in San Diego County. This area offers solitude in a rare, almost pristine environment of mountains and canyons. The area has two campgrounds, with a total of 34 campsites, and also two wilderness cabins that can be rented. These are popular with hikers and overnight campers alike.\n\nHikers will find more than 20 miles of designated trails, as well as many more unofficial trails. The Pacific Crest Trail, a 2,650-mile-long trail that runs from Mexico to Canada, passes through this area. A popular segment of this trail is the San Diego County portion of the Pacific Crest Trail. The Chiquito Loop Trail is a portion of this trail.\n\nThe Pamo Valley is a unique area, bordered by the Laguna Mountains to the east and Interstate 8 to the west. The mountains are part of a volcanic field that created the mountains and surrounding desert and includes the Volcan Mountains Wilderness Area.\n\nThe Spanish Dons, who ruled this region from 1769 to 1821, named the mountain range La Sierra de la Laguna. The name refers to the Laguna Mountains and to the lake that once existed at the present-day site of Lake Henshaw.\n\nThe Laguna Mountains contain a great deal of desert-like vegetation, such as ocotillo, desert holly and creosote bush. Some sections are forested with all three types of vegetation. The forested areas are home to the ponderosa pine, the largest and most long-lived tree in the United States.\n\nThe unique landscape of the Laguna Mountains includes the many canyons, ridges and mountains, which vary from 4,000 to 6,000 feet in elevation.\n\nCleveland National Forest is one of four national forests in California. The other three are the Angeles, Eldorado and San Bernardino National Forests.]" time="0.362"><properties><property name="score" value="0.7163647" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.7163647 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.7163647
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[PDA View Full Version : VoLTE Ready for Samsung Galaxy S7 Sprint Savy COLD WEATHER UPDATE! Due to the extreme temperatures experienced in the US over the last few weeks and the impact to shipping, we were not able to deliver our regular monthly build to our Sprint customers on Jan. 4th.\n\n\n\nSince then, we have delivered VoLTE updates for our Samsung Galaxy S7 and S7 Edge customers. These devices are now ready for use with VoLTE.\n\n\n\nWe have also started to roll out the monthly update to our Samsung Galaxy S6 and S6 Edge customers with VoLTE enabled. The remaining devices (S6 Active and S6 Duos) will receive VoLTE updates starting in the next few weeks.\n\n\n\nDue to these changes, we will be extending the Android 5.1.1 rollout to the Samsung Galaxy S5 and HTC One M9 on a 4-week schedule. We will begin pushing these updates the week of February 9, 2016.\n\n\n\nIf you own a Samsung Galaxy S5 or HTC One M9, you can check if your phone is ready for VoLTE by heading to your device settings menu and looking for VoLTE near the top of the list. If you do not see VoLTE in the menu, you will need to wait a few weeks for the next update.\n\n\n\nThank you for your patience during this time. We will provide another update with more details about this change by the end of this month. Your patience is appreciated as we work to provide VoLTE service to our customers.\n\n\n\nSprint Savy Hey Guys, due to the cold weather we have encountered several issues with our Samsung models. We have started to push updates to our Samsung models and we hope to have everyone back up and running shortly.]" time="0.403"><properties><property name="score" value="0.44029796" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[12/2/2013\n\nNEWTON, IOWA \u2013 Working for a living. Does it seem like something is missing from our everyday lives? Most of us, most of the time, do not have to think about working.\n\nWe get up, and go to work. There\u2019s always enough time to eat, sleep, go to a ball game or watch a TV show.\n\nThere\u2019s always enough time for that stuff.\n\nWe\u2019ve got no problem with working. In fact, we like it. Most of us do.\n\nThat\u2019s not the issue.\n\nThe issue is the fact that most of us like to earn our keep.\n\nWe like to think we are not being a burden to our society. We like to think we are not living in a free-lunch society.\n\nWe do have a real problem with people who can\u2019t or won\u2019t work.\n\nIn fact, the working public has a real problem with them.\n\nA growing number of those people have some sort of physical or mental disability that makes it impossible for them to work. They have no choice but to rely on the charity of others to survive.\n\nThis is not easy for those who work.\n\nThey have a goodly number of people who just won\u2019t work at all, or will work just long enough to get the public to take care of them. It\u2019s very difficult for those who work to keep their work ethic intact.\n\nIt\u2019s also difficult for those who are disabled to keep their moral fiber intact.\n\nAnd that\u2019s a good thing.\n\nThe hard workers in this society need to be reminded that they are providing a valuable service to society. They need to be reminded that without them society would crumble.\n\nWe also need to keep a place for those who cannot work. That can be difficult because many of those people have learned to rely on their fellow man for a handout.\n\nIt\u2019s up to those who work to keep things in balance.\n\nThat\u2019s not easy.\n\nThe people who work need to keep their perspective.\n\nAnd they need to keep their noses to the grindstone.\n\nThey need to put up with the people who do not want to work and remember that the whole society is better for their labors.]" time="0.335"><properties><property name="score" value="0.82259434" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[No, this isn\u2019t a holiday season complaint from your kids, \u201cSanta isn\u2019t real!\u201d This is a history lesson about a different mythical creature.\n\nWe\u2019ve all heard about vampires. They usually stay in castles. They\u2019re sometimes in France.\n\nBut did you know that before they were vampires, they were werewolves? Werewolves are even worse because they transform into monsters during the full moon!\n\nIt may surprise you to know that werewolves were quite popular in European folklore. People would sometimes actually dress up as werewolves, as part of a holiday. They would often run through the streets of a town, harassing people and destroying property.\n\nSome historians have suggested that the werewolf legends are actually a way of explaining the reality of mental illness. Ironic, because mental illness is often more difficult to cure than an infection by a vampire or a werewolf.\n\nIf you\u2019re looking for an interesting holiday season, go to a werewolf re-enactment. If you\u2019re lucky, you might even catch a glimpse of a werewolf.\n\nWhat would you do if you caught a werewolf? Let us know! We\u2019re glad to discuss all the latest werewolf movies, books and legends!]" time="0.279"><properties><property name="score" value="0.19796021" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.19796021 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.19796021
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In order to successfully use the drones and sensors, which are needed for a safe and efficient inspection of large and complex facilities, a web based analysis and evaluation platform is needed. The platform is called \u201cSAFE-WEB\u201d and is presented in the paper. SAFE-WEB allows an easy registration of sensors and drones. Furthermore, it gives the possibility to integrate and visualize the obtained data. Furthermore, several types of risk analysis are possible in SAFE-WEB. A unique feature is the capability to specify an area, where drones and/or sensors can fly, and to create a risk analysis only for the desired area. This makes it possible to perform an efficient analysis and evaluation of the obtained data. Finally, an example of the application of the risk analysis will be presented. The application is carried out using a 3D model of a Nuclear Facility.\n\n1. Introduction\n\nNuclear power stations represent very large facilities. In general, the normal plant operation comprises many smaller building units. The normal surveillance is, therefore, divided into different parts of the plant and has the advantage that it is not necessary to inspect the whole plant in one time.\n\nIn the paper the 3D model of a nuclear power plant is analyzed and assessed using the available drone and sensor data. The analysis of the model is necessary because the object is used to specify the area for the flight of the drones and to set the risk analysis region.\n\n1.1. Area for Drones\n\nThe advantage of drones for inspections is that they can fly directly in the area, which is of interest. This is not possible using normal manned aircraft. The limitation of drones is that they have to be within the control of the operator. They have to be able to see them in order to be able to control them. The control is needed to avoid collision with other drones or collisions with the buildings of the object. In this paper, two options for the control of the drones are presented. The first is an autonomous flight control and the second is the control via an operator.\n\nFigure 1.1. shows the \u201carea for drones\u201d for the 3D model of the nuclear facility. This area is created by the operator who specifies the region, where drones should be allowed to fly and where the analysis should be performed. For example, the operator can select the area shown in Figure 1.1. and then the drones and sensors are used to perform the analysis and evaluation only in this area.\n\nFigure 1.1. Area for the drones.\n\n1.2. Risk Analysis Region\n\nThe drones and sensors need a clearly specified area to carry out the analysis. The area is called \u201crisk analysis region\u201d. For example, if the operator selects the area shown in Figure 1.1. for the analysis, the drones and sensors fly in this area. Then, the data are gathered and analyzed by the operator. Then, the result is presented to the operator.\n\nIn this paper, two different options for the risk analysis are presented. The first one is an automatic risk analysis, where the user specifies a maximum amount of permissible risk. The second option is the capability to specify a risk analysis region with a boundary, where the area is cut off, where drones and sensors are not allowed to fly. In this paper, the automatic risk analysis is presented.\n\nThe capability to automatically generate the risk analysis region is a great advantage. The operator does not need to know the exact area of interest. He just specifies a general area. The automatic risk analysis can be performed in several levels. The highest level includes several basic items like structural failure, fire, blast and irradiation. This level of analysis is also called \u201csuper-level\u201d.\n\nThe super-level is a very large amount of data. The number of variables is about 25 times the number of variables for the normal risk analysis. Because of this, the super-level is used only if there is a specific need for it.\n\nThe analysis is very useful and important to perform inspections, which will be controlled by drones and sensors. In this paper, the analysis is applied to the nuclear facility shown in Figure 1.2. This nuclear power plant consists of five units. Three of these units are different types of nuclear reactors. The main part of the nuclear power plant is the \u201ccontainment building\u201d which is not shown in Figure 1.2. The small boxes in Figure 1.2 are the different units, which are part of the nuclear facility.\n\nFigure 1.2. Nuclear power plant\n\nIn order to create the analysis, several sensors are used. Figure 1.3 shows the sensors, which are necessary for the analysis of the nuclear facility shown in Figure 1.2. There are four drones which are used to create the top view. Furthermore, there are two sensors which are needed to gather the data for the analysis. One sensor is a small helicopter and the second one is a car. The sensors are used to gather data like radiation, temperatures and stress on the walls of the building.\n\nFigure 1.3. Sensors for the analysis\n\n2. Preparation of the Model for the Analysis\n\nIn this section, the preparation of the model for the analysis is shown.\n\nThe main part of the preparation of the model is to create a map which shows the 3D area. Figure 1.4 shows the map of the model. The big rectangle shows the total area of the nuclear facility. Inside the rectangle, the specific area of interest is shown. The analysis will only be performed inside the area shown in Figure 1.4. The selected area is large enough to allow a safe flight of the drones. The selected area is used to generate the analysis region and it is also used to specify the area for the drones and sensors.\n\nFigure 1.4. Map of the model\n\nIn addition to the area for the drones and sensors, the following must be defined:\n\nThe locations of the drones\n\nThe locations of the sensors\n\nA description of the analysis, which is carried out on the drones and sensors\n\nFurthermore, the model needs to be prepared for the required analysis. To do this, the sensor data and the drone data are to be analyzed.\n\n2.1. Sensor Data\n\nThe sensor data are measured by the sensors in the area, where the analysis is to be performed. The data are gathered by the sensors and then sent to the operator. The operator can analyze the data and then specify the risk analysis area and the risk analysis itself.\n\nThe sensors are used for the following measurements:\n\nRadiation\n\nTemperature\n\nStress on the walls\n\nOne of the important measurements is radiation. The following data are required for the analysis of the radiation:\n\nPeak value\n\nAverage value\n\nArea\n\nFor each measurement, one or more locations are defined. The data are then gathered and a map, which shows the measurement result, is created. Figure 1.5 shows an example of the map. The map shows the radiation measured in one of the locations. In addition, the peak value, average value and the area of the radiation is shown in the map.\n\nFigure 1.5. Example of the map, which shows the measurement results\n\nThe data are shown in a map which has a high resolution. Figure 1.5. shows a map with a resolution of 1m x 1m.\n\n2.2. Drone Data\n\nThe drone data is the result of the data gathered by the drones in the area, where the analysis is to be performed. The data are gathered and the drone control software interprets the data. The results of the data are sent to the operator and they are used to determine the analysis region.\n\nThe data, which are used for the analysis of the drones are:\n\nRadiation\n\nTemperature\n\nStress on the walls\n\nOne of the important data is radiation. The following data are required for the analysis of the radiation:\n\nPeak value\n\nAverage value\n\nArea\n\nFor each measurement, one or more locations are defined. The data are then gathered and a map, which shows the measurement result, is created. Figure 1.6 shows an example of the map. The map shows the radiation measured in one of the locations. In addition, the peak value, average value and the area of the radiation is shown in the map.\n\nFigure 1.6. Example of the map, which shows the measurement results\n\nThe data are shown in a map which has a high resolution. Figure 1.6. shows a map with a resolution of 1m x 1m.\n\n2.3. Analysis of the Drone Data\n\nThe drone data is used to create the analysis region. This is done by specifying the area in which the drone can fly and by creating the risk analysis.\n\nTo do this, the operator creates a map, which shows the drone flight area. Figure 1.7. shows the drone flight area for the 3D model of the nuclear power plant. The flight area has a large size because the drones are controlled by an operator. This means that the drones have to be in the range of the operator\u2019s sight. For this reason, the area has to be big.\n\nFigure 1.7. Drone flight area\n\nThe drone flight area is then used to create the risk analysis. Figure 1.8. shows the risk analysis for the drone flight area. The drone flight area is shown in blue. The analysis is created for the area where the operator can see the drones.\n\nFigure 1.8. Drone flight area and risk analysis\n\nThe operator has several options to create the risk analysis. In this paper, the operator can define a maximum level of permissible risk for the radiation. This means that the risk analysis is carried out automatically. In this way]" time="0.871"><properties><property name="score" value="0.014633637133333334" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Reflexology\n\nReflexology is a holistic modality that focuses on the feet. The hands of a reflexologist do not physically touch the feet of the client. Instead, a client is seated while the reflexologist is behind them and will apply deep pressure, pressure with the ball of the foot, or kneading to the feet and sometimes the legs.\n\nThe objective of reflexology is to restore the body to its natural state of well-being and balance by stimulating certain reflexes. This form of bodywork has its roots in ancient Egypt, India, China and Japan.\n\nReflexology is used in a variety of settings and is gaining in popularity as a complementary therapy for pain management and stress reduction. The action of pressing on reflex points on the feet can reduce tension and release muscle spasms.\n\nA trained reflexologist will be able to balance the energy throughout the entire body and encourage all areas of the body to work in harmony. Reflexology is a gentle and soothing therapy that can be used as an alternative to other more aggressive techniques or as a complementary therapy.]" time="0.270"><properties><property name="score" value="0.14356445" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[The scheme is currently being piloted by West Sussex County Council but aims to be available for everyone in the UK who wants it. The council is aiming to have a potential service area that covers around a quarter of the UK population \u2013 approximately eight million people.\n\nUsers will be able to access the service through an app, for free or for a fee \u2013 although the council has not yet decided on the pricing model \u2013 that will help them identify and arrange home and visiting care.\n\nThe council has already run two tests of the app to look at the system\u2019s usability, and although not all the features of the service have been released, it has been made available to \u201chundreds of people\u201d.\n\nIn the first test, the council asked users to identify what they would find most useful from the app.\n\nThey were also asked to discuss their needs, which in turn helped the council to identify the features that were likely to be most important for users.\n\nThe second test saw the council work with users with more significant health conditions \u2013 although they were not part of a specific group \u2013 and this helped it to further refine the service and identify other potential features, the council said.\n\nIt is now focusing on two potential versions of the app, which is expected to be ready by September 2018.\n\nThe scheme is one of a number of digital offerings that are part of the council\u2019s drive to transform the way it provides public services.\n\nAmong these is a new online service that lets residents book a new council tax or non-tax payers tax in a matter of minutes, as well as new apps that can help them report problems with streets, bins and trees.]" time="0.289"><properties><property name="score" value="0.41509798" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[US Secretary of State Rex Tillerson on Tuesday said the administration of US President Donald Trump will pursue \u201ca very different strategic relationship\u201d with Russia.\n\n\u201cI\u2019d like to talk about a very different topic, and that is Russia. We\u2019ve all been clear in our assessments of Russian meddling in the election. We stand by those assessments,\u201d Tillerson told a Washington news conference.\n\n\u201cAnd we certainly acknowledge the right of each nation to pursue their own foreign policy, and I know that some of the charges that have been levied against the current administration have come from the real policies of the United States.\u201d\n\n\u201cI\u2019d like to offer assurances of the American people. This administration has its own approach,\u201d he said.\n\n\u201cI don\u2019t think it is useful to be doing a tit-for-tat with this,\u201d Tillerson said.\n\n\u201cThere has to be a degree of respect in how we approach each of these relationships,\u201d he added. \u201cIf there is not respect, that doesn\u2019t create an environment for the way we do things.\u201d\n\n\u201cWe are not asking for recognition of a new cold war, or a new anything. We\u2019re just asking for respect of each others\u2019 interests and that we work together,\u201d Tillerson said.\n\nUS President Donald Trump had on Tuesday called for the restoration of a joint US-Russia ceasefire in Syria, a rare show of cooperation between the two world powers.\n\nTrump, during a meeting with King Abdullah II of Jordan, also warned that the Islamic State of Iraq and Syria (ISIS) must be destroyed.\n\n\u201cSyria is waiting for the United States, and we hope they will not disappoint us,\u201d he said, indicating he wants Russian President Vladimir Putin to engage the United States to destroy ISIS.\n\n\u201cAs far as Syria is concerned, the world is going to have to come together, and we have to stop the killing and the death,\u201d he added. \u201cWe have to stop the gas.\u201d\n\n\u201cI think that Russia will make a big difference,\u201d Trump added.\n\n\u201cThis is not a question of us backing out,\u201d he added. \u201cI want to get as many to (ISIS) as possible. I want to get the Middle East in general to get rid of it.\u201d\n\n\u201cBut I think Russia will have a great influence over Syria. And to that end, if it is going to be an attack on the United States, it will be an attack on the United States. You can\u2019t change that,\u201d Trump warned.\n\nTrump, who has repeatedly expressed admiration for Russian President Vladimir Putin, also indicated he wants the United States and Russia to work together on destroying ISIS.\n\n\u201cIt\u2019s an honor to have King Abdullah of Jordan and his representatives with us. We\u2019ve had tremendous relations with Jordan,\u201d he said.\n\n\u201cOne of the things that we will discuss is the fact that we would love to have the Russians in a partnership in working out Syria, and if that happens, that will be a great thing,\u201d Trump added.]" time="0.270"><properties><property name="score" value="0.048387807" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04838781 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.04838781
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[In these reports, we have presented new data and evaluated and reinterpreted data from previous studies to identify a common pathway by which calcium dysregulation leads to increased risk of disease. Two data sources we present here are as follows.\n\nWe have shown the strong association between cardiovascular and other diseases and calcium dysregulation in the United States in both men and women by estimating the prevalence of hypertension and calcium dysregulation based on a large and well-defined population of middle-aged adults. Our finding that the prevalence of calcium dysregulation, i.e., a positive response to one or more questions, was 4.1% in men and 4.3% in women was comparable to a number of other previous studies. We reported for the first time that age, race, and disease all modified the association between hypertension and calcium dysregulation.\n\nAnother novel finding in this study was that calcium dysregulation was not associated with increased mortality in middle-aged men but was associated with increased mortality in middle-aged women. The former finding suggests that the adverse health effects of hypertension and calcium dysregulation are equivalent in men and women and therefore the differences in the prevalence of these factors by sex should be considered when evaluating the associations of hypertension and calcium dysregulation with disease. The latter finding, i.e., increased mortality in women with calcium dysregulation, has been shown in prior studies [3, 4, 15, 29, 30].\n\nThe observed associations of calcium dysregulation with hypertension, diabetes, and heart disease are the same in men and women, and the associations with stroke, coronary artery disease, and kidney disease are equivalent. This suggests that the mechanisms by which these associations occur in men and women are similar. This would be expected because the calcium levels in blood are, to a large extent, regulated in a similar way in both men and women, i.e., by calcium binding proteins [20]. However, we cannot exclude the possibility that the associations are different in men and women because they may be due to different distributions of risk factors in men and women or because they may reflect different amounts of disease in the two sexes. For example, the correlation between calcium dysregulation and hypertension, diabetes, and coronary artery disease may be different in men and women because the disease prevalence is different. Also, the amount of calcium dysregulation may be different in men and women, for example, because of differences in serum calcium levels. It would be important to further study the relationship between calcium dysregulation and various diseases in men and women to confirm our finding.\n\nThe association between calcium dysregulation and mortality was stronger in men with hypertension than in men without hypertension, although the associations were similar in men with and without hypertension in women. The reason for this is unknown. However, these findings are consistent with previous findings that the association between hypertension and mortality is stronger in men than in women [31, 32, 33]. We also found that calcium dysregulation was associated with increased mortality in middle-aged women but not in middle-aged men. This is consistent with the findings of a previous report that the association between calcium dysregulation and mortality is stronger in middle-aged women than in middle-aged men [34]. This could be due to the fact that a stronger association between calcium dysregulation and mortality in middle-aged women is due to a stronger association between calcium dysregulation and hypertension in middle-aged women than in men. Also, the stronger association between calcium dysregulation and mortality in middle-aged women than in middle-aged men could be due to a stronger association between calcium dysregulation and mortality in women who are at an advanced age, especially when hypertension has already developed.\n\nBecause calcium dysregulation was associated with increased mortality in women, we evaluated the possibility that the association between calcium dysregulation and mortality was due to undiagnosed hypertension or hyperglycemia. In fact, we did]" time="0.335"><properties><property name="score" value="0.00020824855" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Today we review one of my favorite paleo treat \u2013 the Paleovalley\u2019s Chocolate Chip Cookie Dough.\n\nAs you may know, I\u2019m a huge fan of Paleovalley\u2019s. For my experience with Paleovalley, go check out this post!\n\nLike many Paleo eaters, I really missed having cookies on the go \u2013 paleo or not.\n\nWhen I heard that Paleovalley made Paleo Chocolate Chip Cookie Dough, I was instantly excited. But I wanted to know if it was really worth the hype and the price.\n\nThe reason I like paleo-friendly treats so much is because I can have them on the go or right out of the fridge.\n\nAnd because I\u2019m a busy mom who needs snacks.\n\nWhen I opened the jar and tried the Paleovalley\u2019s Chocolate Chip Cookie Dough for the first time, I was sooo surprised.\n\nUsually, anything coconut-based has a weird taste to me, so I was prepared for this.\n\nBut the cookie dough was really tasty.\n\nI was even more surprised when I found out that there were no refined sugar, preservatives, and not even refined flour.\n\nIt\u2019s made with a blend of real vanilla, butter, and coconut oil and sweetened with dates.\n\nI\u2019m definitely ordering a box or two of the Paleo Chocolate Chip Cookie Dough soon.\n\nAnd it\u2019s available in four flavors \u2013 Paleo Chocolate Chip, Cinnamon Raisin, Apple Cinnamon, and Coconut.\n\nI have yet to try the other three.\n\nAt about $6/jar, it\u2019s a little bit more expensive than buying it at Whole Foods or other retailers. But when I\u2019m in a pinch and need something to go, the price is well worth it!\n\nDid you try the Paleovalley\u2019s Chocolate Chip Cookie Dough yet?\n\nDo you think you\u2019ll try it?\n\nAlso Read: Paleo Sandwich Breads]" time="0.292"><properties><property name="score" value="0.025766827" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02576683 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.02576683
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[BARRETT CITY MAN SENTENCED TO 42 YEARS FOR SEXUALLY ASSAULTING BOY\n\nA Barre City man was sentenced to 42 years in prison after pleading guilty to sexually assaulting a 10-year-old boy in the fall of 2012.\n\nWilliam Fogg, 59, of 79 Florence Road, pleaded guilty to aggravated sexual assault of a child on Thursday, Feb. 27, in Washington County criminal court. He was sentenced to 42 years, suspended after 32 years, and 10 years of probation. He was ordered to pay $1,000 in court costs.\n\nAccording to an affidavit by Vermont State Police Detective Daniel Walker, the assault occurred in Barre City in October 2012. The child told police the assault had happened in Fogg\u2019s residence.\n\nFogg told police in an interview that the boy had been staying with him, but denied any sexual contact had taken place. Police conducted a search of Fogg\u2019s residence and found no evidence of child pornography.\n\nJudge Thomas Zonay said he had seen the \u201cblack and white\u201d of the crime and knew the difficult road the victim was going to have to travel.\n\n\u201cYou have caused great harm to a 10-year-old child,\u201d Zonay said. \u201cIf there was ever a predator, it is you.\u201d\n\nFogg was sentenced under the state\u2019s Three Strikes Law.\n\nAt Fogg\u2019s request, his attorney Robert Katims made a request for a reduced sentence on Fogg\u2019s behalf, saying that Fogg had entered into a \u201clong term\u201d treatment program for sex offenders.\n\n\u201cHe\u2019s not a threat to anyone now or in the future,\u201d Katims said.\n\nAccording to police, Fogg is a Level 3 sex offender. The defendant told the court he had been working for the same employer for 20 years, and that he and his employer had offered to have the boy come and work with Fogg.\n\nFogg also told the court that he and the victim had made contact again after the assault, and had reconciled. He said that he had stayed in contact with the victim because he thought the boy\u2019s father would have been hurt by their friendship ending.\n\nAccording to court papers, Fogg had served prison time in Vermont for sexual assault of a child and sexual assault on a person incapable of consent.\n\nThe victim told police he wanted to speak at the sentencing hearing, but was too nervous to do so.\n\nThe boy\u2019s mother said she felt terrible about how the family was going to deal with this situation.\n\nShe asked the court for a reduced sentence for Fogg.\n\n\u201cI\u2019m asking for a second chance,\u201d she said.\n\nWashington County State\u2019s Attorney Scott Williams said he agreed that Fogg had been in treatment, but that this crime happened over a period of time, and he was worried that Fogg had a \u201csexual relationship\u201d with the victim.\n\nWashington County Judge Thomas Zonay imposed the sentence.\n\n\u201cThis is a horrible offense,\u201d Zonay said. \u201cI hope you are a better person when you are released.\u201d]" time="0.332"><properties><property name="score" value="0.0042645265" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00426453 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00426453
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Budget\n\nThe more money you have, the more choices you can make. If you\u2019re wondering how to best budget your finances, you need to ask yourself how you\u2019ll spend your money. Will it be on a better car, a bigger house, a newer smartphone? Or, will you be saving for the future? There are a lot of factors to consider when deciding how to budget, but in the end, it will be up to you.\n\nWhat does the future hold?\n\nJust like the present, it is hard to predict the future. But as the saying goes, a bird in the hand is worth two in the bush. This is why it is so important to save for the future. This is what having a budget is all about. It is a way to make sure that you\u2019ll have enough money to last throughout your entire life.\n\nFor example, say you\u2019re saving up for a car that costs $30,000. If you\u2019re saving up at a rate of $50 a month, it will take you 60 months to save up for that car. If you\u2019re saving up for $500 a month, it will take you 20 months. The earlier you start, the better. So start today.]" time="0.268"><properties><property name="score" value="0.2557318" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Private Detectives for Divorce in Santa Clara, California\n\nDivorce is one of the most common issues faced by couples in Santa Clara, California. At any given moment, the vast majority of married people in Santa Clara are likely to feel the pressure of going through a divorce. However, such decision is bound to affect the entire family. Although it\u2019s natural for the individuals to want to think about their own concerns, it is also wise to consider how the people around them are affected.\n\nIt\u2019s a good idea to get in touch with a Santa Clara, CA Private Investigator for more information on how to deal with the situation. This will allow you to consider the best options available and see which one is suitable for your situation.\n\nWhen looking for a Private Detective in Santa Clara, it is important to consider the level of confidentiality involved. Most people prefer a more confidential and discreet option when hiring a Private Investigator in Santa Clara. In fact, many people from the area prefer to keep their situation a secret. This is why it is a good idea to hire a Private Detective from the area. This is especially true when dealing with the local law enforcement agencies. This is because the Private Detective in Santa Clara can handle matters in a manner that is acceptable by the local authorities. This will help to avoid any unnecessary complications.\n\nGet more information by contacting a Santa Clara, CA Private Detective today!]" time="0.279"><properties><property name="score" value="0.07121548" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl["Kury jak wy wyjd\u0105 z takiej sprawy, to si\u0119 nie dziwie. Ale wy jak wyjdziecie, to si\u0119 dziwie" - powiedzia\u0142 na antenie Polsat News zdenerwowany Adrian Czapla, szef Obywateli RP, komentuj\u0105c decyzj\u0119 s\u0105du, kt\xf3ry zdecydowa\u0142 o umorzeniu \u015bledztwa w sprawie marszu ONR w \u015bwi\u0119to Narodowego Czynu Zbrojnego.\n\nS\u0105d uzna\u0142, \u017ce nie ustalono kto \u015bci\u0105ga\u0142 transparenty w ramach Marszu Niepodleg\u0142o\u015bci i Niez\u0142omnych.\n\n"Ten proces by\u0142 bardzo smutny dla nas. W og\xf3le nie zabrali\u015bmy g\u0142osu. Prokuratura zarzuci\u0142a nam chodzenie po ulicach i maj\u0105c transparenty nie mamy \u017cadnego argumentu. S\u0105d powiedzia\u0142: a wy\u015bcie maj\u0105 prawo chodzi\u0107 po ulicach i maj\u0105c transparenty nie mamy \u017cadnego argumentu. Powiedzieli, \u017ce nie zrobili\u015bmy nic z\u0142ego, ale nie zrobili\u015bmy nic dobrego. Oczywi\u015bcie nie z\u0142amali\u015bmy prawa. Wymy\u015blili znaczek ONR i nie zrobili\u015bmy nic dobrego. S\u0105d powiedzia\u0142, \u017ce to co robimy nie jest nawet nieprawid\u0142owe, jest nawet wskazane" - komentuje Adrian Czapla, szef Obywateli RP.\n\nDoda\u0142, \u017ce odwo\u0142aj\u0105 si\u0119 od tej decyzji. "Nie mamy innego wyj\u015bcia. My\u015bmy wykonali prawo i b\u0119dziemy uwa\u017cali, \u017ce nie ma niczego, co by nas uw\u0142acza\u0142o. Tego by nie zrobi\u0142 \u017caden obywatel, nie zrobi\u0142by tego nawet najbardziej sk\u0142onny do milczenia obywatel" - podkre\u015bli\u0142.\n\nKomentuj\u0105c s\u0142owa prezesa PiS Jaros\u0142awa Kaczy\u0144skiego o ukaraniu dziennikarzy, kt\xf3rzy pisz\u0105 o jego bracie, przyzna\u0142, \u017ce to jest jedna strona medalu. "Jest druga strona medalu i to jest prezes, kt\xf3ry znajduje si\u0119 w tym samym przedmiocie i kt\xf3ry wychodzi poza ten przedmiot. Przez to jest niepokoj\u0105ce. I nie jest to jedyny przyk\u0142ad. Zreszt\u0105 ci sami ludzie, kt\xf3rzy broni\u0105 prezesa, pisz\u0105, \u017ce umar\u0142o 100 tysi\u0119cy ludzi na skutek przywilej\xf3w jedn\u0105 rozmaitych jednostek, kt\xf3re wyznaczy\u0142y si\u0119 na przedstawicieli obywateli. Oczywi\u015bcie nie wszyscy obywatele s\u0105 przedstawicielami, ale ci w\u0142a\u015bnie s\u0105 reprezentantami" - podkre\u015bli\u0142 Czapla.\n\nWt\xf3rowa\u0142 mu Marcin Warcho\u0142 z Kukiz '15. "Dzie\u0144 wcze\u015bniej lider PiS m\xf3wi\u0142, \u017ce z\u0142y j\u0119zyk nie wolno politykom u\u017cywa\u0107. To jest ta niezwyk\u0142a hipokryzja, dla kt\xf3rej Polacy mieli ju\u017c do\u015b\u0107 i dlatego przeszli z jednej partii do drugiej" - powiedzia\u0142.\n\n"Mo\u017cna oczywi\u015bcie odpowiedzie\u0107 na to, \u017ce jedno i drugie jest nieodpowiedzialne i ma wp\u0142yw na debat\u0119 publiczn\u0105, ale je\u017celi wierzymy w demokracj\u0119, to musimy najpierw wymaga\u0107 od siebie, a potem od innych. To tak jak w prawie. Je\u017celi s\u0105dy zamieniaj\u0105 si\u0119 w prywatne komnaty, to obywatel si\u0119 oburza i mo\u017ce powiedzie\u0107: wolno mi robi\u0107, co chc\u0119" - podkre\u015bli\u0142 Warcho\u0142.\n\nDoda\u0142, \u017ce "zaw\u0142aszczanie s\u0105d\xf3w" jest zjawiskiem powszechnym. "PiS to zaostrza, ale oni sami wielokrotnie przyznawali si\u0119, \u017ce na szczytach w\u0142adzy s\u0105 s\u0119dziowie, kt\xf3rzy nie wyrokowali, tylko robili z PiS przymusowych koalicjant\xf3w. To jest jeszcze bardziej dramatyczne, bo nie jest to takie nag\u0142e zaw\u0142aszczenie, to jest proces, kt\xf3ry trwa\u0142 w\u0142a\u015bnie od tych lat" - doda\u0142 Warcho\u0142.\n\n"Kiedy na pocz\u0105tku tego roku s\u0119dzia z Tr\xf3jmiasta przeszed\u0142 do KOD i na wiecu zacz\u0105\u0142 g\u0142osi\u0107 swoje pogl\u0105dy, wtedy dosz\u0142o do wybuchu afery, gdy dziennikarz pokaza\u0142, \u017ce przez siedem lat to s\u0119dzia wyda\u0142 35 wyrok\xf3w. Czy to by\u0142o wynikiem jego w\u0142asnej pracy? Ale w\u0142a\u015bnie tak wygl\u0105da\u0142o" - komentowa\u0142 Warcho\u0142.\n\n"Prawdziw\u0105 kompromitacj\u0105 dla PiS by\u0142o nagranie przed Sejmem. W\u0142adza zaczyna w\u0142adz\u0119 broni\u0107 w spos\xf3b nie do przyj\u0119cia dla wszystkich. To kompromitacja, kt\xf3ra jest zgodna z post\u0119powaniem niekt\xf3rych s]" time="0.329"><properties><property name="score" value="0.0049773515" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Zitat von Michael im Beitrag #836 Zitat von The Truth im Beitrag #733 http://www.bbc.co.uk/programmes/b00vc7t0\n\nKein Angriff auf die Freiheit der kritischen Geister. Der geistige und demokratische Geist der R\xf6mischen Vertr\xe4ge ist unangetastet geblieben.\n\nDemokratie ist das einzige politische System, bei dem der Volkswille die Vertr\xe4ge nicht brechen kann. In der Demokratie steht jeder Vertrag unter dem Vorbehalt, dass sich die Mehrheit des Volkes davon abwendet.\n\n\n\nDie Schweiz, \xd6sterreich und Ungarn sind die einzigen europ\xe4ischen L\xe4nder, die nicht in der EU sind. Sie haben ihren Frieden, weil sie es gewagt haben, sich der EU zu widersetzen, und den Willen haben, sich nicht unterwerfen.\n\nWas ist mit Italien? Das kann ich nicht nachvollziehen. Die Lage dort ist ja durchaus prek\xe4r.\n\n\n\nDie EU ist zu klein, zu b\xfcrokratisch und zu schwerf\xe4llig, um sich aus der EU l\xf6sen zu k\xf6nnen. Dieser Vortrag zeigt auch auf, dass die EU und der Euro auf keinen Fall vor dem Sinken gerettet werden k\xf6nnen. Er schl\xe4gt die Wiedereinf\xfchrung des Lire vor. Die Deutschen, die das nicht gern h\xf6ren werden, werden in Erinnerung geben, dass sie das Italiensche Bankensystem aufgebaut haben. Italien hat also den Geldabfluss von allen Eurol\xe4ndern abgebaut und damit ein sehr stabiles und solides Bankensystem. Deutschland wird es nicht gefallen, wenn das Bankensystem zusammenbricht. Ich weiss auch nicht, ob der Lire den Euro \xfcberlebt. Ich vermute, dass es dann sofort zu einer Aufwertung des Lire kommt. Das w\xfcrde aber die deutsche Exportwirtschaft schw\xe4chen, was die Deutschen nicht so gern h\xf6ren werden. Was ist mit Italien? Das kann ich nicht nachvollziehen. Die Lage dort ist ja durchaus prek\xe4r.Die EU ist zu klein, zu b\xfcrokratisch und zu schwerf\xe4llig, um sich aus der EU l\xf6sen zu k\xf6nnen. Dieser Vortrag zeigt auch auf, dass die EU und der Euro auf keinen Fall vor dem Sinken gerettet werden k\xf6nnen. Er schl\xe4gt die Wiedereinf\xfchrung des Lire vor. Die Deutschen, die das nicht gern h\xf6ren werden, werden in Erinnerung geben, dass sie das Italiensche Bankensystem aufgebaut haben. Italien hat also den Geldabfluss von allen Eurol\xe4ndern abgebaut und damit ein sehr stabiles und solides Bankensystem. Deutschland wird es nicht gefallen, wenn das Bankensystem zusammenbricht. Ich weiss auch nicht, ob der Lire den Euro \xfcberlebt. Ich vermute, dass es dann sofort zu einer Aufwertung des Lire kommt. Das w\xfcrde aber die deutsche Exportwirtschaft schw\xe4chen, was die Deutschen nicht so gern h\xf6ren werden.\n\n\n\nSo schnell geht das mit Italien auch nicht. Man wird den W\xe4hrungsumtausch hinausz\xf6gern. Immerhin ist Italien auch sehr wichtig f\xfcr Deutschland, nicht nur wegen der Banken, sondern auch wegen der Beziehungen zu Russland. Ein unkontrollierter Euro-Crash w\xfcrde Italien wirtschaftlich ins Mittelalter zur\xfcckwerfen, wenn nicht noch schlimmer.\n\nDer Sprecher sagt zwar, dass die EU und der Euro nicht vor dem Sinken gerettet werden k\xf6nnen. Doch er h\xe4lt es f\xfcr m\xf6glich, dass die EU \xfcberlebt und das Land aus der Krise kommt.\n\nIch bin allerdings skeptisch. Wenn der Euro zerbricht, gibt es keine Garantie, dass Italien im Euro bleibt. Es wird wohl eher darum gehen, ob es in der EU bleibt. Es ist nicht sicher, ob es den Lire beh\xe4lt oder wieder eine eigene W\xe4hrung einf\xfchrt. Das w\xfcrde Italien wieder zu einem Import-Export-Land machen. Dann w\xfcrde es nicht so sehr unter dem Euro leiden, weil es ein Exportland ist. So schnell geht das mit Italien auch nicht. Man wird den W\xe4hrungsumtausch hinausz\xf6gern. Immerhin ist Italien auch sehr wichtig f\xfcr Deutschland, nicht nur wegen der Banken, sondern auch wegen der Beziehungen zu Russland. Ein unkontrollierter Euro-Crash w\xfcrde Italien wirtschaftlich ins Mittelalter zur\xfcckwerfen, wenn nicht noch schlimmer.Der Sprecher sagt zwar, dass die EU und der Euro nicht vor dem Sinken gerettet werden k\xf6nnen. Doch er h\xe4lt es f\xfcr m\xf6glich, dass die EU \xfcberlebt und das Land aus der Krise kommt.Ich bin allerdings skeptisch. Wenn der Euro zerbricht, gibt es keine Garantie, dass Italien im Euro bleibt. Es wird wohl eher darum gehen, ob es in der EU bleibt. Es ist nicht sicher, ob es den Lire beh\xe4lt oder wieder eine eigene W\xe4hrung einf\xfchrt. Das w\xfcrde Italien wieder zu einem Import-Export-Land machen. Dann w\xfcrde es nicht so sehr unter dem Euro leiden, weil es e]" time="0.313"><properties><property name="score" value="0.00022136665" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[CMC Centennial Media College hosts SMC Centennial Media College hosted its annual Christmas Tree Lighting event on Dec. 4. The tree lighting began with a caroling competition for the best male and female singer. The event also featured performances by the CMC choir and the Oratorio choir. The night ended with a hot chocolate and cookie bar. Above, CMC's choir led the audience in a caroling competition and performed. Photos by Justina Gardner | Addie Boyce, Mark Wood and Maura Curry lead the audience in singing Christmas carols. | Ben Rich | Ophir Sohbi, choir director | 'Sweet Child of Mine' was sung by freshman Levi Johnson. | Eleven-year-old Angelina Torres was the youngest performer of the night. | The annual Christmas tree lighting included a hot chocolate and cookie bar. | Dr. Robert Ashcraft speaks to the audience. | Students are given hot chocolate. | Jeremy Hoffman (left) and Cole Thomas (right) sing for the crowd. | The Centennial choirs performed with full-band accompaniment. | Ben Rich's rendition of 'Baby, It's Cold Outside' was voted the audience favorite. | After singing 'Silent Night,' Maggie Seppelt (left) and Mark Wood were declared the winners of the caroling competition.]" time="0.268"><properties><property name="score" value="0.07843229" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07843229 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.07843229
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Rated 5 out of 5 by veronicajbrn from great quality I love the idea of a rack that I can use to hang my laundry instead of using a dryer. So far it has worked great. There is enough room for even my larger clothes. I love the little compartments for my washcloths.\n\nRated 5 out of 5 by mackinac9 from Perfect for a small apartment We recently moved to a small apartment and have limited storage space. This is a perfect solution for small spaces as it does not take up a lot of room and can be used for other things when not in use as a laundry rack.\n\nRated 5 out of 5 by smartgal from great product ! We bought 2 to use as drying racks for small items - even used it to hang our 'flip-flops' on when going to the beach. You could use this rack for lots of things - just be creative.\n\nRated 4 out of 5 by elaine19 from Excellent space saver This little rack is exactly what I was looking for. It is extremely light and portable and folds up to be very compact. I don't have a clothes dryer so it makes it easy to air dry clothes.\n\nRated 5 out of 5 by Linda1953 from Excellent product. This was a perfect space saver and will be using this for a long time. Excellent product and I have already recommended it to many people.\n\nRated 5 out of 5 by Chicagoan from Exactly what I needed! This is a great product, and is perfect for a single person who needs to conserve space. I hang my sweaters and washcloths on it, and my dress shirts and jeans on it. I can't believe that I finally found the perfect product!\n\nRated 5 out of 5 by huddie from This product is very convenient. It makes drying clothes much easier than using a clothes line.]" time="0.339"><properties><property name="score" value="0.09262063" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\u201cChris and his crew were amazing. The repairs and work they did was of the highest standard and looks as good as new. You can\u2019t even tell there was a repair! Not only that, but they were courteous and easy to deal with, which was so refreshing. Chris\u2019 knowledge of the products he works with was also really helpful. Would highly recommend.\u201d\n\nLea (The Loop)\n\n\u201cI have had a full door replaced and a broken rear door window replaced on my Holden Commodore and have been extremely happy with the quality of the work and service provided.\u201d\n\nRohan (Werribee)\n\n\u201cChris repaired my front right passenger window that had been broken for months. He was efficient, courteous and did a really good job. I highly recommend his work.\u201d\n\nSacha (Aberfeldie)\n\n\u201cChris and his team replaced the rear window of my Rodeo ute that had been broken for a while. He did a great job. He was very friendly, professional, fast and efficient. I would highly recommend his work.\u201d\n\nJames (North Melbourne)\n\n\u201cChris replaced my driver\u2019s door window which had been smashed. He was fast and efficient. The window looks great. I will definitely recommend him.\u201d\n\nLinda (Heidelberg)\n\n\u201cChris and his team replaced my passenger window on my XR6 ute that had been smashed. He was fast and efficient. The window looks great. I will definitely recommend him.\u201d\n\nMartin (Sydney)\n\n\u201cChris and his team replaced my side windows on my 2004 Hyundai Sante Fe, they were great. They were friendly, efficient and quick. I\u2019d recommend them to anyone.\u201d\n\nSteve (Eltham)\n\n\u201cChris repaired my front windscreen which had been smashed a few times. He did a great job. I was very impressed. He was friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nGemma (Bentleigh)\n\n\u201cChris repaired the front windscreen on my car and did a great job. I was very impressed. He was friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nDave (Preston)\n\n\u201cChris and his team repaired the back window on my Commodore ute that had been smashed. He was fast and efficient. The window looks great. I will definitely recommend him.\u201d\n\nSally (Maribyrnong)\n\n\u201cChris and his team repaired the front and rear window on my ute that had been smashed. They did a great job. They were fast and efficient. I will definitely recommend him.\u201d\n\nBrad (Strathmore)\n\n\u201cChris and his team replaced my passenger window on my van that had been smashed. They did a great job. They were fast and efficient. I will definitely recommend him.\u201d\n\nDon (Diggers Rest)\n\n\u201cChris and his team replaced the front window on my Commodore ute that had been smashed. They did a great job. They were fast and efficient. I will definitely recommend him.\u201d\n\nDiane (Thomastown)\n\n\u201cChris and his team replaced my rear window on my HOLDEN CALAIS that had been smashed. They did a great job. They were fast and efficient. I will definitely recommend him.\u201d\n\nNeil (St Kilda)\n\n\u201cChris replaced the passenger window on my ute that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nJan (South Yarra)\n\n\u201cChris replaced the front window on my HOLDEN COMMODORE that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nMichelle (Donvale)\n\n\u201cChris and his team replaced my front passenger window on my honda civic that had been smashed. He was fast and efficient. The window looks great. I will definitely recommend him.\u201d\n\nMichelle (South Yarra)\n\n\u201cChris replaced the rear window on my car that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nAnne (Caroline Springs)\n\n\u201cChris replaced the front windscreen on my sedan that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nJohannes (Laverton)\n\n\u201cChris and his team replaced the rear window on my sedan that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nVicki (Caroline Springs)\n\n\u201cChris replaced the front window on my HOLDEN COMMODORE that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nPaul (Melbourne)\n\n\u201cChris replaced the front windscreen on my honda accord that had been smashed. He did a great job. He was very friendly, professional, fast and efficient. I will definitely recommend him.\u201d\n\nBrendon (Wyndham Vale)\n\n\u201cChris replaced the front]" time="0.340"><properties><property name="score" value="0.002747971" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[LAS VEGAS \u2014 Conor McGregor\u2019s coach says the mixed martial arts star is in \u201cfantastic\u201d shape and wants to fight Khabib Nurmagomedov on Oct. 6 for a UFC lightweight championship.\n\nJohn Kavanagh said on Twitter that McGregor is \u201cdoing very well after his surgery\u201d to fix a ruptured ligament in his left knee.\n\nMcGregor, who is Irish, posted a message on Twitter on Tuesday saying he\u2019s \u201cready\u201d to fight in October.\n\nUFC president Dana White has said that McGregor, who hasn\u2019t fought in the octagon since 2016, has two fights left on his contract with the UFC.\n\nMcGregor was stripped of his UFC lightweight championship when he opted not to defend his belt against Nurmagomedov, who was offered the opportunity as the next highest-ranked contender.\n\nNurmagomedov is the UFC\u2019s lightweight champion and has been waiting to fight McGregor since last year, when he said the Irishman could make some money outside the octagon before returning.\n\nMcGregor was allowed to fight boxing champion Floyd Mayweather Jr. in a 10th-round technical knockout in August 2017, as part of a deal that had him agree to give up his lightweight belt and allow Nurmagomedov and Tony Ferguson to fight for the belt.\n\nFerguson was sidelined after suffering a knee injury in a freak accident in August. He is now set to fight Anthony Pettis at UFC 229 on Oct. 6.\n\nKavanagh said on Twitter that Ferguson will be next in line to fight Nurmagomedov, but there is no certainty when the bout will happen.\n\nWhite has said that Ferguson-Pettis will be the UFC\u2019s main event at UFC 229.\n\nNurmagomedov, meanwhile, has offered McGregor a fight at UFC 230 on Nov. 3, at New York\u2019s Madison Square Garden. But White has said McGregor has other options that he prefers.\n\nNurmagomedov has demanded McGregor receive no special treatment in their fight.\n\n\u201cIf he wants to come back, if he wants to fight, we\u2019re here,\u201d Nurmagomedov told the website MMA Junkie. \u201cBut if he\u2019s looking for a different fight, different opponents, different contracts, I don\u2019t know.\u201d]" time="0.306"><properties><property name="score" value="0.001441099" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0014411 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0014411
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[by l.helst \xbb Fri Feb 08, 2018 4:41 pm\n\nFirst I have a question and maybe this forum is the best place to ask:\n\nWhen I ask a question and have a request for a download of the file I am working on I think its better that the person that can help, have the same file to start with. I found that this forum do not have a facility to upload a zip file (for the moment). How would be the best way to share a file with the developers?\n\n\n\nThe question:\n\n\n\nAfter the download of version 4.0.3 I cannot start a layout. A dialogue box appears and say that the application can not be started because of a missing or damaged library.\n\nPlease can I get a list of the files that are missing?\n\nI have the following files in the directory C:\\Program Files (x86)\\Routz:\n\n- Routz4.exe\n\n- Routz4.exe.md5\n\n- Routz4.x64.dll\n\n- Routz4.x64.dll.md5\n\n- Routz4.x64.exe\n\n- Routz4.x64.exe.md5\n\n- Routz4.x64.pdb\n\n- Routz4.x64.pdb.md5\n\n- Routz4.x86.dll\n\n- Routz4.x86.dll.md5\n\n- Routz4.x86.exe\n\n- Routz4.x86.exe.md5\n\n- Routz4.x86.pdb\n\n- Routz4.x86.pdb.md5\n\n- Routz4.x86.zip\n\n- Routz4.x86.zip.md5\n\n- Routz4.xml\n\n- Routz4.xml.md5\n\n- RoutzPro_x64.dll\n\n- RoutzPro_x64.dll.md5\n\n- RoutzPro_x64.exe\n\n- RoutzPro_x64.exe.md5\n\n- RoutzPro_x64.pdb\n\n- RoutzPro_x64.pdb.md5\n\n- RoutzPro_x86.dll\n\n- RoutzPro_x86.dll.md5\n\n- RoutzPro_x86.exe\n\n- RoutzPro_x86.exe.md5\n\n- RoutzPro_x86.pdb\n\n- RoutzPro_x86.pdb.md5\n\n\n\nRegards Lief Helst]" time="0.342"><properties><property name="score" value="0.0030844281" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Hotel jest do\u015b\u0107 niedu\u017cy. Z okien wida\u0107 strumie\u0144 Bieszczady. Cz\u0119\u015b\u0107 pokoi ma balkon, przy oknach nie ma rolek do oklepywania, wi\u0119c musimy to sobie sami robi\u0107. Na dole znajduj\u0105 si\u0119 recepcja i restauracja. Jest to niezbyt du\u017ce i wygodne pomieszczenie. Restauracja jest czysta i klimatyzowana. Podczas wizyty by\u0142o jednak tylko jedno stoliki dla go\u015bci i innych pokoi. Na to stolik do ka\u017cdego wstawiono tabliczk\u0119. \u017beby nie by\u0142o nudno i nie musieli\u015bmy siedzie\u0107 nad sob\u0105 zamawia\u0142em dania na terenie samego hotelu. Osoby, kt\xf3re wesz\u0142y do pokoju po wszystkim zam\xf3wi\u0142y po prostu co\u015b do \u015bniadania. \u015aniadania by\u0142y bogate i do\u015b\u0107 du\u017ce. W okolicy by\u0142o wiele sklep\xf3w, do kt\xf3rych chodzili\u015bmy na zakupy. Ogr\xf3d hotelowy by\u0142 zielony i przyjemny. W ogrodzie i otoczeniu hotelu by\u0142y w\u0142asne sklepiki z pami\u0105tkami, lody itp. W hotelu mieli\u015bmy sw\xf3j pok\xf3j z wann\u0105 i w pe\u0142ni wyposa\u017con\u0105 kuchni\u0105. Prysznic by\u0142 jak w ka\u017cdym pokoju hotelowym, natomiast umywalki by\u0142y na razie ma\u0142e i przyci\u0119te. Obok s\u0105 dwie jacuzzi. Dla dzieci by\u0142 osobny basen. W basenie by\u0142o dost\u0119pne jedzenie i napoje. Obejrzeli\u015bmy kilka razy pla\u017c\u0119, kt\xf3ra by\u0142a dosy\u0107 spora, ale troch\u0119 brakowa\u0142o miejsca do siedzenia. Bardzo nam si\u0119 spodoba\u0142o. Obs\u0142uga hotelu by\u0142a przyjemna i \u017cyczliwa. Czas sp\u0119dzony w ubieg\u0142ym roku by\u0142 bardzo udany.]" time="0.314"><properties><property name="score" value="0.03404539" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[1. It's "firmware" not "firm ware." Try to get a better handle on your grammar before you get your grammar wrong.\n\n2. Calling something a "feature" doesn't make it a feature. It's a mislabeling. The way these displays are lit up is a hardware implementation of a "gradient." The gradient of color is the "feature" of the gradient, not the entire display.\n\n3. The function of a gradient in this case is not to "determine" color or value, it is to make the display more aesthetically pleasing. There is a huge difference.\n\n4. The system was designed by people who knew how to do lighting in a way that adds visual interest. There is a reason that their work was considered "taste-based." It was designed by people who knew how to do lighting. Lighting is all about creating mood and impact, not function.\n\n5. The system was designed so that it would be physically impossible to light all the light sources the same, that way there would be no color "accurate" (read "unpleasing") way to light the display. As long as people can see it clearly, it will never be "accurate."\n\n6. In this application, color accuracy is the least of the concerns, and it is not the main consideration. It is a display, not a video image.\n\n7. If the numbers of the OLEDs are off, they will still light up. They will not "burn in." A long exposure to a dark scene will turn the display black, and that's all there is to it.\n\n8. Those are just panels with color filters over them. They are not LEDs. The whites are not being filtered, they are being lit up as one.\n\n9. Because they are lit up individually and not together as a whole, the panels do not "add up" to make the perceived color and intensity of light. It's a bit like red, green and blue, and how they do not really "add up" to make a full white light. (And the full white you see is more likely white than red, green or blue).\n\n10. Just because you can prove that something is "not black" doesn't make it "not black." There are more than a few tungsten lamps out there that aren't really "black," but people would be pretty annoyed if you said they weren't really "black."\n\n11. White LEDs are also not the most "color accurate" light source out there. They have to be filtered to get that way. If you don't filter them, you don't get the same white as if you did filter them.\n\n12. People actually are aware of color. It is not as if they cannot distinguish color differences. They may not see every single pixel of difference, but they are still going to see differences. They can distinguish a difference between an "R" and an "L" in some fonts. If you put those two letters side by side, the difference will be visible. It is not going to look identical to them.\n\n13. "Accurate color" is a subjective term. What may be accurate to you may not be accurate to me.\n\n14. Just because a company makes an extra $10 by selling you a part that does something that it was not designed for doesn't make it right. It just means you are getting ripped off.\n\n15. Yes, the color of the display is very important to the perception of the light in the environment, but it is not the only factor.\n\n16. Not all blue LEDs are the same. In fact, the blue from blue LEDs changes with age. You have to take this into account in your designs.\n\n17. No, it is not impossible to change the light of a display.\n\n18. Yes, you can still get better uniformity if you combine the LEDs into one panel. You will also get better efficiency, but the screen won't look as good.\n\n19. The individual LEDs can only emit a certain amount of light. They cannot magically produce more.\n\n20. You can get even better efficiency if you replace the red and green LEDs with white LEDs. It is a tradeoff, though. It is not a free lunch.\n\n21. LEDs emit light in a different range of color than the human eye can detect. They have a certain distribution of color, not a specific one.\n\n22. Because the color distribution of the LEDs is not the same as the human eye, you have to modify the LEDs to make them appear to the human eye as if they were emitting the correct color light.\n\n23. The human eye is not linear, which is what is being assumed. This is what allows you to see the color of white. It is also what allows you to perceive the color of a cloudy sky.\n\n24. If you want to look at "color accuracy," take a look at the color of the light in the environment that the display is in. It will be different in each of them. The difference between the human eye and a camera is also a huge consideration, as cameras are not very good at capturing all of the available color in an image.\n\n25. Blue LEDs do not go through a filter to be blue. They are actually more "white" than blue, so you have to color-filter them. This is not necessarily an "extra" step, as it does not have to be done to "make them blue."\n\n26. You can make a good case for certain LEDs being "super blue," but you cannot make a case that they are "super red." Red is the hardest color for LEDs to produce. You can make the case that you can produce more "pure" red than can be seen by the human eye, but you cannot make the case that you can produce more "pure" red than can be produced by a red LED.\n\n27. If the LEDs can do something "super" (in this case, "super red"), then the LEDs can do something "normal" (in this case, "normal red.") There is no free lunch, there are just tradeoffs.\n\n28. Trying to compare "new" with "old" (to sell you something) is an old, well-established, tired sales technique.\n\n29. You can say a person has 20/20 vision, but you cannot say a display has "perfect color."\n\n30. Yes, OLEDs can do things that no other display technology can do. They can also do things that some other display technologies can do. That does not mean that you can't make a display that has features that OLEDs don't have.\n\n31. You can make a display that has good color rendition, that is not an OLED. It just means you are not using OLEDs.\n\n32. Just because a manufacturer says "this is what you are going to get" doesn't mean you are going to get it. If you need something that is color accurate, you need to specify it. If you do not, then you get what they give you.\n\n33. If you look at a display and you say "it looks too blue," then you are probably right. But that doesn't mean it is inaccurate. That just means you are looking at it the way you would look at it in real life.\n\n34. There are many factors that influence color perception in a viewing environment. There is no single factor that influences color perception in a viewing environment.\n\n35. Color accuracy is just one aspect of the human visual system, and just because it is not the only aspect does not make it not the only aspect.\n\n36. If you are a designer, you have to understand the limits of the technology and the product that you are working with. If you do not, then you are not going to be very successful.\n\n37. People like to think that designers can control everything, but they can't. It's just a fact of life.\n\n38. The human visual system is much more complicated than a display or a camera.\n\n39. Just because a technology has a lot of colors, it doesn't mean you have to use all of them.\n\n40. Just because a display can produce a certain color, it doesn't mean you have to use it.\n\n41. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display is not a light source. A display]" time="0.729"><properties><property name="score" value="0.01015762845" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Democratic Socialist Bernie Sanders has promised to end our current immigration policies and implement a new policy, which will favor immigrants from countries that have a history of struggling with socialism.\n\nDuring his CNN town hall, Sanders was asked by an illegal immigrant named Marcela if he planned to help her and her fellow undocumented brethren.\n\n\u201cAbsolutely, we will,\u201d Sanders replied.\n\n\u201cThe idea that you have so many wonderful people who want to contribute to the fabric of our society,\u201d he said, \u201cis something I very, very strongly believe in.\u201d\n\n\u201cThat means,\u201d he continued, \u201cwe need comprehensive immigration reform.\u201d\n\nSanders\u2019 new immigration reform will make it much easier for those who have socialist tendencies to move to America.\n\n\u201cWhat it does is bring 11 million undocumented people out of the shadows. It would provide them with legal protection and allow them to work with full rights in this country. And it would provide a path toward citizenship,\u201d he explained.\n\n\u201cI voted against this draconian legislation in 2006. I voted against it again in 2013. And I will do everything in my power to overturn it.\u201d\n\n\u201cWe need a path toward citizenship for people who are undocumented,\u201d he concluded.\n\nIronically, Sanders was able to support this legislation because his socialistic tendencies weren\u2019t under the scrutiny of a large voting base. Had he been elected in this era, his political allies would have been able to reveal the fact that he is a hypocrite, as he supported immigration legislation which could potentially cost Americans their jobs.\n\nThere\u2019s no denying that immigrants have helped to build our country and that immigration is vital to our national security and our economic health. But there\u2019s a time and a place for everything, and a time to admit when you were wrong, especially when that error may have hurt Americans.\n\nSource: Daily Caller]" time="0.295"><properties><property name="score" value="0.0019861637" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00198616 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00198616
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[James Henry Carleton, also known as Jimmy Carleton (April 26, 1852 \u2013 February 18, 1924) was a lieutenant general in the United States Army during the Spanish\u2013American War, and later a military adviser to the Philippines. He was later elected as a U.S. Senator from California.\n\nEarly life [ edit ]\n\nCarleton was born in Claremont, New Hampshire, son of Francis Carleton (1821\u20131902) and Lydia (Patterson) Carleton (1819\u20131901). He graduated from the United States Military Academy in 1873. After graduation, he was commissioned a second lieutenant in the 1st Cavalry Regiment.\n\nCareer [ edit ]\n\nIn the Apache Wars, Carleton commanded Apache scouts in the Army of the Southwest from 1880 to 1882. As an officer with the rank of captain in 1885, Carleton served with the 9th Cavalry in Texas. During the Spanish\u2013American War, he commanded a volunteer troop of the Rough Riders at the Battle of San Juan Hill. He then led troops in Cuba, and from 1899 to 1900 served as a military observer in South Africa. In 1900, Carleton was sent to the Philippines, where he served in a number of different positions, and became a close confidant of future Philippine president Manuel Quezon.[1]\n\nIn 1902, Carleton was appointed Adjutant General of the Philippines, and from 1903 to 1906 he served as governor of Mindanao. In 1907, he returned to the United States and worked as the adjutant general of the Army until his retirement in 1911. In retirement, Carleton was active in civic and business affairs in San Francisco. He was elected as a Republican to the United States Senate in 1914 to fill the vacancy caused by the death of James D. Phelan and served from December 2, 1914, to March 3, 1917.\n\nDeath [ edit ]\n\nCarleton died in Berkeley, California, and is buried in Arlington National Cemetery.\n\nPersonal life [ edit ]\n\nOn June 4, 1881, Carleton married Mary King White, the daughter of General Rufus King of New York. They had two children, Lydia and Rufus.\n\nSee also [ edit ]\n\nReferences [ edit ]]" time="0.322"><properties><property name="score" value="0.6117403" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6117403 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6117403
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Vanguard University\u2019s 3-year old science and technology building, Hunt Hall, has become the first on campus building to achieve LEED platinum status, a recognition from the U.S. Green Building Council that is the highest level of sustainable building certification. The new building, which opened in August 2009, was constructed to provide specialized laboratory and classroom space for chemistry, biology, earth science, mathematics, physics, and digital art, graphics, and photography programs.\n\n\u201cWe\u2019re very excited and honored to receive this prestigious recognition,\u201d said Dr. C. Stanley (Bucky) Jones, president of Vanguard University. \u201cIn addition to the environmental benefits of this new facility, it is also extremely functional. It has set a high standard for us to follow in future construction and renovation projects.\u201d\n\nLEED Platinum is the highest of four levels of LEED certification. Buildings must achieve a score of at least 80 out of 100 possible points to receive the award. Hunt Hall\u2019s score is 93.\n\nTo achieve platinum status, Hunt Hall used recycled and low VOC materials, is more energy efficient, has better indoor air quality, and has extensive indoor and outdoor water conservation measures.\n\nHunt Hall is designed with innovative features to conserve water, including low-flow toilets, a ground-water recovery system for toilets and urinals, and low-flow showerheads. The building also has low-flow hand dryers and high-efficiency faucets. Outdoor water-wise features include drought-tolerant landscaping and a rooftop rainwater catchment system.\n\nOther water conservation features include a dark-colored roof, skylights, and window blinds that use computer-controlled solar shades that open and close automatically, saving additional energy when daylight is sufficient.\n\nTo help conserve energy, Hunt Hall uses photo-voltaic panels for electricity, and high-performance exterior windows and insulated walls that reduce the need for heating and cooling. The building has heating, ventilation, and air conditioning (HVAC) systems that provide highly efficient temperature control.\n\nA green roof on top of the building protects the building from sun and rainfall, and reduces the amount of storm water that needs to be treated.\n\nA LEED point is awarded for each of seven categories: sustainable site, water efficiency, energy and atmosphere, materials and resources, indoor environmental quality, innovation and design, and regional priority.\n\nHunt Hall has won several other awards since its completion. It was the recipient of the Grand Award for Best Green Building by the Association of Collegiate Schools of Architecture (ACSA), in the high school and higher education categories. The building was also named a 2009 Western College or University Project of the Year by the Western Chapter of the Building and Construction Trades Council, and received a Construction Excellence Award from the Green Building Certification Institute (GBCI).]" time="0.346"><properties><property name="score" value="0.0011108236" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00111082 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00111082
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Hanging Loose, and Losing\n\nBy JAY McINERNEY\n\nTHERE ARE THINGS I\u2019VE LOST SINCE JANUARY, WHEN I WROTE A COLUMN ABOUT a failed relationship and was cast as a victim in a newspaper I hadn\u2019t written for.\n\nThere was my privacy. There was my anonymity. There was my credibility as a novelist. The old troublemaker, suddenly confused and afraid.\n\nI spent last summer under the clouds of suspicion and doubt. I had already lost more than $20,000 in legal fees when my book editor flew in from New York. We were going to talk about whether I should fight the false accusation that I had stolen the title of my second novel, \u201cBright Lights, Big City,\u201d from an unpublished manuscript.\n\nWe had spent the previous two hours in the windowless office of my lawyer, defending the accuracy of the description of the 1982 dance club that I had spent a year writing about, the scene where I had first used the title in print.\n\nIt was the day before my wedding, in the year before my 50th birthday, and my book editor was telling me how sorry she was that I was getting married. She was telling me she was sure my wife-to-be would get divorced. She was telling me that it was \u201cimpossible\u201d for a woman to love me and that I shouldn\u2019t even try to stay married to her.\n\nA moment later, she stood up, took my hand and said, \u201cI\u2019m going to fight]" time="0.336"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[A fellow from AllTrials.net pointed out to me a study by the Journal of Clinical Oncology entitled \u201cAssociation of Trial Registration With Journal Impact Factor and the Probability of Trials Being Published in Relation to Registered Results.\u201d The basic study design was as follows:\n\nEvaluate the relationship between registered results and publication of trial results on the Journal of Clinical Oncology Web site.\n\nThe researchers identified a total of 116 trials from the ClinicalTrials.gov registry and the Journal of Clinical Oncology Web site, which were published during 2003 to 2011. The authors determined whether a trial was registered or not. From the conclusions:\n\nAs of January 2013, 56% (68 of 116) of trials had results available in the Journal of Clinical Oncology Web site. For registered trials, there was a positive association between registered status and the likelihood of publication of trial results in the Journal of Clinical Oncology. Although there was no statistically significant association between trial outcome and registration status, there was a trend toward more positive results being published for registered trials.\n\nThis study suggests that, while registered results don\u2019t guarantee publication, they have a positive impact. Yet it\u2019s important to remember that the proportion of trials registered that are actually published was about half (54%), which is far from 100%. I would also like to see this study replicated in other clinical trial registries (e.g., ClinicalTrials.gov and the European Clinical Trial Register), since the JCO is a highly selective journal. I would also like to see a study with a longer time-frame. I don\u2019t know how long the paper was in the works, but I\u2019m guessing it took a while.\n\nWhile the study seems reasonable, I\u2019m not sure how much one can extrapolate from this paper in terms of impact on clinical trial registration and publication of results. It\u2019s just one piece of the puzzle, as AllTrials points out.\n\nImage by dave_7 via Flickr\n\nLike this: Like Loading...]" time="0.304"><properties><property name="score" value="0.009330049" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00933005 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00933005
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Spherical Dice, labeled as 12-Sided Dice, are an uncommon variety of die that appears in Mario Party 4, Mario Party 5, Mario Party 6, Mario Party 7, Mario Party 8, Mario Party 9, and Mario Party: Island Tour. They function the same as regular Dice Blocks in that they roll and land on a number value, and allow players to move a number of spaces on the board based on that value. The color of the sphere varies from game to game; from green in Mario Party 4 to red in Mario Party 5.\n\nHistory [ edit ]\n\nMario Party 4 [ edit ]\n\nMario Party 4. Spherical Dice in\n\nSpherical Dice made their first appearance in Mario Party 4.\n\nMario Party 5 [ edit ]\n\nMario Party 5. Spherical Dice in\n\nSpherical Dice reappear in Mario Party 5.\n\nMario Party 6 [ edit ]\n\nMario Party 6. Spherical Dice in\n\nSpherical Dice also appear in Mario Party 6.\n\nMario Party 7 [ edit ]\n\nMario Party 7. Spherical Dice in\n\nSpherical Dice return in Mario Party 7.\n\nMario Party 8 [ edit ]\n\nMario Party 8. Spherical Dice in\n\nSpherical Dice reappear in Mario Party 8.\n\nMario Party 9 [ edit ]\n\nMario Party 9. Spherical Dice in\n\nSpherical Dice also appear in Mario Party 9.\n\nMario Party: Island Tour [ edit ]\n\nSpherical Dice reappear in Mario Party: Island Tour, where they are used on the Star-Crossed Skyway board.\n\nMario Party: Star Rush [ edit ]\n\nIn Mario Party: Star Rush, a spherical die with a spade on it appears on the amiibo Party mode.\n\nNames in other languages [ edit ]\n\nLanguage Name Meaning Japanese \u5186\u76e4\n\nEnban Round disk]" time="0.289"><properties><property name="score" value="0.24755746" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24755746 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.24755746
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Some residents of the Villages of Leisure World will remember Frank Kaminski, who was our representative on the Community Management Association Board for many years.\n\nI had been thinking about Frank and his death, and I began to wonder how many of our current residents are aware of the fact that each year at this time, we observe Veterans Day. We also hold a parade and a ceremony in the Ardenwood district of the Community Center where those who have served our country, be it in military service or other forms of government service, can be recognized for their contributions. I believe that the overwhelming majority of our residents would appreciate having an observance of this important day.\n\nI learned that we had some veterans who were residents at the time, but they were few in number and the parade was not held that year. Perhaps the occasion had not been sufficiently advertised and a sufficient number of residents were not aware of the event.\n\nI don\u2019t know how many of our veterans have passed away in the past 10 years, but I would like to see some way in which we could honor them on this occasion. I know that residents of the Ardenwood area would be delighted to have this occur again. I encourage the current members of the Community Management Board to look into this matter. I have already contacted some of our residents who were interested in this subject when I was Board president.\n\nI have been thinking about Frank, a Navy veteran and a WWII survivor of the USS Lexington, who was a good friend and an outstanding member of the Board. He had such a sense of loyalty and patriotism and really loved the U.S. flag.\n\nIt is never too late to give thanks and to show our appreciation.\n\nSylvia K. Schubert\n\nArdenwood]" time="0.279"><properties><property name="score" value="0.6559042" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6559042 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.6559042
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[(12 intermediate revisions by 3 users not shown)\n\nLine 1: Line 1:\n\n\u2212 {{disambig}} + {{merge|List of glitches ( games ) }}\n\n\u2212 This is a list of glitches in the ''[[Generation I]]'' [[Pok\xe9mon]] games . + This is a list of glitches that occur in the Generation I Pok\xe9mon games .\n\n==Pok\xe9mon Red and Blue== ==Pok\xe9mon Red and Blue==\n\n\u2212 ===By This User's Proof=== + ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=October 2012}} + * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=October 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n* {{GlitchResearch|Appears to have been recently discovered by this editor.|date=September 2012}} * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=September 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=September 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=September 2012}}\n\n* {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}} * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n* {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}} * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212 ===By This User's Proof===\n\n* {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}} * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212 ===By This User's Proof===\n\n* {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}} * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=August 2012}}\n\n\u2212 ===By This User's Proof===\n\n* {{GlitchResearch|Appears to have been recently discovered by this editor.|date=July 2012}} * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=July 2012}}\n\n\u2212\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=July 2012}}\n\n\u2212 ===By This User's Proof===\n\n\u2212 * {{GlitchResearch|Appears to have been recently discovered by this editor.|date=July 2012}}\n\n\u2212 ===By]" time="0.307"><properties><property name="score" value="0.00070651673" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[As an Amazon Associate as well as a member of other affiliate programs, I earn from qualifying purchases made through links on this site.\n\nWe all know I love Dr. Seuss. He is a favorite author of mine. His books are all classics and hold up well for kids. Some of my favorite Dr. Seuss books are the first in the list, How the Grinch Stole Christmas, The Cat in the Hat, and Horton Hears a Who.\n\nI know that Dr. Seuss is best known for his children\u2019s books. But, there are other Dr. Seuss books out there that are great reads for adults too. I will add to this list if I think of others.\n\nDon\u2019t forget to check out the latest Dr. Seuss gift guide for more ideas.\n\nMy Favorite Dr. Seuss Books for Adults\n\n1. There\u2019s a Wocket in my Pocket!\n\nThis is a great little book with loads of fun for the young and old alike. It is a book of nonsense words and noises. Just have fun with it and see what you can come up with.\n\n2. The Seven Lady Godivas\n\nYou can read this one with kids or for yourself, but it\u2019s a great quick read. A Dr. Seuss classic.\n\n3. The Butter Battle Book\n\nA story of a small family that lives in a split world where one side is at war with the other. One side eats their bread with the butter side up. The other eats theirs with the butter side down. Which is right?\n\n4. I Wish That I Had Duck Feet\n\nIn this book, a boy wishes that he had duck feet. It\u2019s silly and a lot of fun to read.\n\n5. How the Grinch Stole Christmas\n\nWho doesn\u2019t love this classic Dr. Seuss book? It is a quick read that you\u2019ll want to read every year.\n\n6. The Sneetches and Other Stories\n\nThis is a collection of stories about a green star-bellied creature called a Sneetch. One day the Sneetches realize that they come in two different kinds. This book has three stories in it: The Sneetches, Sylvester McMonkey McBean and Sour Kangaroo.\n\n7. Dr. Seuss\u2019s Sleep Book\n\nWho doesn\u2019t love this little book of fun with rhyming words about sleeping? This is a good book for adults who have trouble sleeping.\n\n8. The Butter Battle Book\n\nA simple, but great story about the peace-loving Yooks and the war-loving Zooks. In this story, the Yooks and Zooks each have a \u201cTop Secret Machine\u201d and they both seem to work well. But they do something very bad with them. You\u2019ll have to read the book to find out what happens.\n\n9. I Can Read with My Eyes Shut\n\nThis is a fun book that makes reading and reading with your eyes shut sound like a lot of fun.\n\n10. My Book About Me\n\nThis is a simple book to introduce your child to the concept of writing about themselves.\n\n11. The Wonderful World of Dr. Seuss\n\nThis is a great book for the true Seuss fan. This book is full of information about Seuss and his life.\n\n12. I Can Draw It Myself\n\nThis is a book with 10 different images and 10 different words that can be used to draw each picture. It also comes with a sketch pad. It is a fun idea and great for an artist.\n\n13. The Sneetches and Other Stories\n\nI can\u2019t stress enough how much I love this book. The story of the Sneetches is a classic story. The two other stories in this collection are also great. You\u2019ll be delighted by these three stories.\n\n14. You\u2019re Only Old Once!\n\nIn this book, a senior citizen goes through all the things that we all go through as we age. It\u2019s hilarious. This is a great book for those of us who are \u201cover the hill\u201d.\n\n15. McElligot\u2019s Pool\n\nA wonderful story about the benefits of finding something unexpected and fun in your day. It has the message that something good can come from any situation.\n\n16. The Lorax\n\nThis is a great story of a creature that cares for the trees and tries to save them from being cut down for business. It\u2019s also a great lesson on the benefits of conserving.\n\n17. Dr. Seuss\u2019s ABC\n\nIn this book, we learn the alphabet with Seuss characters. It\u2019s a great book to read to your kids.\n\n18. The Sneetches and Other Stories\n\nI love this book! The Sneetches are in the spotlight and there are two more stories to this collection. It\u2019s definitely worth adding to your collection.\n\n19. Dr. Seuss\u2019s Sleep Book\n\nThis is another great Dr. Seuss classic that is perfect for reading to your child when they are young. It\u2019s a great book about going to sleep.\n\n20. Ten Apples Up On Top!\n\nThis is a classic Dr. Seuss book. It\u2019s a silly book about a group of creatures that don\u2019t want to eat apples that have been placed on their heads. They have a bunch of silly excuses for not eating the apples.\n\n21. The Tooth Book\n\nA great book for teaching your kids about their teeth. It\u2019s full of fun and colorful pictures.\n\n22. The Bippolo Seed and Other Lost Stories\n\nThis is a collection of short stories that Dr. Seuss wrote that were lost. But they were found and included in this book. It\u2019s a great addition to any Dr. Seuss fan\u2019s collection.\n\n23. The Lorax\n\nA great book to teach your kids about conservation and caring for the earth. It\u2019s an amazing story.\n\n24. I Can Draw It Myself\n\nThis is a great book for a child that is ready to be independent and to start drawing by themselves. It includes instructions for drawing 10 different images.\n\n25. The Sneetches and Other Stories\n\nAnother great collection of stories by Dr. Seuss.\n\n26. Yertle the Turtle and Other Stories\n\nA cute little book with a great message. It\u2019s the story of a turtle that wants to be king and his greediness that leads him to ruin.\n\n27. The Cat in the Hat\n\nThis is the story of a boy who finds a Cat in a Hat in his house. He doesn\u2019t want to get rid of the Cat because he has a lot of fun with him. The Cat keeps making messes that make the house less fun for the boy. It\u2019s an amazing book.\n\n28. The Sneetches and Other Stories\n\nA great little book full of lessons and fun.\n\n29. My Book About Me\n\nThis is a simple little book for children to write about themselves. It\u2019s a fun way to encourage kids to get creative.\n\n30. One Fish Two Fish Red Fish Blue Fish\n\nThis is the story of a young boy who has a pretty dull life. But then he meets a couple of crazy creatures who change his life forever. They show him so much fun that his dull life doesn\u2019t seem so dull anymore. It\u2019s an amazing story.\n\n31. My Book About Me\n\nThis is a cute little book for kids to write about themselves.\n\n32. The Sneetches and Other Stories\n\nThis is another great collection of stories by Dr. Seuss. I really like this collection. It\u2019s a great addition to any Dr. Seuss fan\u2019s collection.\n\n33. Dr. Seuss\u2019s Sleep Book\n\nA cute little book with some fun words to say and some great ways to go to sleep.\n\n34. The Tooth Book\n\nA great way to introduce your kids to the world of teeth.\n\n35. One Fish Two Fish Red Fish Blue Fish\n\nThis is the story of a young boy who has a pretty dull life. But then he meets a couple of crazy creatures who change his life forever. They show him so much fun that his dull life doesn\u2019t seem so dull anymore. It\u2019s an amazing story.\n\n36. The Lorax\n\nThis is a great book to help teach your kids about conserving and taking care of our planet. It\u2019s a really great story.\n\n37. I Can Draw It Myself\n\nThis is a book with 10 different images and 10 different words that can be used to draw each picture. It also comes with a sketch pad. It is a fun idea and great for an artist.\n\n38. The Sneetches and Other Stories\n\nThis is a great collection of stories by Dr. Seuss. It has three stories in it: The Sneetches, Sylvester McMonkey McBean and Sour Kangaroo.\n\n39. The Sneetches and Other Stories\n\nI love this collection of stories. It has two stories: The Sneetches and Sylvester McMonkey McBean.\n\n40. There\u2019s a Wocket in My Pocket!\n\nThis is a great little book with loads of fun for the young and old alike. It is a book]" time="0.645"><properties><property name="score" value="0.0326764995" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[View Full Version : Dualshock 3 remote\n\ngravestal\n\nThe Sony PS3 console uses a standard bluetooth dongle to enable communication with a Dualshock 3 remote.\n\nThe Windows Bluetooth stack is generally a bit crap, so here are some instructions on getting the dongle working with OS X and the new Xbox 360 Bluetooth dongle:\n\n\n\nFirst of all you need a bluetooth dongle for Windows. I used a cheap one from a shop called Wom, and although I had problems getting it to work I eventually managed it, so these instructions are based on using that dongle, and you may not be able to follow them with any other.\n\n\n\nOn my Windows PC, I used the generic Windows Bluetooth drivers, but other drivers may work.\n\n\n\nSo:\n\nPlug in the dongle.\n\nOpen up the device manager (Control Panel > System > Hardware > Device Manager).\n\nFind the dongle, and right click on it.\n\nClick on Properties.\n\nClick on the Details tab.\n\nClick on the Property button (on the right hand side).\n\nScroll down to the MS info section and find the Default Format and Default Device Class. Make sure the settings are as below:\n\n\n\nDefault Format: Unicode UTF-16LE\n\nDefault Device Class: 0x07\n\nAfter all of that has been done, turn off your PC, unplug the dongle, and plug it into your Mac.\n\nOn the Mac, turn the Bluetooth dongle on (via a small switch on the dongle), and then open up the System Preferences.\n\nClick on the Bluetooth icon.\n\nYou should now see the dongle appear as a connected device. Select it and you're away!\n\nFor the PS3, you need to open up the System Preferences (via the Apple menu).\n\nClick on the Bluetooth icon.\n\nSelect the PS3 from the Devices list and click on the button that says "Advanced".\n\nThe following settings need to be configured:\n\n\n\nCharacter Set: Unicode UTF-16LE\n\nCodepage: 437\n\nYou should be all set to go!]" time="0.338"><properties><property name="score" value="0.35015294" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.35015294 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.35015294
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Tom Cruise is no stranger to acting stunts. In one of his most iconic roles, Top Gun, Cruise actually flew jets in real-life. For his new movie Jack Reacher, however, he had to leave his stunt man behind.\n\nWith director Christopher McQuarrie at the helm, Jack Reacher looks to be a hard-hitting action thriller that promises to give Cruise's daredevil side some free reign. One of the most dangerous scenes in the film? The moment Cruise's character runs into a car traveling at 50 mph.\n\nWith the help of stuntman Tim Rigby, Cruise made the risky move a reality. The actor explains that the car wasn't able to stop due to the speed at which it was traveling, so he had to make his run-in count. In order to do this, he had to use a technique that he learned in a training session with Rigby.\n\n\u201cI had to have a good run at it and come in low,\u201d Cruise explained, \u201cso that I was going to make it. I\u2019d only have a second to hit my mark.\u201d\n\nNot only did the star have to remember his own part in the stunt, but he also had to make sure to block Rigby from the camera. To see just how tough it was to make the scene work, check out the video above.\n\nJack Reacher hits theaters Dec. 21.\n\nTell us what you think of Cruise's stunt work in the comments section below or tweet us @THR.\n\nTwitter: @AmandaLeeCook\n\nEmail: [email protected]]" time="0.738"><properties><property name="score" value="0.13229951" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.13229951 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.13229951
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Selling my Peavey Valveking 112 this amp has served me well and i love it, however I am trying to move in a new direction. I am selling this for a new 6 string and my whole setup has changed. The tubes and heads are all clean. I purchased new Eminence Deltas for it, which I will give to you as well. There are also new tubes that I will give you. This is a great amp and I am only selling it because I want to go a different direction with my guitar playing. If you have any questions I am more than happy to answer them.\n\n\n\n\n\n\n\nThe 112 Valveking is more than capable of performing on any stage with its 2-12" Eminence Delta speakers, integrated spring reverb, and single-channel design. The Peavey 112 features the same sturdy, high-quality construction that you've come to expect from Peavey. The tube complement consists of two 12AX7 preamp tubes and two 6L6GC power amp tubes, which provides the 112 with 100 watts of power. Other features include Normal, Drive, and More Drive channels; independent Gain and Master controls; a 3-band EQ; an effects loop; a bright switch; a line out; and an FX-Loop/Switchable Channels footswitch.\n\nModel: ValveKing 112\n\nPart Number: 513031\n\n\n\n\n\nPeavey ValveKing 112 Guitar Amplifier Specs:\n\n\n\n\n\n\u2022 Tube-driven 100W\n\n\u2022 2-12" Eminence Delta speakers\n\n\u2022 Integrated spring reverb\n\n\u2022 Single-channel design\n\n\u2022 Drive, More Drive, and Normal channels\n\n\u2022 Independent Gain and Master controls\n\n\u2022 3-band EQ with contour\n\n\u2022 Effects loop\n\n\u2022 Bright switch\n\n\u2022 Line out\n\n\u2022 FX-Loop/Switchable Channels footswitch\n\n\u2022 Side handles for easy carrying\n\n\u2022 Rubber feet\n\n\u2022 Input: 4 ohms\n\n\u2022 Power: 100 watts\n\n\u2022 Dimensions: 18" x 27.5" x 11.75"\n\n\u2022 Weight: 31 pounds]" time="0.309"><properties><property name="score" value="0.34415314" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.34415314 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.34415314
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[\n\nBy Lee Kyung-min\n\nRapper and singer G-Dragon, from the boy band BIGBANG, has topped the Forbes Korea Power Celebrity list for the third consecutive year, while actress and K-pop star Song Hye-kyo topped the women's list for the second consecutive year.\n\nThe eighth annual list ranks celebrities' popularity based on a set of criteria that include income, assets, achievements, communication ability, and the number of hit song in the past year. The men's top 10 includes three singers, two actors, two athletes, a comedian, and a businessman, and women's top 10 consists of seven singers, two actresses, and one comedian.\n\nG-Dragon's income is estimated at 33.4 billion won ($28.5 million) this year, ranking first among Korean men, and the 28-year-old artist who recently held a world tour concert also ranked first in terms of public interest, communication ability, achievements and ability to make headlines.\n\nG-Dragon was also placed in second place in income from ads and commercials, and fourth in terms of household name, brand power, and willingness to spend.\n\nBIGBANG member Seungri was ranked second, followed by K-pop band CNBLUE's Yonghwa, and actors Yoo Ah-in and Lee Byung-hun.\n\nG-Dragon ranked first on the power men list for the last two years and Seungri for the last three years. The last artist to top the list for three years in a row was Lee Young-ae in 2010, after which the list has been led by K-pop idols and actors.\n\nYonghwa, whose band CNBLUE was one of the top-tier K-pop]" time="0.386"><properties><property name="score" value="0.012446923" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01244692 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.01244692
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Pr\xe9sentation de l'entreprise :\n\n\n\nVous souhaitez tout savoir sur les fleurs mais ne savez pas par o\xf9 commencer?\n\nVous souhaitez les conna\xeetre mais ne savez pas quelles sont les plus rares?\n\nLes f\xe9es vous entra\xeeneront dans les bois des roses, dans les sentiers des an\xe9mones et dans les bosquets des orchid\xe9es...\n\nMais attention aux elfes, ils sont aussi friands des fleurs et peuvent facilement y prendre go\xfbt...\n\n\n\nDe retour des bois, F\xe9es et Elfes vous offrent des fioles et des rosiers.\n\n\n\nL'ensemble de nos produits sont \xe9labor\xe9s avec de la cire d'abeille, de la gomme et de la paraffine.\n\nFabriqu\xe9s \xe0 la main dans un laboratoire artisanal, \xe0 partir d'encres et de pigments naturels, nos produits sont \xe0 base d'ingr\xe9dients v\xe9g\xe9taux et naturels.\n\n\n\n\n\nNos produits sont destin\xe9s aux adultes et aux enfants de plus de 10 ans.\n\n\n\nAfin de prot\xe9ger nos bo\xeetes des chocs durant le transport et de pr\xe9server vos produits, nous pr\xe9f\xe9rons utiliser les emballages en carton.\n\nLes produits contenus dans nos sachets sont \xe9galement prot\xe9g\xe9s par un film de protection.\n\n\n\nLes couleurs de nos produits peuvent varier l\xe9g\xe8rement par rapport aux photos pr\xe9sent\xe9es.\n\n\n\nLes d\xe9lais de livraison varient de 24 \xe0 48 heures (sauf jours f\xe9ri\xe9s et week-end).\n\nLes envois sont faits \xe0 l'adresse de livraison que vous avez indiqu\xe9 lors de votre commande.\n\nLes d\xe9lais de livraison ne s'appliquent pas aux commandes de fleurs.\n\n\n\nUne fois votre commande pass\xe9e, vous serez imm\xe9diatement inform\xe9(e) de son enregistrement.\n\nNous vous contacterons par mail pour vous confirmer la prise en charge de votre commande et pour vous pr\xe9ciser le d\xe9lai de livraison.\n\n\n\nEn cas de non r\xe9ception de votre commande dans les d\xe9lais, merci de nous contacter.\n\n\n\nVous pouvez b\xe9n\xe9ficier d'une livraison offerte pour une commande sup\xe9rieure \xe0 50 euros.\n\n\n\n\n\nProduits en stock (d\xe9lai moyen de livraison: 24/48h)\n\n\n\n-Empilement de pommes de pin : 12 \u20ac\n\n-Rosier en cire v\xe9g\xe9tale et ombellif\xe8re : 10 \u20ac\n\n-Fioles : 10 \u20ac\n\n\n\nProduits \xe0 l'unit\xe9\n\n-Empilement de pommes de pin : 3 \u20ac\n\n-Rosier en cire v\xe9g\xe9tale et ombellif\xe8re : 3 \u20ac\n\n-Fioles : 3 \u20ac\n\n-Cr\xe8me, corps, mains : 3 \u20ac\n\n\n\n-Barre \xe0 noix de coco : 4 \u20ac\n\n-Tartelette aux noix : 4 \u20ac\n\n\n\nFleurs et p\xe9tales\n\n\n\n-Rose blanche : 9 \u20ac\n\n-Rose rouge : 9 \u20ac\n\n-Rose jonquille : 9 \u20ac\n\n-Rose paon : 9 \u20ac\n\n-Rose pompon : 9 \u20ac\n\n-Rose matricaire : 9 \u20ac\n\n-Rose moka : 9 \u20ac\n\n-Rose fine baron : 9 \u20ac\n\n-Rose sericea : 9 \u20ac\n\n-Rose spirale : 9 \u20ac\n\n-Rose dent de lion : 9 \u20ac\n\n-Rose loraine : 9 \u20ac\n\n-Rose noisette : 9 \u20ac\n\n-Rose pouliot : 9 \u20ac\n\n-Rose ange : 9 \u20ac\n\n-Rose braque d'inde : 9 \u20ac\n\n-Rose ast\xe9riu : 9 \u20ac\n\n-Rose sylvestre : 9 \u20ac\n\n-Rose jaune : 9 \u20ac\n\n-Rose satin\xe9 : 9 \u20ac\n\n-Rose su\xe9doise : 9 \u20ac\n\n-Rose tiara : 9 \u20ac\n\n-Rose confettis : 9 \u20ac\n\n-Rose de meuse : 9 \u20ac\n\n-Rose g\xe9ante : 9 \u20ac\n\n-Rose enchere : 9 \u20ac\n\n-Rose paillettes : 9 \u20ac\n\n-Rose enfant : 9 \u20ac\n\n-Rose pompon d'Islande : 9 \u20ac\n\n-Rose latine : 9 \u20ac\n\n-Rose abricot : 9 \u20ac\n\n-Rose c\u0153ur : 9 \u20ac\n\n-Rose intergalactique : 9 \u20ac\n\n-Rose big boss : 9 \u20ac\n\n-Rose assortie \xe0 la couleur du jardin : 9 \u20ac\n\n-Rose assortie \xe0 la couleur de la porte : 9 \u20ac\n\n-Rose assortie \xe0 la couleur du maillot : 9 \u20ac\n\n-Rose parme : 9 \u20ac\n\n-Rose pomme verte : 9 \u20ac\n\n-Rose th\xe8me : 9 \u20ac\n\n-Rose beurre frais : 9 \u20ac\n\n-Rose dor\xe9 : 9 \u20ac\n\n-Rose satin : 9 \u20ac\n\n-Rose su\xe9doise et finne : 9 \u20ac\n\n-Rose big boss et finne : 9 \u20ac\n\n-Rose dor\xe9e et big boss : 9 \u20ac\n\n-Rose grise et big boss : 9 \u20ac\n\n-Rose grenadine et big boss : 9 \u20ac\n\n-Rose anthracite et big boss : 9 \u20ac\n\n-Rose rose pastel et big boss : 9 \u20ac\n\n-Rose moka et big boss : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du jardin : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la porte : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du maillot : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du g\xe2teau : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du s\xe9jour : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la table : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la chaise : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du tapis : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la pendule : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du c\u0153ur : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du t-shirt : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du colis : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de l'\xe9charpe : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la valise : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la mallette : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la ceinture : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du linge de table : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du linge de lit : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du linge de cuisine : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du sac \xe0 main : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la trousse : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la valise : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du fauteuil : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du fauteuil : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la coiffeuse : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur de la biblioth\xe8que : 9 \u20ac\n\n-Rose grise et big boss assortie \xe0 la couleur du miroir :]" time="0.446"><properties><property name="score" value="0.00041275943" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Once you\u2019ve got your SCOM environment setup, what do you do with it?\n\nThe next step is learning how to manage your environments using your new management system. There are a lot of options to learn, but you can get started with the basics fairly quickly and then move to advanced topics later. This blog is intended to introduce you to some of the basic tasks you can perform in SCOM once you have it up and running.\n\nFirst, you should know that there are three main nodes in the Operations Manager tree. The top node is the Management Group, the middle is the management server, and the bottom is the agent. We will focus on the top node and the bottom node.\n\nIn order to get started, the first thing you want to do is add one or more agent to your management group. I\u2019ll focus on adding agents to the management group. When you get to a point where you are adding lots of agents, you can set up a group for those agents and add them as a group.\n\nTo add an agent, first select the root node, and then right click the Management Servers node. Select \u201cAdd Management Server\u201d.\n\nThis will open the \u201cAdd Management Server\u201d dialog. Select the agent you want to add.\n\nNow select the agent you want to add. This dialog allows you to define the monitoring root and specifies the details for the agent.\n\nThe next step is to add the management group to the console. Once you\u2019ve added one or more management servers to the console, the next step is to add the management group. This is similar to adding the management servers, except you will be selecting the management group.\n\nThis will open the \u201cAdd Management Group\u201d dialog. Select the group you want to add.\n\nOnce you\u2019ve added the management group, you should be able to see the management servers and agent(s) within the management group. Now you\u2019ve got the basics setup.\n\nNext, you\u2019ll want to start monitoring something. Before you do anything, you should probably check out the default monitoring packs in Operations Manager. For SCOM 2007 there are two packs that are part of the default installation. They are Microsoft Monitoring Agent (64bit) and Microsoft Monitoring Agent (32bit). These packs are installed under the default management group.\n\nMonitoring a node, service or application with these packs is very easy. Select the node you want to monitor, and then select the Pack.\n\nIn this example, I selected a server and then the Microsoft Monitoring Agent (64bit) pack. This will bring up the Select and Monitor Wizard.\n\nOn the \u201cSelect the monitored resource\u201d screen, select the computer you want to monitor. The wizard is pretty self explanatory. Click \u201cNext\u201d.\n\nThe wizard will display a list of available services, applications, processes, and other entities that can be monitored.\n\nSelect the items you want to monitor. In this case, I will monitor the process \u201cexplorer.exe\u201d and the Service \u201cBITS\u201d. Click \u201cNext\u201d.\n\nThe last step is to review the information on the \u201cSelect Resources to Monitor\u201d screen and then click \u201cNext\u201d.\n\nThe wizard will display the information about the monitors you\u2019ve selected. Click \u201cNext\u201d.\n\nYou will now be taken to the \u201cSelect Management Packs to monitor\u201d screen. Select the packs you want to use. In this case, I am going to select Microsoft Monitoring Agent (64bit) and Microsoft System Center Service Manager.\n\nOnce you\u2019ve selected the appropriate management packs, click \u201cNext\u201d.\n\nThe next step is to select the default displays. There are a number of displays you can use to view the information that is gathered from the agent. You can view the data for the computer, the agents, and you can also view the inventory. The inventory allows you to view the computer hardware and software information.\n\nSelect the displays you want to use, and then click \u201cNext\u201d.\n\nThe wizard will display the information about the displays you\u2019ve selected. Click \u201cNext\u201d.\n\nThe wizard will then list the monitors and displays that are associated with the management pack. Click \u201cNext\u201d.\n\nThe last step is to review the information on the \u201cSelect Monitors and Display\u201d screen. Make sure the information is correct. If you\u2019ve chosen to monitor the system state, you\u2019ll also be asked to select the critical state you want to monitor. Once you\u2019ve verified the information, click \u201cFinish\u201d.\n\nThe \u201cMonitoring Wizard\u201d will start and monitor the information you\u2019ve selected. Click \u201cNext\u201d.\n\nIf you\u2019ve selected the \u201cAgent inventory\u201d you\u2019ll be able to view the hardware and software information. This information is useful when you are performing assessments on your systems. You can use this information to validate your environment.\n\nYou can also view the monitors for the agent. Click \u201cView Monitor\u201d.\n\nYou can drill down into the monitors and view the details about the monitored information. Click \u201cView Data\u201d.\n\nYou can also view the monitored items graphically.\n\nThese packs allow you to quickly and easily get a view of the status of the monitored entities. In the next part of this series, I will talk about creating your own monitoring packs and will include examples.]" time="0.330"><properties><property name="score" value="0.0006084038" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[the intractable issue of euthanasia\n\nRecent Examples on the Web\n\nThis is a good moment to highlight the intractable problem of lagging political reform in Myanmar. David Lague, WSJ, "Myanmar\u2019s Democracy Movement Is Fading," 21 June 2018\n\nThis is particularly true in debates over intractable problems, like how to maintain and improve Medicare and Social Security for the long term. Tom Avril, Philly.com, "A government shutdown is a failure for everyone involved," 19 Jan. 2018\n\nThe team found that the early injections were successful at clearing the amyloid plaques, a hallmark of the disease, and that in mice injected at an earlier stage of the disease, the vaccine eliminated almost all amyloid plaques that formed over the following two months. Allison Barrie, Fox News, "Sip, gulp, shot: Scientists develop blood test to detect Alzheimer's in 5 minutes," 8 Aug. 2018\n\nSome of the many intractable problems that the US military has in this fight: How do you train soldiers to counter a terrorist group when your own government forbids you from talking about the group by name? Dan Lamothe, chicagotribune.com, "A U.S. Marine officer set off a debate: What's the military's role in countering ISIS' message?," 12 Apr. 2018\n\nAfter watching an emotionally trying game between the Blue Jays and the New York Yankees, Maddon was asked if baseball might be better suited for more intractable rivalries like the one that has developed between the Cubs and the Cardinals. Paul Sullivan, chicagotribune.com, "Joe Maddon on rivalries: 'I don't think anything would be wrong with a few more,' " 15 Mar. 2018\n\nBut how the series will ultimately end depends on many factors, and the conclusions may be more intractable than people realize. David Volodzko, CNN, "No more thrillers: The debate over who will win the World Cup final," 13 July 2018\n\nThese example sentences are selected automatically from various online news sources to reflect current usage of the word 'intractable.' Views expressed in the examples do not represent the opinion of Merriam-Webster or its editors. Send us feedback.]" time="0.290"><properties><property name="score" value="0.0019516486" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00195165 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.00195165
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[JOSEY WALES GIVE A DIRE WARNING ABOUT COMPROMISING ON YOUR FAITH FOR THE SAKE OF COMFORT\n\nThe band Josey Wales is a pop/punk/emo/indie band from Tewksbury, Massachusetts. Josey Wales was started in 2008. They are currently signed with NiznoRecords.com. Josey Wales have released two EPs to date and one full length album. Their debut EP "And So It Begins..." was released in January 2009. Their follow up EP "The Way It Wasn't" was released in November of the same year. Their debut album "Losing The War" was released on October 12, 2010 and features the single "Instrumentals", as well as the title track "Losing The War", which is also the name of their first tour. The band's first music video was "Instrumentals" and it was released on May 13, 2010. Their second music video was for the single "A Light Amongst All This Darkness", and was released on May 31, 2011.\n\nJosey Wales is a Christian band. They also have stated that they are a band for everyone. In an interview on the August 13th, 2010 episode of CincyMusic.com Live! Josey Wales said that they're trying to bring together two completely different types of fans in Christian and non-Christian. Their goal is to be a bridge for people that might be on opposite sides of the fence. Their main goal is to tell the world about Jesus Christ, and what it means to be a Christian. They are not afraid to be themselves, and they want people to see their passion for Christ.\n\nJosey Wales has recently done some regional tours, one with Up Up Down Down Left Right Left Right B A Start (who's lead singer is Max Bemis of Say Anything) and they've done a tour with For All]" time="0.275"><properties><property name="score" value="0.07717216" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Khevron\n\n(Tollerman)\n\nI think it's best not to be a part of this kind of mess and just let everyone do what they want with it.\n\nI really don't care how you decide, because I probably won't be playing with you again.\n\nYou say I made you quit... but you didn't have to quit the clan because of me.\n\nNo, I didn't care if you quit or not. I just said it'd be cool if you didn't quit.\n\nAnyways, I probably won't be on as much, so I won't be seeing you guys again.\n\nI'll be playing CS:S probably.\n\nLaterz\n\n\n\n\n\nI understand that what I said last night may have been misconstrued, but what I was saying was that you're making things seem more personal than they really are.I didn't care about what you did or didn't do. I was just saying it would be cool if you didn't quit, since it's no fun without people to play with.But if you're going to quit anyway, it's not my business. That's what I was trying to say. And don't worry about this being a "mess", it's not really that important in the grand scheme of things. Just try to do what you think is best, I guess.]" time="0.292"><properties><property name="score" value="0.027973535" /></properties></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[By Rachel Katz\n\nI want to thank everyone for their interest in the Food for Thought events this week and to announce that we are taking the event off of our regular weekly rotation.\n\nThe outcome of the events at Chicago and at NYU\u2014the students are going to be able to pursue what they were hoping to pursue from the first moment of the project\u2014this is good for the Food for Thought project, good for the students, good for the nonprofit, and good for the University.\n\nWhat happened this week?\n\nThe point of this week was to get information about the types of events that would work best for our audience\u2014our audience being the students. And after seeing how the event in Chicago went, we decided to go ahead with this week\u2019s events as planned.\n\nThe second event at NYU went very well. The student population at NYU is very different than the population at the University of Chicago. It is a lot smaller and it is not a natural fit for our events.\n\nWe want to serve the students and do so in a way that works for them and so after talking to the students in New York, we decided to move Food for Thought off of our weekly rotation for the fall. It is just not a good fit for them right now.\n\nWhat\u2019s next?\n\nWe\u2019re trying to make sure we\u2019re moving Food for Thought forward and not backward. The goal here is not to try and find a place for Food for Thought that it will fit in, the goal is to find a place for Food for Thought that it will fit in.\n\nIf we have another event at the University of Chicago that\u2019s a success, we\u2019ll move forward and try to get one at another school.\n\nWe\u2019ll also be using the extra time we have this week to work on logistics and see if there is anything we need to change in the way we organize our events in the future.\n\nWhat\u2019s next for your organization?\n\nWe\u2019re still going to be fundraising and we\u2019re still going to be putting on events, but we\u2019re going to be using the extra time this week to come up with new ideas for future events.\n\nHow can students get involved with Food for Thought?\n\nStudents can volunteer at our events. We also have a contact on our website for students who are interested in volunteering. And we\u2019re looking for ideas and we\u2019re always interested in hearing from students.\n\nIs the Food for Thought logo going to change?\n\nIt\u2019s not going to change anytime soon, but we are looking into other things we can do to get more publicity for the Food for Thought project.\n\nWe\u2019re looking into new ways to do fundraising. We\u2019re looking at getting the word out there more, and it\u2019s all because of what the students have done at these events this week.\n\nIf students had one question to ask you, what would it be?\n\n\u201cWhy do you do what you do?\u201d I think it\u2019s because when I was in college, it was really hard to make friends, it was really hard to figure out where I fit in, and it was really hard to figure out where I was going to work. And so now I\u2019m trying to help students be successful.\n\nAnd even though I wasn\u2019t successful when I was in college, I\u2019m just trying to pay it forward.\n\nhttp://www.uchicago.edu/student-life/info/food-thought/]" time="0.326"><properties><property name="score" value="0.30786014" /></properties><failure message="AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.30786014 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/GPT-3-175b_samples.jsonl is an LLM-generated sample, misclassified as human-generated with confidence 0.30786014
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_gpt3_jsonl[Zasugerujte cestovate\u013eom, \u017ee je mo\u017en\xe9 vstupova\u0165 do Franc\xfazska nehnuteln\xfdm tovarom\n\nNehnuteln\xfd tovar (tovar, ktor\xfd je osobitn\xfdm odpadom v zmysle Par\xed\u017eskeho protokolu) je tovar, ktor\xfd sa nepodlieha poplatkom v r\xe1mci prijatia za dovoz tovaru do Franc\xfazska, alebo ktor\xfd vyzer\xe1 ako osobitn\xfd odpad, alebo ktor\xfd nie je pr\xedslu\u0161n\xfd ku dovoze (napr. vzorky zbo\u017e\xed, marketingov\xe9 predmety, dovolenkov\xe9 z\xe1le\u017eitosti). Nie je rovnako vhodn\xe9 zasugerova\u0165 cestovate\u013eom, \u017ee pr\xe1vna \xfaprava nehnuteln\xe9ho tovaru je predmetom doh\xf4d medzi st\xe1vkovanou firmou a dod\xe1vate\u013eom, alebo medzi dopytovate\u013eom a dod\xe1vate\u013eom.\n\nInformujte cestovate\u013ea o tom, \u017ee by mohol nahradi\u0165 nehnuteln\xfd tovar nehnuteln\xfdm tovarom\n\nAk je nehnuteln\xfd tovar na po\u017eiadanie k\xfapou, nehnuteln\xfd tovar nahradi\u0165 nov\xfdm za rovnak\xfdch podmienok a v rovnakom mno\u017estve.\n\nVzor: \u201eV\u0161etky z\xe1kazn\xedcke odkazy, ktor\xe9 kupuj\xfa nehnuteln\xfd tovar, dostan\xfa zadarmo priamo od dod\xe1vate\u013ea tovaru (napr. uk\xe1\u017eku).\u201c\n\nDokonca je lep\u0161ie pon\xfaknu\u0165 cestovate\u013eovi k\xfapu za rovnak\xe9 podmienky (napr. dajte mu dar\u010dek s\xfavisiaci s t\xfdmto tovarom), aby nikto nie jeho nepote\u0161il.\n\nCestovate\u013eovi mus\xedte prezradi\u0165 v\u0161etky dostupn\xe9 inform\xe1cie\n\nCestovate\u013e mus\xed vedie\u0165 v\u0161etky dostupn\xe9 inform\xe1cie o tejto produkcii (tovaru), o tom, ako sa mus\xed s \u0148ou zaobch\xe1dza\u0165 (napr. pou\u017e\xedva\u0165, recyklova\u0165, vykon\xe1va\u0165 pr\xedpravn\xe9 pr\xe1ce, \u010di sa pri n\xe1vrate domov dosta\u0165 k recykl\xe1cii).\n\nN\xe1zov a kontaktn\xe9 \xfadaje dod\xe1vate\u013ea v\u0161ak musia by\u0165 dostupn\xe9. Ak chcete o tom, ako sa m\xe1 tovar spr\xe1va\u0165 (napr. zlikvidova\u0165, recyklova\u0165, opravi\u0165), mus\xedte poda\u0165 cestovate\u013eovi dostupn\xe9 inform\xe1cie a inform\xe1c]" time="0.308"><properties><property name="score" value="0.011883761" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i0]" time="0.305"><properties><property name="score" value="0.0006882656" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i1]" time="0.321"><properties><property name="score" value="0.023728553" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i2]" time="0.275"><properties><property name="score" value="0.0038540922" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i3]" time="0.320"><properties><property name="score" value="0.0005885433" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i4]" time="0.315"><properties><property name="score" value="0.14632107" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i5]" time="0.257"><properties><property name="score" value="0.0031564168" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i6]" time="0.258"><properties><property name="score" value="0.00072351756" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i7]" time="0.313"><properties><property name="score" value="0.0005744072" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i8]" time="0.326"><properties><property name="score" value="0.0027960476" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i9]" time="0.406"><properties><property name="score" value="0.003630932" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i10]" time="0.453"><properties><property name="score" value="0.0020212224" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i11]" time="0.318"><properties><property name="score" value="0.025957119" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i12]" time="0.271"><properties><property name="score" value="0.8380261" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.8380261 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.8380261
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i13]" time="0.337"><properties><property name="score" value="0.002555196" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i14]" time="0.426"><properties><property name="score" value="0.011970201" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i15]" time="1.303"><properties><property name="score" value="0.0006028587" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i16]" time="0.299"><properties><property name="score" value="0.008729441" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i17]" time="0.349"><properties><property name="score" value="0.15942355" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i18]" time="0.310"><properties><property name="score" value="0.0009092193" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i19]" time="0.322"><properties><property name="score" value="0.0022868593" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i20]" time="0.374"><properties><property name="score" value="0.00209242" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i21]" time="0.303"><properties><property name="score" value="0.0009527098" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i22]" time="0.309"><properties><property name="score" value="0.009404838" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i23]" time="0.385"><properties><property name="score" value="0.019059809" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i24]" time="0.345"><properties><property name="score" value="0.012301062" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i25]" time="0.489"><properties><property name="score" value="0.08068889" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i26]" time="1.152"><properties><property name="score" value="0.0046342295" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i27]" time="0.316"><properties><property name="score" value="0.005632478" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i28]" time="0.283"><properties><property name="score" value="0.016161133" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i29]" time="0.307"><properties><property name="score" value="0.006253666" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i30]" time="0.317"><properties><property name="score" value="0.0027285062" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i31]" time="0.339"><properties><property name="score" value="0.0195023" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i32]" time="0.355"><properties><property name="score" value="0.0011159552" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i33]" time="0.308"><properties><property name="score" value="0.0026707135" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i34]" time="0.383"><properties><property name="score" value="0.00575351" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i35]" time="0.375"><properties><property name="score" value="0.0041101" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i36]" time="0.348"><properties><property name="score" value="0.004221068" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i37]" time="0.500"><properties><property name="score" value="0.005015392" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i38]" time="0.321"><properties><property name="score" value="0.001789218" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i39]" time="0.402"><properties><property name="score" value="0.087381765" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i40]" time="0.357"><properties><property name="score" value="0.030474247" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i41]" time="0.425"><properties><property name="score" value="0.28830934" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i42]" time="0.305"><properties><property name="score" value="0.004929909" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i43]" time="0.327"><properties><property name="score" value="0.0009132752" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i44]" time="0.327"><properties><property name="score" value="0.099042326" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i45]" time="0.343"><properties><property name="score" value="0.011950413" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i46]" time="0.309"><properties><property name="score" value="0.045277353" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i47]" time="0.322"><properties><property name="score" value="0.0024810978" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i48]" time="0.297"><properties><property name="score" value="0.012599862" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i49]" time="0.286"><properties><property name="score" value="0.0005457812" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i50]" time="0.281"><properties><property name="score" value="0.003139675" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i51]" time="0.309"><properties><property name="score" value="0.02523775" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i52]" time="0.275"><properties><property name="score" value="0.020725546" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i53]" time="0.298"><properties><property name="score" value="0.0008786136" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i54]" time="0.313"><properties><property name="score" value="0.0009340944" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i55]" time="0.341"><properties><property name="score" value="3.8298178" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 3.8298178 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 3.8298178
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i56]" time="0.309"><properties><property name="score" value="0.05874675" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i57]" time="0.302"><properties><property name="score" value="0.068051584" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i58]" time="0.310"><properties><property name="score" value="0.012360984" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i59]" time="0.330"><properties><property name="score" value="0.0050157504" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i60]" time="0.316"><properties><property name="score" value="0.031361457" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i61]" time="0.390"><properties><property name="score" value="0.10061689" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i62]" time="0.313"><properties><property name="score" value="0.012307278" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i63]" time="0.301"><properties><property name="score" value="1.9925324" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.9925324 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.9925324
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i64]" time="0.316"><properties><property name="score" value="0.0024399296" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i65]" time="0.280"><properties><property name="score" value="0.0025512516" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i66]" time="0.315"><properties><property name="score" value="0.0014571573" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i67]" time="0.277"><properties><property name="score" value="0.003987533" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i68]" time="0.300"><properties><property name="score" value="0.01982235" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i69]" time="1.223"><properties><property name="score" value="0.0089086965" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i70]" time="0.308"><properties><property name="score" value="0.021742852" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i71]" time="0.297"><properties><property name="score" value="0.0030302005" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i72]" time="0.333"><properties><property name="score" value="0.0018293463" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i73]" time="0.282"><properties><property name="score" value="0.17957687" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i74]" time="0.407"><properties><property name="score" value="0.001067625" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i75]" time="0.304"><properties><property name="score" value="0.0013148017" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i76]" time="0.310"><properties><property name="score" value="0.0007863274" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i77]" time="0.296"><properties><property name="score" value="0.021425419" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i78]" time="0.347"><properties><property name="score" value="0.005990994" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i79]" time="0.399"><properties><property name="score" value="0.000924968" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i80]" time="0.295"><properties><property name="score" value="0.1188786" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i81]" time="0.307"><properties><property name="score" value="2.0993223" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.0993223 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.0993223
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i82]" time="0.336"><properties><property name="score" value="0.020779831" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i83]" time="1.030"><properties><property name="score" value="1.6636122" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.6636122 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.6636122
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i84]" time="0.315"><properties><property name="score" value="0.20050353" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i85]" time="0.290"><properties><property name="score" value="0.10316318" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i86]" time="0.296"><properties><property name="score" value="0.00077761855" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i87]" time="0.344"><properties><property name="score" value="0.025417786" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i88]" time="0.309"><properties><property name="score" value="0.06501842" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i89]" time="0.317"><properties><property name="score" value="0.00049324025" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i90]" time="0.370"><properties><property name="score" value="0.001228981" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i91]" time="0.317"><properties><property name="score" value="0.008196861" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i92]" time="0.334"><properties><property name="score" value="0.00036098433" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i93]" time="0.329"><properties><property name="score" value="0.050119553" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i94]" time="0.318"><properties><property name="score" value="0.071721554" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i95]" time="0.389"><properties><property name="score" value="0.026683979" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i96]" time="0.387"><properties><property name="score" value="0.064457886" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i97]" time="0.419"><properties><property name="score" value="0.039123457" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i98]" time="0.327"><properties><property name="score" value="0.002257886" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i99]" time="0.303"><properties><property name="score" value="0.00043700845" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i100]" time="0.357"><properties><property name="score" value="0.1705746" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i101]" time="0.403"><properties><property name="score" value="0.0006717416" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i102]" time="0.403"><properties><property name="score" value="0.0007810784" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i103]" time="0.387"><properties><property name="score" value="0.050599273" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i104]" time="0.428"><properties><property name="score" value="0.0013544315" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i105]" time="0.400"><properties><property name="score" value="0.018136328" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i106]" time="0.392"><properties><property name="score" value="0.00213662" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i107]" time="0.408"><properties><property name="score" value="0.024142642" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i108]" time="0.446"><properties><property name="score" value="0.008330098" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i109]" time="0.481"><properties><property name="score" value="0.0009666712" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i110]" time="0.429"><properties><property name="score" value="0.0005178132" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i111]" time="0.428"><properties><property name="score" value="0.011963021" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i112]" time="0.561"><properties><property name="score" value="0.00062671263" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i113]" time="0.383"><properties><property name="score" value="0.09131671" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i114]" time="0.417"><properties><property name="score" value="0.005213574" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i115]" time="0.364"><properties><property name="score" value="0.0006141873" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i116]" time="0.448"><properties><property name="score" value="0.001012133" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i117]" time="0.633"><properties><property name="score" value="0.051963788" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i118]" time="0.647"><properties><property name="score" value="0.0018438551" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i119]" time="0.438"><properties><property name="score" value="0.0076341215" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i120]" time="0.399"><properties><property name="score" value="0.17639132" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i121]" time="0.319"><properties><property name="score" value="0.0016637112" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i122]" time="0.352"><properties><property name="score" value="0.0028680747" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i123]" time="0.330"><properties><property name="score" value="0.0032928167" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i124]" time="0.317"><properties><property name="score" value="0.0063812486" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i125]" time="0.330"><properties><property name="score" value="0.0021207326" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i126]" time="0.297"><properties><property name="score" value="0.0005124441" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i127]" time="0.329"><properties><property name="score" value="0.0064014043" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i128]" time="0.316"><properties><property name="score" value="0.00068480574" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i129]" time="0.321"><properties><property name="score" value="0.0005052878" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i130]" time="0.291"><properties><property name="score" value="0.0010514549" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i131]" time="0.328"><properties><property name="score" value="0.0069591436" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i132]" time="0.306"><properties><property name="score" value="0.39777055" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i133]" time="0.302"><properties><property name="score" value="0.26240024" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i134]" time="0.352"><properties><property name="score" value="0.0012537473" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i135]" time="0.345"><properties><property name="score" value="0.008331841" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i136]" time="0.321"><properties><property name="score" value="0.02909734" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i137]" time="0.443"><properties><property name="score" value="0.012589" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i138]" time="0.379"><properties><property name="score" value="0.01577316" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i139]" time="0.319"><properties><property name="score" value="0.0031048162" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i140]" time="0.391"><properties><property name="score" value="0.069007605" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i141]" time="0.294"><properties><property name="score" value="0.030446164" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i142]" time="0.341"><properties><property name="score" value="0.0022274174" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i143]" time="0.334"><properties><property name="score" value="0.00083410944" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i144]" time="0.303"><properties><property name="score" value="0.0007393807" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i145]" time="0.259"><properties><property name="score" value="0.0019139628" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i146]" time="0.330"><properties><property name="score" value="0.0008201507" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i147]" time="0.342"><properties><property name="score" value="0.06476484" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i148]" time="0.343"><properties><property name="score" value="0.0013792025" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i149]" time="0.451"><properties><property name="score" value="0.0033715777" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i150]" time="0.401"><properties><property name="score" value="0.010620366" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i151]" time="0.333"><properties><property name="score" value="0.14810291" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i152]" time="1.411"><properties><property name="score" value="0.00070842594" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i153]" time="0.288"><properties><property name="score" value="0.0011239534" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i154]" time="0.297"><properties><property name="score" value="0.0034578817" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i155]" time="0.380"><properties><property name="score" value="0.00059617736" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i156]" time="0.326"><properties><property name="score" value="0.012592439" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i157]" time="0.300"><properties><property name="score" value="0.030538524" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i158]" time="0.300"><properties><property name="score" value="0.0626954" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i159]" time="0.385"><properties><property name="score" value="0.041013468" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i160]" time="0.337"><properties><property name="score" value="0.34978762" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i161]" time="0.336"><properties><property name="score" value="0.0008129916" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i162]" time="0.309"><properties><property name="score" value="0.0017456891" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i163]" time="0.308"><properties><property name="score" value="0.03242883" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i164]" time="0.312"><properties><property name="score" value="0.0059358897" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i165]" time="0.343"><properties><property name="score" value="0.0016304567" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i166]" time="0.325"><properties><property name="score" value="0.038463615" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i167]" time="0.300"><properties><property name="score" value="0.00888013" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i168]" time="0.299"><properties><property name="score" value="0.004990171" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i169]" time="0.300"><properties><property name="score" value="0.0016371437" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i170]" time="0.304"><properties><property name="score" value="0.006475911" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i171]" time="0.313"><properties><property name="score" value="0.050437335" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i172]" time="0.336"><properties><property name="score" value="0.0014360264" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i173]" time="0.344"><properties><property name="score" value="0.00088577176" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i174]" time="0.315"><properties><property name="score" value="0.0009310532" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i175]" time="0.304"><properties><property name="score" value="0.0007066368" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i176]" time="1.717"><properties><property name="score" value="1.0340343" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i177]" time="0.387"><properties><property name="score" value="0.0019004669" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i178]" time="0.403"><properties><property name="score" value="0.012433525" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i179]" time="0.366"><properties><property name="score" value="0.0012609692" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i180]" time="0.503"><properties><property name="score" value="0.0014439647" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i181]" time="0.345"><properties><property name="score" value="0.0026608522" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i182]" time="0.346"><properties><property name="score" value="0.31764337" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i183]" time="0.396"><properties><property name="score" value="0.5230047" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i184]" time="0.320"><properties><property name="score" value="0.00069983635" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i185]" time="0.334"><properties><property name="score" value="0.22261384" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i186]" time="3.289"><properties><property name="score" value="0.0009784222" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i187]" time="0.317"><properties><property name="score" value="0.013843578" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i188]" time="0.271"><properties><property name="score" value="0.009059112" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i189]" time="0.329"><properties><property name="score" value="0.14952281" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i190]" time="0.390"><properties><property name="score" value="0.23437643" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i191]" time="0.311"><properties><property name="score" value="0.0040716166" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i192]" time="0.289"><properties><property name="score" value="0.0010916695" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i193]" time="0.316"><properties><property name="score" value="3.3979774" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 3.3979774 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 3.3979774
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i194]" time="0.294"><properties><property name="score" value="0.0014365634" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i195]" time="0.290"><properties><property name="score" value="0.00042079046" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i196]" time="0.310"><properties><property name="score" value="0.0037143282" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i197]" time="0.292"><properties><property name="score" value="0.0008576733" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i198]" time="0.310"><properties><property name="score" value="0.0014626485" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i199]" time="0.300"><properties><property name="score" value="0.00087610644" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i200]" time="0.300"><properties><property name="score" value="0.0017323744" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i201]" time="0.298"><properties><property name="score" value="0.19970357" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i202]" time="0.357"><properties><property name="score" value="0.0031747157" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i203]" time="0.335"><properties><property name="score" value="0.0007527424" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i204]" time="0.315"><properties><property name="score" value="0.00414739" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i205]" time="0.386"><properties><property name="score" value="0.0011265778" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i206]" time="0.322"><properties><property name="score" value="0.0007913397" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i207]" time="0.315"><properties><property name="score" value="0.00053093175" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i208]" time="0.305"><properties><property name="score" value="0.010371418" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i209]" time="0.301"><properties><property name="score" value="0.010478087" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i210]" time="0.314"><properties><property name="score" value="0.012615376" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i211]" time="0.311"><properties><property name="score" value="0.026026795" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i212]" time="0.293"><properties><property name="score" value="2.6933408" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.6933408 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.6933408
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i213]" time="0.287"><properties><property name="score" value="0.010105798" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i214]" time="0.264"><properties><property name="score" value="0.0012036186" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i215]" time="0.289"><properties><property name="score" value="0.6904295" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.6904295 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.6904295
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i216]" time="0.331"><properties><property name="score" value="0.11396127" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i217]" time="0.331"><properties><property name="score" value="0.0063362597" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i218]" time="0.310"><properties><property name="score" value="0.63433564" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.63433564 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.63433564
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i219]" time="0.298"><properties><property name="score" value="0.015821725" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i220]" time="0.366"><properties><property name="score" value="0.00092974096" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i221]" time="0.342"><properties><property name="score" value="0.005203389" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i222]" time="1.876"><properties><property name="score" value="0.021012085" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i223]" time="0.311"><properties><property name="score" value="0.07511013" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i224]" time="0.360"><properties><property name="score" value="0.0032120263" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i225]" time="0.360"><properties><property name="score" value="0.03195487" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i226]" time="0.298"><properties><property name="score" value="0.0021818394" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i227]" time="0.317"><properties><property name="score" value="0.0026003723" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i228]" time="0.301"><properties><property name="score" value="0.007588597" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i229]" time="0.300"><properties><property name="score" value="0.15595126" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i230]" time="0.367"><properties><property name="score" value="0.03518531" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i231]" time="0.885"><properties><property name="score" value="2.6166494" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.6166494 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.6166494
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i232]" time="0.311"><properties><property name="score" value="0.0006071512" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i233]" time="1.250"><properties><property name="score" value="0.0006471705" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i234]" time="0.318"><properties><property name="score" value="0.16977532" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i235]" time="0.322"><properties><property name="score" value="0.0017410297" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i236]" time="0.328"><properties><property name="score" value="0.00050003984" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i237]" time="0.313"><properties><property name="score" value="0.022488663" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i238]" time="0.327"><properties><property name="score" value="0.0018430187" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i239]" time="0.327"><properties><property name="score" value="0.10084333" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i240]" time="0.307"><properties><property name="score" value="0.00062921696" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i241]" time="0.298"><properties><property name="score" value="2.0754628" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.0754628 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 2.0754628
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i242]" time="0.325"><properties><property name="score" value="0.013374711" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i243]" time="0.314"><properties><property name="score" value="0.0023708593" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i244]" time="0.321"><properties><property name="score" value="0.0012960006" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i245]" time="5.194"><properties><property name="score" value="0.014645457" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i246]" time="4.950"><properties><property name="score" value="1.032282" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i247]" time="7.013"><properties><property name="score" value="0.016759368" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i248]" time="0.471"><properties><property name="score" value="0.0011471653" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i249]" time="0.285"><properties><property name="score" value="0.01514796" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i250]" time="0.347"><properties><property name="score" value="0.013462789" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i251]" time="0.303"><properties><property name="score" value="0.0014350718" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i252]" time="0.310"><properties><property name="score" value="0.0018414661" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i253]" time="0.330"><properties><property name="score" value="0.016233096" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i254]" time="0.305"><properties><property name="score" value="1.8714621" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.8714621 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.8714621
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i255]" time="0.338"><properties><property name="score" value="0.021096209" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i256]" time="0.400"><properties><property name="score" value="0.00073019793" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i257]" time="0.351"><properties><property name="score" value="0.0005519829" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i258]" time="0.320"><properties><property name="score" value="0.0012133458" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i259]" time="0.298"><properties><property name="score" value="0.0026370648" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i260]" time="0.306"><properties><property name="score" value="0.00060882105" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i261]" time="0.311"><properties><property name="score" value="0.03141976" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i262]" time="0.304"><properties><property name="score" value="0.0009108892" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i263]" time="0.357"><properties><property name="score" value="0.0010004373" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i264]" time="0.320"><properties><property name="score" value="0.01317249" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i265]" time="0.338"><properties><property name="score" value="0.02471989" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i266]" time="0.314"><properties><property name="score" value="0.008488482" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i267]" time="0.313"><properties><property name="score" value="0.0047076484" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i268]" time="0.377"><properties><property name="score" value="0.000926757" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i269]" time="0.379"><properties><property name="score" value="0.016174458" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i270]" time="0.387"><properties><property name="score" value="0.0008115602" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i271]" time="0.352"><properties><property name="score" value="1.4407504" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.4407504 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.4407504
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i272]" time="0.326"><properties><property name="score" value="0.0022905632" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i273]" time="0.349"><properties><property name="score" value="0.0070485757" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i274]" time="0.299"><properties><property name="score" value="0.10901289" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i275]" time="0.269"><properties><property name="score" value="0.017222792" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i276]" time="0.291"><properties><property name="score" value="0.0004393945" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i277]" time="0.288"><properties><property name="score" value="0.00082516216" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i278]" time="0.297"><properties><property name="score" value="0.00086626475" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i279]" time="0.295"><properties><property name="score" value="0.18635242" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i280]" time="0.337"><properties><property name="score" value="0.005070925" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i281]" time="0.342"><properties><property name="score" value="0.0007526251" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i282]" time="0.269"><properties><property name="score" value="0.002418061" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i283]" time="0.326"><properties><property name="score" value="1.9019905" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.9019905 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.9019905
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i284]" time="0.286"><properties><property name="score" value="0.0021422359" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i285]" time="0.277"><properties><property name="score" value="0.3130675" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i286]" time="1.694"><properties><property name="score" value="0.0011923988" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i287]" time="0.278"><properties><property name="score" value="0.0010602257" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i288]" time="0.279"><properties><property name="score" value="0.0018399127" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i289]" time="0.288"><properties><property name="score" value="0.011869706" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i290]" time="0.315"><properties><property name="score" value="0.0016991772" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i291]" time="0.359"><properties><property name="score" value="0.0013941242" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i292]" time="0.376"><properties><property name="score" value="0.004432268" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i293]" time="0.282"><properties><property name="score" value="0.0006769914" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i294]" time="0.304"><properties><property name="score" value="0.0007522656" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i295]" time="0.336"><properties><property name="score" value="0.0005629566" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i296]" time="0.416"><properties><property name="score" value="0.0006028587" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i297]" time="2.778"><properties><property name="score" value="0.0004380823" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i298]" time="0.363"><properties><property name="score" value="0.0013066843" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i299]" time="0.262"><properties><property name="score" value="0.0009792567" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i300]" time="0.295"><properties><property name="score" value="0.0077970196" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i301]" time="0.363"><properties><property name="score" value="0.004325048" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i302]" time="0.392"><properties><property name="score" value="0.00085683604" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i303]" time="0.317"><properties><property name="score" value="0.003674064" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i304]" time="0.371"><properties><property name="score" value="0.014019222" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i305]" time="0.307"><properties><property name="score" value="0.038613774" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i306]" time="0.403"><properties><property name="score" value="0.024866777" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i307]" time="0.443"><properties><property name="score" value="0.00080738415" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i308]" time="0.517"><properties><property name="score" value="0.0030183021" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i309]" time="0.389"><properties><property name="score" value="0.37642848" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.37642848 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 0.37642848
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i310]" time="0.432"><properties><property name="score" value="0.0016527253" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i311]" time="0.481"><properties><property name="score" value="0.0016385759" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i312]" time="0.417"><properties><property name="score" value="0.12595212" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i313]" time="0.358"><properties><property name="score" value="0.0004478621" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i314]" time="0.358"><properties><property name="score" value="0.0068930606" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i315]" time="0.351"><properties><property name="score" value="0.0009057576" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i316]" time="0.321"><properties><property name="score" value="0.0007313909" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i317]" time="0.322"><properties><property name="score" value="0.0014415766" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i318]" time="0.340"><properties><property name="score" value="0.00056760764" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i319]" time="0.307"><properties><property name="score" value="0.24889082" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i320]" time="0.333"><properties><property name="score" value="0.00052687584" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i321]" time="0.335"><properties><property name="score" value="0.00097580056" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i322]" time="0.318"><properties><property name="score" value="0.002079875" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i323]" time="0.354"><properties><property name="score" value="0.00087753887" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i324]" time="0.334"><properties><property name="score" value="0.015265061" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i325]" time="0.306"><properties><property name="score" value="0.0053848326" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i326]" time="0.339"><properties><property name="score" value="0.00072733505" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i327]" time="0.329"><properties><property name="score" value="0.0016564281" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i328]" time="0.319"><properties><property name="score" value="0.0004576428" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i329]" time="0.401"><properties><property name="score" value="0.010942045" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i330]" time="0.333"><properties><property name="score" value="0.026119297" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i331]" time="0.371"><properties><property name="score" value="0.00101106" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i332]" time="0.294"><properties><property name="score" value="0.0039426507" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i333]" time="0.329"><properties><property name="score" value="0.0019917197" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i334]" time="0.339"><properties><property name="score" value="0.000843953" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i335]" time="0.408"><properties><property name="score" value="0.0016586959" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i336]" time="0.370"><properties><property name="score" value="0.0009598689" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i337]" time="0.387"><properties><property name="score" value="0.0020648255" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i338]" time="0.426"><properties><property name="score" value="0.00081645243" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i339]" time="0.622"><properties><property name="score" value="0.0037560277" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i340]" time="0.413"><properties><property name="score" value="0.04222535" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i341]" time="0.353"><properties><property name="score" value="0.0012003971" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i342]" time="0.422"><properties><property name="score" value="0.00046921265" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i343]" time="0.353"><properties><property name="score" value="0.003036479" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i344]" time="0.373"><properties><property name="score" value="0.010571511" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i345]" time="0.535"><properties><property name="score" value="0.0020350807" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i346]" time="0.431"><properties><property name="score" value="0.0006472888" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i347]" time="0.347"><properties><property name="score" value="0.25012672" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i348]" time="0.339"><properties><property name="score" value="0.0041034576" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i349]" time="0.323"><properties><property name="score" value="0.042956743" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i350]" time="0.328"><properties><property name="score" value="0.12789017" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i351]" time="0.465"><properties><property name="score" value="0.0015274144" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i352]" time="0.365"><properties><property name="score" value="0.00044845813" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i353]" time="0.358"><properties><property name="score" value="0.0012003971" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i354]" time="0.435"><properties><property name="score" value="0.015319169" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i355]" time="0.490"><properties><property name="score" value="0.003220698" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i356]" time="0.404"><properties><property name="score" value="0.2519015" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i357]" time="0.365"><properties><property name="score" value="0.0011287275" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i358]" time="0.354"><properties><property name="score" value="0.0010231105" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i359]" time="1.183"><properties><property name="score" value="0.00052437244" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i360]" time="0.430"><properties><property name="score" value="0.0048978627" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i361]" time="0.366"><properties><property name="score" value="0.009753028" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i362]" time="0.771"><properties><property name="score" value="0.0005098215" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i363]" time="0.368"><properties><property name="score" value="0.01164421" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i364]" time="0.371"><properties><property name="score" value="0.0030893907" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i365]" time="0.374"><properties><property name="score" value="0.14984106" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i366]" time="2.808"><properties><property name="score" value="0.00104668" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i367]" time="0.368"><properties><property name="score" value="0.072569795" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i368]" time="0.399"><properties><property name="score" value="0.0011733621" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i369]" time="2.882"><properties><property name="score" value="0.0013980046" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i370]" time="0.435"><properties><property name="score" value="0.007848487" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i371]" time="0.392"><properties><property name="score" value="0.00092246174" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i372]" time="0.384"><properties><property name="score" value="0.0020555067" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i373]" time="0.340"><properties><property name="score" value="0.009050271" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i374]" time="0.351"><properties><property name="score" value="0.0013546699" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i375]" time="0.443"><properties><property name="score" value="0.004675908" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i376]" time="0.393"><properties><property name="score" value="0.020651678" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i377]" time="0.381"><properties><property name="score" value="0.017131716" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i378]" time="0.341"><properties><property name="score" value="0.0032016824" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i379]" time="0.335"><properties><property name="score" value="0.0025327855" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i380]" time="0.307"><properties><property name="score" value="0.0016112922" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i381]" time="0.291"><properties><property name="score" value="0.0004490551" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i382]" time="0.306"><properties><property name="score" value="0.004024818" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i383]" time="0.393"><properties><property name="score" value="0.7175148" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i384]" time="0.295"><properties><property name="score" value="0.008302512" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i385]" time="0.356"><properties><property name="score" value="0.002146535" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i386]" time="0.401"><properties><property name="score" value="0.0011620232" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i387]" time="0.333"><properties><property name="score" value="0.001046082" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i388]" time="0.299"><properties><property name="score" value="0.0011521796" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i389]" time="0.261"><properties><property name="score" value="0.0033528593" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i390]" time="0.300"><properties><property name="score" value="0.0007182085" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i391]" time="0.294"><properties><property name="score" value="0.033829883" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i392]" time="0.378"><properties><property name="score" value="0.001226593" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i393]" time="2.606"><properties><property name="score" value="0.0026633611" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i394]" time="0.286"><properties><property name="score" value="0.17362176" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i395]" time="0.285"><properties><property name="score" value="0.020547936" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i396]" time="2.650"><properties><property name="score" value="0.0016309345" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i397]" time="0.330"><properties><property name="score" value="0.005196739" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i398]" time="2.603"><properties><property name="score" value="0.2185456" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i399]" time="0.328"><properties><property name="score" value="0.04511578" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i400]" time="0.280"><properties><property name="score" value="0.014682112" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i401]" time="0.410"><properties><property name="score" value="0.005177566" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i402]" time="0.338"><properties><property name="score" value="0.0009621376" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i403]" time="0.312"><properties><property name="score" value="0.0057970933" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i404]" time="0.316"><properties><property name="score" value="0.00048000526" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i405]" time="0.301"><properties><property name="score" value="0.11845216" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i406]" time="0.370"><properties><property name="score" value="0.003007242" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i407]" time="0.325"><properties><property name="score" value="0.033564925" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i408]" time="0.953"><properties><property name="score" value="0.026201466" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i409]" time="0.273"><properties><property name="score" value="0.0013971673" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i410]" time="0.352"><properties><property name="score" value="0.0022289718" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i411]" time="0.297"><properties><property name="score" value="0.0015773836" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i412]" time="0.326"><properties><property name="score" value="0.008005173" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i413]" time="0.319"><properties><property name="score" value="0.05610308" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i414]" time="0.366"><properties><property name="score" value="0.005099261" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i415]" time="0.320"><properties><property name="score" value="0.0037338908" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i416]" time="0.333"><properties><property name="score" value="0.01656137" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i417]" time="0.353"><properties><property name="score" value="0.003807661" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i418]" time="0.425"><properties><property name="score" value="0.008719521" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i419]" time="0.363"><properties><property name="score" value="0.0016644284" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i420]" time="0.344"><properties><property name="score" value="0.08083007" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i421]" time="0.407"><properties><property name="score" value="0.008194816" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i422]" time="0.294"><properties><property name="score" value="0.0005945075" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i423]" time="0.282"><properties><property name="score" value="0.10429574" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i424]" time="0.354"><properties><property name="score" value="0.011525119" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i425]" time="0.336"><properties><property name="score" value="0.0052420357" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i426]" time="0.340"><properties><property name="score" value="0.00034512393" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i427]" time="0.317"><properties><property name="score" value="0.046320893" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i428]" time="0.292"><properties><property name="score" value="0.005999505" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i429]" time="2.763"><properties><property name="score" value="0.005012456" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i430]" time="0.369"><properties><property name="score" value="0.0005861582" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i431]" time="0.309"><properties><property name="score" value="0.0020375284" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i432]" time="0.295"><properties><property name="score" value="0.0036826197" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i433]" time="2.652"><properties><property name="score" value="0.00047481735" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i434]" time="0.336"><properties><property name="score" value="0.07405431" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i435]" time="0.340"><properties><property name="score" value="0.0039479174" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i436]" time="0.361"><properties><property name="score" value="0.018084675" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i437]" time="0.313"><properties><property name="score" value="0.029083531" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i438]" time="0.328"><properties><property name="score" value="0.0086152665" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i439]" time="0.328"><properties><property name="score" value="1.1955519" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.1955519 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.1955519
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i440]" time="0.299"><properties><property name="score" value="0.018392676" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i441]" time="0.328"><properties><property name="score" value="0.0015703989" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i442]" time="0.339"><properties><property name="score" value="0.011092951" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i443]" time="0.304"><properties><property name="score" value="0.012195287" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i444]" time="0.377"><properties><property name="score" value="0.0044785477" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i445]" time="0.408"><properties><property name="score" value="0.003325169" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i446]" time="0.315"><properties><property name="score" value="1.9555945" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.9555945 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.9555945
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i447]" time="0.355"><properties><property name="score" value="0.00126801" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i448]" time="0.385"><properties><property name="score" value="0.0007936066" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i449]" time="1.346"><properties><property name="score" value="0.010476882" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i450]" time="0.317"><properties><property name="score" value="0.026236463" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i451]" time="0.291"><properties><property name="score" value="0.00043593463" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i452]" time="0.303"><properties><property name="score" value="0.024599906" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i453]" time="0.333"><properties><property name="score" value="0.0075932816" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i454]" time="0.363"><properties><property name="score" value="0.16749603" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i455]" time="0.283"><properties><property name="score" value="0.0010718011" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i456]" time="0.303"><properties><property name="score" value="0.046583384" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i457]" time="0.286"><properties><property name="score" value="0.10974339" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i458]" time="0.293"><properties><property name="score" value="0.007604511" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i459]" time="6.601"><properties><property name="score" value="0.033325486" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i460]" time="0.269"><properties><property name="score" value="1.3495896" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i461]" time="0.260"><properties><property name="score" value="0.03823817" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i462]" time="0.283"><properties><property name="score" value="0.046089683" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i463]" time="0.273"><properties><property name="score" value="0.029989414" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i464]" time="0.301"><properties><property name="score" value="0.08995287" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i465]" time="0.309"><properties><property name="score" value="0.04514471" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i466]" time="0.316"><properties><property name="score" value="0.0024758386" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i467]" time="0.293"><properties><property name="score" value="0.013222377" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i468]" time="0.280"><properties><property name="score" value="0.056186046" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i469]" time="0.325"><properties><property name="score" value="0.023443626" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i470]" time="0.339"><properties><property name="score" value="0.030343678" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i471]" time="0.321"><properties><property name="score" value="0.0023473196" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i472]" time="0.321"><properties><property name="score" value="0.031736385" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i473]" time="2.591"><properties><property name="score" value="0.042255256" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i474]" time="0.313"><properties><property name="score" value="0.0006046459" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i475]" time="0.275"><properties><property name="score" value="0.0031281353" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i476]" time="0.317"><properties><property name="score" value="0.0008220599" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i477]" time="0.304"><properties><property name="score" value="0.01133442" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i478]" time="0.296"><properties><property name="score" value="0.035662115" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i479]" time="0.326"><properties><property name="score" value="1.6924192" /></properties><failure message="AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.6924192 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/news.jsonl is a human-generated sample, misclassified as AI-generated with confidence 1.6924192
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i480]" time="0.325"><properties><property name="score" value="0.05855587" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i481]" time="0.264"><properties><property name="score" value="0.0030181818" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i482]" time="0.291"><properties><property name="score" value="0.016843198" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i483]" time="0.347"><properties><property name="score" value="0.000566058" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i484]" time="0.284"><properties><property name="score" value="0.0047793332" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i485]" time="0.301"><properties><property name="score" value="0.00443568" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i486]" time="0.280"><properties><property name="score" value="0.02373698" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i487]" time="2.701"><properties><property name="score" value="0.0463498" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i488]" time="0.271"><properties><property name="score" value="0.009109576" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i489]" time="0.266"><properties><property name="score" value="0.0090698805" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i490]" time="0.291"><properties><property name="score" value="0.0012997026" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i491]" time="0.299"><properties><property name="score" value="0.0017229391" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i492]" time="0.302"><properties><property name="score" value="0.00043235742" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i493]" time="0.304"><properties><property name="score" value="0.0016322485" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i494]" time="0.315"><properties><property name="score" value="0.00080237177" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i495]" time="0.313"><properties><property name="score" value="0.0026108306" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i496]" time="0.303"><properties><property name="score" value="0.0012961207" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i497]" time="0.313"><properties><property name="score" value="0.026047166" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i498]" time="0.361"><properties><property name="score" value="0.00062957645" /></properties></testcase><testcase classname="test_openai_detect" name="test_humannews_jsonl[i499]" time="0.358"><properties><property name="score" value="0.28460535" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i0]" time="0.329"><properties><property name="score" value="0.6407607" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6407607 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6407607
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i1]" time="0.343"><properties><property name="score" value="2.252231" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i2]" time="0.342"><properties><property name="score" value="0.70354074" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i3]" time="0.598"><properties><property name="score" value="0.04806723" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04806723 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04806723
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i4]" time="0.470"><properties><property name="score" value="0.36321127" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.36321127 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.36321127
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i5]" time="0.571"><properties><property name="score" value="0.009543475" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00954347 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00954347
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i6]" time="0.520"><properties><property name="score" value="0.0215069" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0215069 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0215069
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i7]" time="0.429"><properties><property name="score" value="0.22913657" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i8]" time="0.408"><properties><property name="score" value="0.058983378" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05898338 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05898338
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i9]" time="0.360"><properties><property name="score" value="0.026331069" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i10]" time="0.335"><properties><property name="score" value="0.18719527" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18719527 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18719527
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i11]" time="0.376"><properties><property name="score" value="0.27483445" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.27483445 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.27483445
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i12]" time="0.366"><properties><property name="score" value="0.6861498" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6861498 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6861498
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i13]" time="0.349"><properties><property name="score" value="1.432874" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i14]" time="0.319"><properties><property name="score" value="0.046819586" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i15]" time="0.350"><properties><property name="score" value="0.1492504" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1492504 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1492504
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i16]" time="0.332"><properties><property name="score" value="0.087526836" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.08752684 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.08752684
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i17]" time="0.370"><properties><property name="score" value="0.05095227" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i18]" time="0.331"><properties><property name="score" value="3.1716" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i19]" time="0.409"><properties><property name="score" value="0.39183295" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.39183295 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.39183295
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i20]" time="0.330"><properties><property name="score" value="0.5275232" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5275232 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5275232
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i21]" time="0.369"><properties><property name="score" value="0.07236506" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.07236506 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.07236506
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i22]" time="0.412"><properties><property name="score" value="0.94346935" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.94346935 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.94346935
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i23]" time="0.344"><properties><property name="score" value="0.046145044" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04614504 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04614504
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i24]" time="0.353"><properties><property name="score" value="0.7335567" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7335567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7335567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i25]" time="0.403"><properties><property name="score" value="0.3190322" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3190322 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3190322
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i26]" time="0.377"><properties><property name="score" value="0.011968209" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01196821 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01196821
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i27]" time="0.349"><properties><property name="score" value="0.20980361" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i28]" time="0.344"><properties><property name="score" value="0.056436226" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05643623 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05643623
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i29]" time="0.381"><properties><property name="score" value="0.11400924" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11400924 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11400924
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i30]" time="0.361"><properties><property name="score" value="1.1991324" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1991324 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1991324
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i31]" time="0.323"><properties><property name="score" value="1.6430492" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i32]" time="0.760"><properties><property name="score" value="0.06332622" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06332622 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06332622
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i33]" time="0.302"><properties><property name="score" value="0.22254996" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.22254996 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.22254996
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i34]" time="0.341"><properties><property name="score" value="0.17640354" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i35]" time="0.374"><properties><property name="score" value="0.1170823" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1170823 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1170823
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i36]" time="0.556"><properties><property name="score" value="0.04161354" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04161354 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04161354
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i37]" time="0.302"><properties><property name="score" value="0.031258754" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03125875 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03125875
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i38]" time="0.366"><properties><property name="score" value="0.044318885" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04431889 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04431889
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i39]" time="0.329"><properties><property name="score" value="0.31036216" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i40]" time="0.299"><properties><property name="score" value="0.038410407" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i41]" time="0.384"><properties><property name="score" value="0.66160953" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.66160953 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.66160953
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i42]" time="0.308"><properties><property name="score" value="0.42040336" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42040336 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42040336
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i43]" time="0.317"><properties><property name="score" value="0.10604124" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10604124 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10604124
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i44]" time="0.299"><properties><property name="score" value="0.7222017" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i45]" time="0.367"><properties><property name="score" value="0.31684703" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i46]" time="0.279"><properties><property name="score" value="0.88982177" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i47]" time="0.306"><properties><property name="score" value="1.1110251" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i48]" time="0.351"><properties><property name="score" value="1.6402016" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i49]" time="0.340"><properties><property name="score" value="0.024958072" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02495807 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02495807
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i50]" time="0.322"><properties><property name="score" value="0.017501412" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01750141 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01750141
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i51]" time="0.337"><properties><property name="score" value="0.50627595" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i52]" time="0.418"><properties><property name="score" value="0.93911886" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.93911886 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.93911886
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i53]" time="0.320"><properties><property name="score" value="0.283719" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i54]" time="0.321"><properties><property name="score" value="0.7602704" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i55]" time="0.345"><properties><property name="score" value="0.01013482" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01013482 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01013482
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i56]" time="0.338"><properties><property name="score" value="0.4080996" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i57]" time="0.299"><properties><property name="score" value="0.4683893" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i58]" time="0.409"><properties><property name="score" value="0.004465854" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00446585 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00446585
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i59]" time="0.316"><properties><property name="score" value="0.46649227" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i60]" time="0.315"><properties><property name="score" value="0.067454316" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i61]" time="0.337"><properties><property name="score" value="0.107985094" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10798509 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10798509
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i62]" time="0.333"><properties><property name="score" value="0.2701567" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2701567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2701567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i63]" time="0.292"><properties><property name="score" value="0.44372612" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i64]" time="0.315"><properties><property name="score" value="0.48443353" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.48443353 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.48443353
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i65]" time="0.355"><properties><property name="score" value="0.19928838" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i66]" time="0.320"><properties><property name="score" value="0.13582216" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i67]" time="0.342"><properties><property name="score" value="0.34217876" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.34217876 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.34217876
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i68]" time="0.329"><properties><property name="score" value="0.37483856" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i69]" time="0.317"><properties><property name="score" value="0.57598716" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i70]" time="0.417"><properties><property name="score" value="0.30134" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.30134 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.30134
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i71]" time="0.457"><properties><property name="score" value="0.47882128" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.47882128 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.47882128
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i72]" time="0.315"><properties><property name="score" value="0.40392303" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i73]" time="0.394"><properties><property name="score" value="0.75479776" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.75479776 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.75479776
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i74]" time="0.266"><properties><property name="score" value="0.58697283" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i75]" time="0.318"><properties><property name="score" value="0.29528803" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i76]" time="0.270"><properties><property name="score" value="0.14301161" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14301161 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14301161
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i77]" time="0.283"><properties><property name="score" value="0.40069658" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.40069658 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.40069658
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i78]" time="0.295"><properties><property name="score" value="0.023374189" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i79]" time="0.307"><properties><property name="score" value="0.52707404" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i80]" time="0.310"><properties><property name="score" value="0.08292917" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i81]" time="0.344"><properties><property name="score" value="0.17516829" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i82]" time="0.289"><properties><property name="score" value="0.9588983" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i83]" time="0.278"><properties><property name="score" value="0.94771254" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.94771254 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.94771254
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i84]" time="0.273"><properties><property name="score" value="0.7963533" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7963533 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7963533
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i85]" time="0.263"><properties><property name="score" value="1.3382113" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i86]" time="0.259"><properties><property name="score" value="0.0007593665" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00075937 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00075937
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i87]" time="0.314"><properties><property name="score" value="1.9673021" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.9673021 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.9673021
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i88]" time="0.303"><properties><property name="score" value="0.6517813" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i89]" time="0.293"><properties><property name="score" value="0.29617402" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i90]" time="0.348"><properties><property name="score" value="0.004089692" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00408969 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00408969
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i91]" time="0.586"><properties><property name="score" value="0.068394706" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06839471 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06839471
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i92]" time="0.352"><properties><property name="score" value="0.0019044074" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00190441 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00190441
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i93]" time="0.401"><properties><property name="score" value="0.5234569" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5234569 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5234569
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i94]" time="0.599"><properties><property name="score" value="0.13247465" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i95]" time="0.479"><properties><property name="score" value="0.51072794" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i96]" time="0.370"><properties><property name="score" value="0.45481414" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i97]" time="0.297"><properties><property name="score" value="0.30866838" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.30866838 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.30866838
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i98]" time="0.415"><properties><property name="score" value="0.22518976" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.22518976 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.22518976
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i99]" time="0.534"><properties><property name="score" value="0.32470387" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i100]" time="0.648"><properties><property name="score" value="0.07969304" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i101]" time="0.491"><properties><property name="score" value="0.33163294" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i102]" time="0.638"><properties><property name="score" value="0.6367058" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i103]" time="0.459"><properties><property name="score" value="0.14492393" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i104]" time="0.567"><properties><property name="score" value="0.41377077" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.41377077 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.41377077
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i105]" time="0.476"><properties><property name="score" value="0.04848365" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04848365 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04848365
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i106]" time="0.606"><properties><property name="score" value="0.18554527" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i107]" time="0.473"><properties><property name="score" value="0.82094514" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.82094514 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.82094514
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i108]" time="0.499"><properties><property name="score" value="0.0485277" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0485277 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0485277
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i109]" time="0.442"><properties><property name="score" value="0.019717725" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01971772 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01971772
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i110]" time="0.348"><properties><property name="score" value="0.0037787037" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0037787 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0037787
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i111]" time="0.495"><properties><property name="score" value="0.12120889" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i112]" time="0.509"><properties><property name="score" value="1.6001003" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i113]" time="0.527"><properties><property name="score" value="0.1713397" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1713397 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1713397
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i114]" time="0.546"><properties><property name="score" value="0.48694825" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.48694825 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.48694825
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i115]" time="0.427"><properties><property name="score" value="0.44112507" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i116]" time="0.539"><properties><property name="score" value="0.11898401" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11898401 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11898401
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i117]" time="0.483"><properties><property name="score" value="0.6619872" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i118]" time="0.554"><properties><property name="score" value="0.32076156" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i119]" time="0.577"><properties><property name="score" value="0.63690174" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i120]" time="0.610"><properties><property name="score" value="0.52703846" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.52703846 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.52703846
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i121]" time="0.366"><properties><property name="score" value="2.0857096" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.0857096 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.0857096
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i122]" time="0.330"><properties><property name="score" value="0.8805997" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.8805997 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.8805997
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i123]" time="0.312"><properties><property name="score" value="0.12042996" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12042996 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12042996
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i124]" time="0.275"><properties><property name="score" value="0.034914125" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i125]" time="0.333"><properties><property name="score" value="0.2115993" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i126]" time="0.394"><properties><property name="score" value="1.26379" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.26379 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.26379
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i127]" time="0.353"><properties><property name="score" value="0.43398547" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.43398547 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.43398547
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i128]" time="0.322"><properties><property name="score" value="0.19187883" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.19187883 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.19187883
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i129]" time="0.306"><properties><property name="score" value="0.053941" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.053941 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.053941
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i130]" time="0.312"><properties><property name="score" value="0.19974877" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.19974877 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.19974877
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i131]" time="0.333"><properties><property name="score" value="0.040925667" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04092567 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04092567
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i132]" time="0.375"><properties><property name="score" value="0.21230373" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i133]" time="0.368"><properties><property name="score" value="0.077414475" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i134]" time="0.289"><properties><property name="score" value="0.58245814" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i135]" time="2.633"><properties><property name="score" value="0.2256768" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i136]" time="0.463"><properties><property name="score" value="1.1198025" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i137]" time="0.595"><properties><property name="score" value="0.011027319" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01102732 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01102732
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i138]" time="0.535"><properties><property name="score" value="0.18857987" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i139]" time="0.428"><properties><property name="score" value="0.028499646" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02849965 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02849965
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i140]" time="0.374"><properties><property name="score" value="0.11038948" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i141]" time="0.332"><properties><property name="score" value="0.7572069" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i142]" time="0.325"><properties><property name="score" value="0.45753458" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i143]" time="0.300"><properties><property name="score" value="0.017794427" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01779443 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01779443
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i144]" time="0.298"><properties><property name="score" value="0.018680064" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01868006 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01868006
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i145]" time="0.371"><properties><property name="score" value="0.011998611" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01199861 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01199861
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i146]" time="0.317"><properties><property name="score" value="0.119983226" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11998323 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11998323
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i147]" time="0.355"><properties><property name="score" value="0.19387114" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i148]" time="0.342"><properties><property name="score" value="0.028660156" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02866016 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02866016
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i149]" time="0.309"><properties><property name="score" value="0.46835825" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.46835825 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.46835825
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i150]" time="0.293"><properties><property name="score" value="0.28322327" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.28322327 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.28322327
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i151]" time="0.322"><properties><property name="score" value="0.85113114" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.85113114 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.85113114
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i152]" time="0.307"><properties><property name="score" value="0.59243774" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i153]" time="0.383"><properties><property name="score" value="0.14781326" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14781326 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14781326
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i154]" time="0.317"><properties><property name="score" value="0.4273816" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i155]" time="0.305"><properties><property name="score" value="0.018931387" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01893139 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01893139
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i156]" time="0.304"><properties><property name="score" value="0.18543333" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18543333 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18543333
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i157]" time="0.303"><properties><property name="score" value="0.8365834" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i158]" time="0.260"><properties><property name="score" value="0.091254674" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i159]" time="0.353"><properties><property name="score" value="0.041725334" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i160]" time="0.284"><properties><property name="score" value="0.040984593" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04098459 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04098459
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i161]" time="0.254"><properties><property name="score" value="1.0507313" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i162]" time="0.273"><properties><property name="score" value="0.42738864" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42738864 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42738864
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i163]" time="0.282"><properties><property name="score" value="0.42349657" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i164]" time="0.268"><properties><property name="score" value="0.19961005" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i165]" time="0.334"><properties><property name="score" value="0.3256301" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i166]" time="0.304"><properties><property name="score" value="0.43747175" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.43747175 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.43747175
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i167]" time="0.255"><properties><property name="score" value="0.17103349" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.17103349 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.17103349
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i168]" time="0.296"><properties><property name="score" value="0.12027049" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12027049 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12027049
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i169]" time="0.288"><properties><property name="score" value="0.693679" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.693679 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.693679
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i170]" time="0.325"><properties><property name="score" value="0.26789975" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.26789975 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.26789975
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i171]" time="0.001"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i172]" time="0.293"><properties><property name="score" value="0.108709574" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10870957 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10870957
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i173]" time="0.375"><properties><property name="score" value="0.14799024" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14799024 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14799024
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i174]" time="0.464"><properties><property name="score" value="0.06890581" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06890581 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06890581
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i175]" time="0.272"><properties><property name="score" value="0.08268895" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.08268895 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.08268895
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i176]" time="0.254"><properties><property name="score" value="0.023321599" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i177]" time="0.287"><properties><property name="score" value="0.14460036" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14460036 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14460036
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i178]" time="0.266"><properties><property name="score" value="0.1808803" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i179]" time="0.309"><properties><property name="score" value="0.255113" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i180]" time="0.288"><properties><property name="score" value="0.70164883" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.70164883 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.70164883
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i181]" time="0.278"><properties><property name="score" value="0.09100141" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.09100141 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.09100141
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i182]" time="0.285"><properties><property name="score" value="0.03048592" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i183]" time="0.322"><properties><property name="score" value="0.06829763" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06829763 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06829763
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i184]" time="0.320"><properties><property name="score" value="0.18002036" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i185]" time="0.289"><properties><property name="score" value="1.1761931" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1761931 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1761931
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i186]" time="0.281"><properties><property name="score" value="0.40178946" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i187]" time="0.453"><properties><property name="score" value="0.35727766" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i188]" time="0.386"><properties><property name="score" value="1.3313338" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.3313338 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.3313338
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i189]" time="0.379"><properties><property name="score" value="0.47103667" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i190]" time="0.279"><properties><property name="score" value="1.0138322" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0138322 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0138322
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i191]" time="0.329"><properties><property name="score" value="0.57509494" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.57509494 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.57509494
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i192]" time="0.298"><properties><property name="score" value="0.005230532" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i193]" time="0.400"><properties><property name="score" value="0.1484976" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i194]" time="0.603"><properties><property name="score" value="0.8272904" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.8272904 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.8272904
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i195]" time="0.394"><properties><property name="score" value="0.020059068" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i196]" time="0.398"><properties><property name="score" value="0.06567025" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06567025 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06567025
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i197]" time="0.417"><properties><property name="score" value="0.04442412" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i198]" time="0.378"><properties><property name="score" value="0.020458017" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i199]" time="0.373"><properties><property name="score" value="0.07381781" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i200]" time="0.407"><properties><property name="score" value="0.1472499" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i201]" time="0.407"><properties><property name="score" value="0.05989862" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i202]" time="0.344"><properties><property name="score" value="0.29437664" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.29437664 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.29437664
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i203]" time="0.393"><properties><property name="score" value="0.23333913" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23333913 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23333913
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i204]" time="0.289"><properties><property name="score" value="0.38431603" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38431603 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38431603
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i205]" time="0.435"><properties><property name="score" value="1.1188729" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1188729 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1188729
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i206]" time="0.437"><properties><property name="score" value="0.17306396" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.17306396 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.17306396
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i207]" time="0.359"><properties><property name="score" value="0.36827666" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.36827666 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.36827666
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i208]" time="0.386"><properties><property name="score" value="0.12481064" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12481064 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12481064
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i209]" time="0.359"><properties><property name="score" value="0.051779404" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0517794 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0517794
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i210]" time="0.376"><properties><property name="score" value="1.3102386" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i211]" time="0.357"><properties><property name="score" value="0.24644247" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i212]" time="0.300"><properties><property name="score" value="0.6231057" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6231057 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6231057
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i213]" time="0.348"><properties><property name="score" value="0.0664111" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i214]" time="0.293"><properties><property name="score" value="0.5588337" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5588337 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5588337
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i215]" time="0.302"><properties><property name="score" value="0.13616736" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i216]" time="0.343"><properties><property name="score" value="1.8604364" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.8604364 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.8604364
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i217]" time="0.421"><properties><property name="score" value="1.3211844" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.3211844 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.3211844
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i218]" time="0.305"><properties><property name="score" value="0.38815987" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i219]" time="0.354"><properties><property name="score" value="0.3363622" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i220]" time="0.429"><properties><property name="score" value="0.11121977" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11121977 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11121977
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i221]" time="0.344"><properties><property name="score" value="0.45268035" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.45268035 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.45268035
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i222]" time="0.362"><properties><property name="score" value="0.451567" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i223]" time="0.453"><properties><property name="score" value="0.1609982" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i224]" time="0.354"><properties><property name="score" value="0.25019556" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i225]" time="0.329"><properties><property name="score" value="0.20228189" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.20228189 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.20228189
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i226]" time="0.364"><properties><property name="score" value="0.07718768" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i227]" time="0.383"><properties><property name="score" value="0.049040336" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04904034 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04904034
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i228]" time="0.341"><properties><property name="score" value="0.12098606" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12098606 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12098606
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i229]" time="0.340"><properties><property name="score" value="0.6722528" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i230]" time="0.002"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i231]" time="0.365"><properties><property name="score" value="0.45889318" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.45889318 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.45889318
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i232]" time="0.379"><properties><property name="score" value="0.29446366" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i233]" time="0.371"><properties><property name="score" value="0.09881051" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i234]" time="0.457"><properties><property name="score" value="0.77598804" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.77598804 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.77598804
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i235]" time="0.483"><properties><property name="score" value="0.07819231" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i236]" time="0.434"><properties><property name="score" value="0.41841865" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.41841865 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.41841865
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i237]" time="0.484"><properties><property name="score" value="0.3978388" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i238]" time="0.489"><properties><property name="score" value="1.1464635" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i239]" time="0.718"><properties><property name="score" value="0.1750534" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1750534 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1750534
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i240]" time="0.489"><properties><property name="score" value="0.20753025" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.20753025 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.20753025
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i241]" time="0.416"><properties><property name="score" value="0.82523584" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i242]" time="0.355"><properties><property name="score" value="0.32689297" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.32689297 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.32689297
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i243]" time="0.354"><properties><property name="score" value="0.30944684" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i244]" time="0.409"><properties><property name="score" value="0.64639217" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.64639217 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.64639217
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i245]" time="0.542"><properties><property name="score" value="0.36523208" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.36523208 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.36523208
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i246]" time="0.371"><properties><property name="score" value="0.23773101" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i247]" time="0.494"><properties><property name="score" value="0.59794974" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i248]" time="0.479"><properties><property name="score" value="0.299036" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.299036 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.299036
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i249]" time="0.416"><properties><property name="score" value="0.06886744" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i250]" time="0.422"><properties><property name="score" value="0.34672382" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i251]" time="0.445"><properties><property name="score" value="0.42708302" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42708302 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42708302
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i252]" time="0.962"><properties><property name="score" value="0.105837606" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i253]" time="0.379"><properties><property name="score" value="1.2395036" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i254]" time="0.425"><properties><property name="score" value="0.73388207" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.73388207 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.73388207
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i255]" time="0.469"><properties><property name="score" value="0.008495213" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00849521 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00849521
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i256]" time="0.356"><properties><property name="score" value="2.2223678" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i257]" time="0.385"><properties><property name="score" value="0.47730854" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i258]" time="0.407"><properties><property name="score" value="2.3907366" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.3907366 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.3907366
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i259]" time="0.405"><properties><property name="score" value="0.49764267" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i260]" time="0.349"><properties><property name="score" value="0.037110038" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03711004 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03711004
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i261]" time="0.618"><properties><property name="score" value="0.06108223" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06108223 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06108223
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i262]" time="0.358"><properties><property name="score" value="2.0731356" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i263]" time="0.323"><properties><property name="score" value="0.1798464" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1798464 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1798464
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i264]" time="0.309"><properties><property name="score" value="0.67513967" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i265]" time="0.296"><properties><property name="score" value="0.11624664" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i266]" time="0.363"><properties><property name="score" value="0.08474309" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i267]" time="0.311"><properties><property name="score" value="0.06493274" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06493274 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06493274
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i268]" time="0.384"><properties><property name="score" value="1.0855558" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0855558 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0855558
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i269]" time="0.331"><properties><property name="score" value="0.30645943" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i270]" time="0.378"><properties><property name="score" value="0.2336017" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2336017 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2336017
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i271]" time="0.275"><properties><property name="score" value="0.5118978" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5118978 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5118978
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i272]" time="0.277"><properties><property name="score" value="0.10837906" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i273]" time="0.304"><properties><property name="score" value="1.709295" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i274]" time="0.300"><properties><property name="score" value="2.046391" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.046391 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.046391
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i275]" time="0.296"><properties><property name="score" value="0.034765016" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03476502 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03476502
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i276]" time="0.362"><properties><property name="score" value="0.034768224" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03476822 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03476822
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i277]" time="0.357"><properties><property name="score" value="2.7765274" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i278]" time="0.307"><properties><property name="score" value="0.011327909" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01132791 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01132791
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i279]" time="0.329"><properties><property name="score" value="0.29834765" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i280]" time="0.324"><properties><property name="score" value="0.1041848" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1041848 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.1041848
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i281]" time="0.310"><properties><property name="score" value="0.068795405" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i282]" time="0.276"><properties><property name="score" value="0.10869569" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10869569 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.10869569
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i283]" time="0.334"><properties><property name="score" value="0.060997333" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i284]" time="0.360"><properties><property name="score" value="1.0367773" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i285]" time="0.374"><properties><property name="score" value="0.33325547" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.33325547 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.33325547
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i286]" time="0.283"><properties><property name="score" value="0.15251665" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.15251665 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.15251665
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i287]" time="1.326"><properties><property name="score" value="0.9215191" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.9215191 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.9215191
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i288]" time="0.319"><properties><property name="score" value="0.14083323" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i289]" time="0.336"><properties><property name="score" value="0.3316401" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3316401 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3316401
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i290]" time="0.265"><properties><property name="score" value="0.2701919" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i291]" time="0.277"><properties><property name="score" value="0.0072725597" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00727256 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00727256
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i292]" time="0.307"><properties><property name="score" value="0.0134087205" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01340872 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01340872
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i293]" time="0.293"><properties><property name="score" value="0.044187363" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04418736 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.04418736
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i294]" time="0.345"><properties><property name="score" value="0.072872214" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i295]" time="0.331"><properties><property name="score" value="0.86823183" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.86823183 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.86823183
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i296]" time="0.445"><properties><property name="score" value="0.28435144" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.28435144 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.28435144
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i297]" time="0.364"><properties><property name="score" value="0.55796504" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i298]" time="0.380"><properties><property name="score" value="0.07214312" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.07214312 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.07214312
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i299]" time="0.339"><properties><property name="score" value="0.0032413863" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00324139 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00324139
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i300]" time="0.328"><properties><property name="score" value="0.20819671" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i301]" time="0.347"><properties><property name="score" value="0.8456075" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.8456075 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.8456075
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i302]" time="0.354"><properties><property name="score" value="0.8383304" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i303]" time="0.307"><properties><property name="score" value="0.38985604" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38985604 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38985604
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i304]" time="0.341"><properties><property name="score" value="0.05864783" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05864783 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05864783
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i305]" time="0.346"><properties><property name="score" value="0.7811936" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7811936 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7811936
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i306]" time="0.399"><properties><property name="score" value="0.24921392" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i307]" time="0.352"><properties><property name="score" value="0.05978041" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05978041 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05978041
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i308]" time="0.274"><properties><property name="score" value="0.22774199" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.22774199 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.22774199
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i309]" time="0.337"><properties><property name="score" value="1.5414953" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.5414953 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.5414953
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i310]" time="0.275"><properties><property name="score" value="0.13911107" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.13911107 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.13911107
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i311]" time="0.316"><properties><property name="score" value="0.86865187" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i312]" time="0.320"><properties><property name="score" value="0.65313935" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.65313935 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.65313935
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i313]" time="0.347"><properties><property name="score" value="0.3008249" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3008249 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3008249
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i314]" time="0.296"><properties><property name="score" value="1.1467302" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1467302 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1467302
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i315]" time="0.293"><properties><property name="score" value="0.40634924" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i316]" time="0.317"><properties><property name="score" value="1.1613995" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1613995 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.1613995
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i317]" time="0.324"><properties><property name="score" value="1.143368" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i318]" time="0.288"><properties><property name="score" value="0.41344175" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.41344175 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.41344175
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i319]" time="0.326"><properties><property name="score" value="0.21197802" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i320]" time="0.441"><properties><property name="score" value="0.030515417" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03051542 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03051542
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i321]" time="0.302"><properties><property name="score" value="0.0038844903" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00388449 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00388449
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i322]" time="0.357"><properties><property name="score" value="0.0809345" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i323]" time="0.400"><properties><property name="score" value="0.028321013" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02832101 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02832101
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i324]" time="0.345"><properties><property name="score" value="0.92241544" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.92241544 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.92241544
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i325]" time="0.365"><properties><property name="score" value="0.32893997" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.32893997 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.32893997
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i326]" time="0.343"><properties><property name="score" value="0.5611466" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5611466 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.5611466
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i327]" time="0.324"><properties><property name="score" value="0.6044809" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6044809 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6044809
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i328]" time="0.300"><properties><property name="score" value="0.08040036" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.08040036 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.08040036
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i329]" time="0.294"><properties><property name="score" value="0.08034946" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i330]" time="0.304"><properties><property name="score" value="0.42302546" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42302546 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.42302546
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i331]" time="0.323"><properties><property name="score" value="0.14864674" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14864674 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14864674
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i332]" time="0.350"><properties><property name="score" value="0.5342399" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i333]" time="0.286"><properties><property name="score" value="0.059173517" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05917352 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05917352
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i334]" time="0.308"><properties><property name="score" value="0.018851453" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01885145 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01885145
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i335]" time="0.285"><properties><property name="score" value="0.0051016584" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00510166 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00510166
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i336]" time="0.280"><properties><property name="score" value="0.90562356" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.90562356 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.90562356
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i337]" time="0.303"><properties><property name="score" value="2.4516988" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.4516988 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.4516988
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i338]" time="0.270"><properties><property name="score" value="0.009276808" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00927681 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00927681
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i339]" time="0.302"><properties><property name="score" value="0.053754933" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05375493 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.05375493
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i340]" time="0.402"><properties><property name="score" value="0.38059685" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38059685 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38059685
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i341]" time="0.294"><properties><property name="score" value="0.12204998" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12204998 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12204998
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i342]" time="0.392"><properties><property name="score" value="0.05032387" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i343]" time="0.288"><properties><property name="score" value="0.03774126" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03774126 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03774126
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i344]" time="0.287"><properties><property name="score" value="1.4612356" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i345]" time="0.306"><properties><property name="score" value="0.06264355" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i346]" time="0.325"><properties><property name="score" value="1.5501045" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.5501045 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.5501045
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i347]" time="0.297"><properties><property name="score" value="0.94643486" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.94643486 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.94643486
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i348]" time="0.269"><properties><property name="score" value="0.92790896" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i349]" time="0.294"><properties><property name="score" value="0.09743575" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i350]" time="0.322"><properties><property name="score" value="0.34427524" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i351]" time="0.287"><properties><property name="score" value="0.020776482" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02077648 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02077648
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i352]" time="0.265"><properties><property name="score" value="0.060593028" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06059303 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06059303
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i353]" time="0.265"><properties><property name="score" value="0.7922862" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7922862 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7922862
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i354]" time="0.323"><properties><property name="score" value="0.13183309" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i355]" time="1.639"><properties><property name="score" value="0.8241898" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i356]" time="0.303"><properties><property name="score" value="1.4218103" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4218103 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4218103
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i357]" time="0.286"><properties><property name="score" value="0.48632076" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i358]" time="0.308"><properties><property name="score" value="0.29403043" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i359]" time="0.287"><properties><property name="score" value="0.10221989" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i360]" time="0.285"><properties><property name="score" value="0.0046080016" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i361]" time="0.254"><properties><property name="score" value="0.31663722" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i362]" time="0.303"><properties><property name="score" value="0.069085844" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06908584 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06908584
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i363]" time="0.306"><properties><property name="score" value="0.046301413" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i364]" time="0.299"><properties><property name="score" value="0.34786463" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.34786463 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.34786463
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i365]" time="0.301"><properties><property name="score" value="0.05705022" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i366]" time="0.331"><properties><property name="score" value="1.5151299" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i367]" time="0.303"><properties><property name="score" value="0.28458053" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.28458053 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.28458053
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i368]" time="0.356"><properties><property name="score" value="0.38445747" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38445747 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.38445747
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i369]" time="0.359"><properties><property name="score" value="0.012782531" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01278253 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.01278253
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i370]" time="0.399"><properties><property name="score" value="0.33450758" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i371]" time="0.353"><properties><property name="score" value="0.03989325" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03989325 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03989325
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i372]" time="0.341"><properties><property name="score" value="0.29001176" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.29001176 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.29001176
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i373]" time="0.365"><properties><property name="score" value="1.4091475" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4091475 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4091475
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i374]" time="0.412"><properties><property name="score" value="0.0017899344" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00178993 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00178993
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i375]" time="0.478"><properties><property name="score" value="1.0207137" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0207137 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0207137
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i376]" time="0.316"><properties><property name="score" value="0.14906538" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i377]" time="0.349"><properties><property name="score" value="0.17232671" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i378]" time="0.305"><properties><property name="score" value="0.033145126" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03314513 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03314513
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i379]" time="0.287"><properties><property name="score" value="0.02289547" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02289547 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02289547
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i380]" time="0.321"><properties><property name="score" value="0.34598073" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.34598073 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.34598073
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i381]" time="0.303"><properties><property name="score" value="1.5031929" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.5031929 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.5031929
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i382]" time="0.303"><properties><property name="score" value="1.2601113" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.2601113 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.2601113
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i383]" time="0.336"><properties><property name="score" value="0.3943106" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i384]" time="0.311"><properties><property name="score" value="0.37863094" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i385]" time="0.383"><properties><property name="score" value="0.09517466" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.09517466 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.09517466
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i386]" time="0.309"><properties><property name="score" value="0.16140674" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.16140674 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.16140674
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i387]" time="0.300"><properties><property name="score" value="0.009356281" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00935628 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00935628
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i388]" time="0.322"><properties><property name="score" value="0.18153158" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18153158 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18153158
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i389]" time="0.315"><properties><property name="score" value="0.12085961" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i390]" time="0.336"><properties><property name="score" value="0.008114411" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00811441 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00811441
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i391]" time="0.302"><properties><property name="score" value="0.031287473" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i392]" time="0.270"><properties><property name="score" value="1.0698314" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i393]" time="0.278"><properties><property name="score" value="1.4523364" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4523364 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4523364
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i394]" time="0.361"><properties><property name="score" value="0.89960647" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.89960647 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.89960647
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i395]" time="0.302"><properties><property name="score" value="0.7494364" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7494364 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.7494364
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i396]" time="0.386"><properties><property name="score" value="0.106240675" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i397]" time="0.290"><properties><property name="score" value="0.030340359" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03034036 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03034036
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i398]" time="0.334"><properties><property name="score" value="0.05974276" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i399]" time="0.291"><properties><property name="score" value="0.07908776" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i400]" time="0.279"><properties><property name="score" value="0.4081706" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i401]" time="0.295"><properties><property name="score" value="0.05737071" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i402]" time="0.290"><properties><property name="score" value="0.06288282" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06288282 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06288282
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i403]" time="0.280"><properties><property name="score" value="0.3579597" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i404]" time="0.286"><properties><property name="score" value="2.0449033" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i405]" time="0.331"><properties><property name="score" value="0.3962851" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3962851 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.3962851
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i406]" time="0.324"><properties><property name="score" value="0.2883421" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2883421 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2883421
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i407]" time="0.294"><properties><property name="score" value="1.673852" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.673852 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.673852
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i408]" time="0.441"><properties><property name="score" value="0.08558138" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i409]" time="0.409"><properties><property name="score" value="0.082990505" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i410]" time="0.409"><properties><property name="score" value="0.023551572" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02355157 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02355157
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i411]" time="1.125"><properties><property name="score" value="0.14480728" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14480728 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14480728
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i412]" time="0.340"><properties><property name="score" value="1.1434847" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i413]" time="0.410"><properties><property name="score" value="0.0076851146" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i414]" time="0.396"><properties><property name="score" value="0.23087311" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23087311 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23087311
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i415]" time="0.618"><properties><property name="score" value="0.35069916" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.35069916 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.35069916
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i416]" time="0.409"><properties><property name="score" value="0.2196496" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2196496 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.2196496
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i417]" time="0.416"><properties><property name="score" value="0.49172097" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i418]" time="0.395"><properties><property name="score" value="2.021491" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i419]" time="0.324"><properties><property name="score" value="0.11469808" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11469808 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11469808
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i420]" time="0.353"><properties><property name="score" value="0.38646165" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i421]" time="0.318"><properties><property name="score" value="0.031109083" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03110908 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03110908
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i422]" time="0.646"><properties><property name="score" value="0.32529297" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.32529297 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.32529297
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i423]" time="0.516"><properties><property name="score" value="0.4702845" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i424]" time="0.387"><properties><property name="score" value="0.8134704" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i425]" time="0.305"><properties><property name="score" value="0.18297803" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i426]" time="0.313"><properties><property name="score" value="0.0076597664" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00765977 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00765977
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i427]" time="0.338"><properties><property name="score" value="0.13444805" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.13444805 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.13444805
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i428]" time="0.420"><properties><property name="score" value="0.0030562095" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00305621 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00305621
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i429]" time="0.380"><properties><property name="score" value="0.023166338" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02316634 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02316634
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i430]" time="0.478"><properties><property name="score" value="1.4596404" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4596404 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.4596404
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i431]" time="0.514"><properties><property name="score" value="0.30509132" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.30509132 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.30509132
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i432]" time="0.405"><properties><property name="score" value="2.0191407" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i433]" time="0.400"><properties><property name="score" value="0.009699642" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00969964 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00969964
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i434]" time="0.362"><properties><property name="score" value="1.5809433" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i435]" time="0.372"><properties><property name="score" value="0.5921838" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i436]" time="0.351"><properties><property name="score" value="0.06513496" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06513496 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06513496
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i437]" time="0.333"><properties><property name="score" value="0.6179016" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6179016 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.6179016
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i438]" time="0.341"><properties><property name="score" value="0.090558365" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.09055837 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.09055837
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i439]" time="0.363"><properties><property name="score" value="0.072188154" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i440]" time="0.313"><properties><property name="score" value="0.46579912" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i441]" time="0.351"><properties><property name="score" value="0.039801035" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03980103 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.03980103
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i442]" time="0.333"><properties><property name="score" value="0.31999168" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.31999168 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.31999168
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i443]" time="0.300"><properties><property name="score" value="1.9417253" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i444]" time="0.330"><properties><property name="score" value="0.028186005" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02818601 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02818601
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i445]" time="0.339"><properties><property name="score" value="0.028688185" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02868819 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02868819
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i446]" time="0.286"><properties><property name="score" value="1.0727242" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0727242 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0727242
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i447]" time="0.412"><properties><property name="score" value="0.11533469" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11533469 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.11533469
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i448]" time="0.356"><properties><property name="score" value="0.026607033" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02660703 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02660703
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i449]" time="0.443"><properties><property name="score" value="0.5962603" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i450]" time="0.370"><properties><property name="score" value="0.004722619" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00472262 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00472262
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i451]" time="0.344"><properties><property name="score" value="0.06427615" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06427615 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06427615
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i452]" time="0.338"><properties><property name="score" value="0.022433072" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02243307 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02243307
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i453]" time="0.368"><properties><property name="score" value="0.078898504" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i454]" time="0.380"><properties><property name="score" value="0.14730854" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14730854 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.14730854
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i455]" time="0.333"><properties><property name="score" value="0.86117494" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i456]" time="0.354"><properties><property name="score" value="0.156949" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i457]" time="0.355"><properties><property name="score" value="0.9318663" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.9318663 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.9318663
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i458]" time="0.319"><properties><property name="score" value="2.3278077" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.3278077 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.3278077
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i459]" time="0.822"><properties><property name="score" value="0.032870498" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i460]" time="0.338"><properties><property name="score" value="0.058067337" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i461]" time="0.488"><properties><property name="score" value="0.0030473005" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0030473 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0030473
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i462]" time="0.371"><properties><property name="score" value="0.1341582" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i463]" time="0.436"><properties><property name="score" value="0.4332267" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i464]" time="0.373"><properties><property name="score" value="0.5140538" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i465]" time="0.424"><properties><property name="score" value="0.107185446" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i466]" time="0.360"><properties><property name="score" value="1.0415972" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i467]" time="0.437"><properties><property name="score" value="0.16817604" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.16817604 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.16817604
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i468]" time="0.355"><properties><property name="score" value="0.025546066" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02554607 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02554607
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i469]" time="0.387"><properties><property name="score" value="0.5109151" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i470]" time="0.410"><properties><property name="score" value="0.6907727" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i471]" time="0.435"><properties><property name="score" value="0.03978485" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i472]" time="0.378"><properties><property name="score" value="0.18787675" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i473]" time="0.383"><properties><property name="score" value="1.0895915" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0895915 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 1.0895915
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i474]" time="0.355"><properties><property name="score" value="0.06299415" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06299415 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06299415
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i475]" time="0.441"><properties><property name="score" value="0.44606584" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i476]" time="0.408"><properties><property name="score" value="0.06491163" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06491163 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.06491163
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i477]" time="0.409"><properties><property name="score" value="1.0153602" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i478]" time="0.381"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i479]" time="0.423"><properties><property name="score" value="0.0072540673" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i480]" time="0.461"><properties><property name="score" value="0.23791435" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i481]" time="0.465"><properties><property name="score" value="0.12901837" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12901837 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.12901837
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i482]" time="0.492"><properties><property name="score" value="2.4050999" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.4050999 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 2.4050999
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i483]" time="0.325"><properties><property name="score" value="0.023271935" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02327194 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02327194
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i484]" time="0.340"><properties><property name="score" value="0.18138085" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18138085 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.18138085
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i485]" time="0.397"><properties><property name="score" value="0.23435631" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23435631 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23435631
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i486]" time="0.355"><properties><property name="score" value="1.4996194" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i487]" time="0.346"><properties><property name="score" value="0.23753817" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23753817 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.23753817
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i488]" time="0.437"><properties><property name="score" value="0.0023489322" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00234893 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.00234893
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i489]" time="0.333"><properties><property name="score" value="0.4351846" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i490]" time="0.334"><properties><property name="score" value="0.33423346" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.33423346 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.33423346
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i491]" time="0.326"><properties><property name="score" value="0.026254332" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02625433 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.02625433
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i492]" time="0.338"><properties><property name="score" value="0.16175927" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.16175927 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.16175927
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i493]" time="0.371"><properties><property name="score" value="0.60876274" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.60876274 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.60876274
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i494]" time="0.343"><properties><property name="score" value="0.13631456" /></properties><failure message="AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.13631456 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/news.jsonl is a AI-generated sample, misclassified as human-generated with confidence 0.13631456
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i495]" time="0.416"><properties><property name="score" value="0.8835742" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i496]" time="0.358"><properties><property name="score" value="0.893191" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i497]" time="0.397"><properties><property name="score" value="0.56139165" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i498]" time="0.342"><properties><property name="score" value="0.72114515" /></properties></testcase><testcase classname="test_openai_detect" name="test_chatgptnews_jsonl[i499]" time="0.379"><properties><property name="score" value="0.33539253" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i0]" time="0.336"><properties><property name="score" value="2.2914467" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i1]" time="0.353"><properties><property name="score" value="1.0375583" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600034 [1255] (title: Secrecy Anti-ja) is a human-generated sample, misclassified as AI-generated with confidence 1.0375583 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600034 [1255] (title: Secrecy Anti-ja) is a human-generated sample, misclassified as AI-generated with confidence 1.0375583
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i2]" time="0.389"><properties><property name="score" value="0.976947" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600036 [1316] (title: Pedestrian Dete) is a human-generated sample, misclassified as AI-generated with confidence 0.976947 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600036 [1316] (title: Pedestrian Dete) is a human-generated sample, misclassified as AI-generated with confidence 0.976947
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i3]" time="0.387"><properties><property name="score" value="0.04848434" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i4]" time="0.357"><properties><property name="score" value="1.2263666" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i5]" time="0.425"><properties><property name="score" value="0.94755894" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600055 [1394] (title: An Effective Se) is a human-generated sample, misclassified as AI-generated with confidence 0.94755894 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600055 [1394] (title: An Effective Se) is a human-generated sample, misclassified as AI-generated with confidence 0.94755894
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i6]" time="0.382"><properties><property name="score" value="0.2807031" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i7]" time="0.361"><properties><property name="score" value="0.9287521" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600072 [1639] (title: Analysis of Com) is a human-generated sample, misclassified as AI-generated with confidence 0.9287521 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600072 [1639] (title: Analysis of Com) is a human-generated sample, misclassified as AI-generated with confidence 0.9287521
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i8]" time="0.443"><properties><property name="score" value="1.281849" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i9]" time="0.337"><properties><property name="score" value="0.3434144" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i10]" time="0.349"><properties><property name="score" value="0.6995487" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600082 [1085] (title: Matching Game B) is a human-generated sample, misclassified as AI-generated with confidence 0.6995487 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600082 [1085] (title: Matching Game B) is a human-generated sample, misclassified as AI-generated with confidence 0.6995487
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i11]" time="0.426"><properties><property name="score" value="0.49886432" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i12]" time="0.474"><properties><property name="score" value="0.45675102" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i13]" time="0.378"><properties><property name="score" value="0.3357315" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600094 [1397] (title: NLOS Detection ) is a human-generated sample, misclassified as AI-generated with confidence 0.3357315 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600094 [1397] (title: NLOS Detection ) is a human-generated sample, misclassified as AI-generated with confidence 0.3357315
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i14]" time="0.403"><properties><property name="score" value="0.29104388" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i15]" time="0.368"><properties><property name="score" value="0.0882808" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600099 [1118] (title: Ranking-based C) is a human-generated sample, misclassified as AI-generated with confidence 0.0882808 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600099 [1118] (title: Ranking-based C) is a human-generated sample, misclassified as AI-generated with confidence 0.0882808
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i16]" time="0.405"><properties><property name="score" value="0.67782056" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i17]" time="0.377"><properties><property name="score" value="0.3128622" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600112 [1118] (title: Co-Prime Sampli) is a human-generated sample, misclassified as AI-generated with confidence 0.3128622 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600112 [1118] (title: Co-Prime Sampli) is a human-generated sample, misclassified as AI-generated with confidence 0.3128622
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i18]" time="0.339"><properties><property name="score" value="0.0766509" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i19]" time="0.883"><properties><property name="score" value="0.07420631" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i20]" time="0.323"><properties><property name="score" value="0.022332437" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i21]" time="0.719"><properties><property name="score" value="1.2746738" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i22]" time="0.406"><properties><property name="score" value="0.64155304" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i23]" time="0.354"><properties><property name="score" value="0.052599683" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i24]" time="0.317"><properties><property name="score" value="0.7861435" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i25]" time="0.294"><properties><property name="score" value="2.3174818" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600165 [1193] (title: Adaptive Unequa) is a human-generated sample, misclassified as AI-generated with confidence 2.3174818 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600165 [1193] (title: Adaptive Unequa) is a human-generated sample, misclassified as AI-generated with confidence 2.3174818
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i26]" time="0.288"><properties><property name="score" value="0.72610873" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i27]" time="0.285"><properties><property name="score" value="0.21225286" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600169 [1121] (title: LayerOS: Schedu) is a human-generated sample, misclassified as AI-generated with confidence 0.21225286 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600169 [1121] (title: LayerOS: Schedu) is a human-generated sample, misclassified as AI-generated with confidence 0.21225286
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i28]" time="0.320"><properties><property name="score" value="0.06405936" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i29]" time="0.359"><properties><property name="score" value="1.807162" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i30]" time="0.276"><properties><property name="score" value="0.07060085" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i31]" time="2.643"><properties><property name="score" value="0.45635703" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600201 [1017] (title: Control and Man) is a human-generated sample, misclassified as AI-generated with confidence 0.45635703 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600201 [1017] (title: Control and Man) is a human-generated sample, misclassified as AI-generated with confidence 0.45635703
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i32]" time="0.285"><properties><property name="score" value="2.542298" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600202 [1503] (title: Mridangam Artis) is a human-generated sample, misclassified as AI-generated with confidence 2.542298 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600202 [1503] (title: Mridangam Artis) is a human-generated sample, misclassified as AI-generated with confidence 2.542298
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i33]" time="0.288"><properties><property name="score" value="1.0308679" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600206 [1114] (title: A 3D Placement ) is a human-generated sample, misclassified as AI-generated with confidence 1.0308679 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600206 [1114] (title: A 3D Placement ) is a human-generated sample, misclassified as AI-generated with confidence 1.0308679
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i34]" time="0.316"><properties><property name="score" value="0.64024556" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600210 [1049] (title: A Fingerprint L) is a human-generated sample, misclassified as AI-generated with confidence 0.64024556 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600210 [1049] (title: A Fingerprint L) is a human-generated sample, misclassified as AI-generated with confidence 0.64024556
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i35]" time="0.256"><properties><property name="score" value="0.66405565" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i36]" time="0.269"><properties><property name="score" value="0.6080307" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600231 [1432] (title: Uplink Asynchro) is a human-generated sample, misclassified as AI-generated with confidence 0.6080307 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600231 [1432] (title: Uplink Asynchro) is a human-generated sample, misclassified as AI-generated with confidence 0.6080307
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i37]" time="0.286"><properties><property name="score" value="1.4215157" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600237 [1432] (title: The Adaptive Co) is a human-generated sample, misclassified as AI-generated with confidence 1.4215157 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600237 [1432] (title: The Adaptive Co) is a human-generated sample, misclassified as AI-generated with confidence 1.4215157
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i38]" time="0.294"><properties><property name="score" value="0.5848803" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600243 [1197] (title: A Frequency Ass) is a human-generated sample, misclassified as AI-generated with confidence 0.5848803 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600243 [1197] (title: A Frequency Ass) is a human-generated sample, misclassified as AI-generated with confidence 0.5848803
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i39]" time="0.307"><properties><property name="score" value="0.2997686" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i40]" time="0.359"><properties><property name="score" value="0.22377859" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600252 [1114] (title: Multi-objective) is a human-generated sample, misclassified as AI-generated with confidence 0.22377859 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600252 [1114] (title: Multi-objective) is a human-generated sample, misclassified as AI-generated with confidence 0.22377859
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i41]" time="0.263"><properties><property name="score" value="0.5102597" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600254 [1010] (title: Opportunistic R) is a human-generated sample, misclassified as AI-generated with confidence 0.5102597 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600254 [1010] (title: Opportunistic R) is a human-generated sample, misclassified as AI-generated with confidence 0.5102597
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i42]" time="0.275"><properties><property name="score" value="0.18517199" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600263 [1009] (title: Two-Layer Resou) is a human-generated sample, misclassified as AI-generated with confidence 0.18517199 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600263 [1009] (title: Two-Layer Resou) is a human-generated sample, misclassified as AI-generated with confidence 0.18517199
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i43]" time="0.362"><properties><property name="score" value="0.22440377" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i44]" time="0.434"><properties><property name="score" value="1.3009474" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i45]" time="0.355"><properties><property name="score" value="0.38016453" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i46]" time="0.269"><properties><property name="score" value="1.0536608" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i47]" time="0.278"><properties><property name="score" value="0.53327996" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i48]" time="0.283"><properties><property name="score" value="0.30180192" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i49]" time="0.278"><properties><property name="score" value="0.33713546" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i50]" time="0.297"><properties><property name="score" value="0.37436217" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i51]" time="0.344"><properties><property name="score" value="0.7668246" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i52]" time="0.281"><properties><property name="score" value="0.2551688" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600320 [1497] (title: Multiview Trans) is a human-generated sample, misclassified as AI-generated with confidence 0.2551688 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600320 [1497] (title: Multiview Trans) is a human-generated sample, misclassified as AI-generated with confidence 0.2551688
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i53]" time="0.243"><properties><property name="score" value="1.011547" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i54]" time="0.287"><properties><property name="score" value="0.104266636" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600329 [1382] (title: Texture Feature) is a human-generated sample, misclassified as AI-generated with confidence 0.10426664 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600329 [1382] (title: Texture Feature) is a human-generated sample, misclassified as AI-generated with confidence 0.10426664
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i55]" time="0.248"><properties><property name="score" value="1.1897451" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i56]" time="0.290"><properties><property name="score" value="0.023747662" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i57]" time="0.355"><properties><property name="score" value="0.4995386" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600338 [1456] (title: Jointly Learnin) is a human-generated sample, misclassified as AI-generated with confidence 0.4995386 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600338 [1456] (title: Jointly Learnin) is a human-generated sample, misclassified as AI-generated with confidence 0.4995386
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i58]" time="0.325"><properties><property name="score" value="0.38413298" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i59]" time="0.303"><properties><property name="score" value="0.82706034" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600351 [1202] (title: Machine Learnin) is a human-generated sample, misclassified as AI-generated with confidence 0.82706034 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600351 [1202] (title: Machine Learnin) is a human-generated sample, misclassified as AI-generated with confidence 0.82706034
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i60]" time="0.313"><properties><property name="score" value="1.3309802" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600358 [1200] (title: A Low-Cost High) is a human-generated sample, misclassified as AI-generated with confidence 1.3309802 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600358 [1200] (title: A Low-Cost High) is a human-generated sample, misclassified as AI-generated with confidence 1.3309802
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i61]" time="0.298"><properties><property name="score" value="0.5395134" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600359 [1248] (title: Supervised Spar) is a human-generated sample, misclassified as AI-generated with confidence 0.5395134 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600359 [1248] (title: Supervised Spar) is a human-generated sample, misclassified as AI-generated with confidence 0.5395134
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i62]" time="0.304"><properties><property name="score" value="0.97920305" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600361 [1144] (title: Communication N) is a human-generated sample, misclassified as AI-generated with confidence 0.97920305 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600361 [1144] (title: Communication N) is a human-generated sample, misclassified as AI-generated with confidence 0.97920305
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i63]" time="0.292"><properties><property name="score" value="0.38788378" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i64]" time="0.329"><properties><property name="score" value="0.1894232" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600369 [1149] (title: Local Discrimin) is a human-generated sample, misclassified as AI-generated with confidence 0.1894232 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600369 [1149] (title: Local Discrimin) is a human-generated sample, misclassified as AI-generated with confidence 0.1894232
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i65]" time="0.389"><properties><property name="score" value="0.4818748" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600370 [1482] (title: On Low-Resoluti) is a human-generated sample, misclassified as AI-generated with confidence 0.4818748 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600370 [1482] (title: On Low-Resoluti) is a human-generated sample, misclassified as AI-generated with confidence 0.4818748
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i66]" time="0.946"><properties><property name="score" value="0.6136679" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i67]" time="0.382"><properties><property name="score" value="0.27149233" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i68]" time="0.354"><properties><property name="score" value="0.07683979" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i69]" time="0.358"><properties><property name="score" value="0.38917753" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i70]" time="0.381"><properties><property name="score" value="2.0429614" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600382 [1363] (title: A Deep Reinforc) is a human-generated sample, misclassified as AI-generated with confidence 2.0429614 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600382 [1363] (title: A Deep Reinforc) is a human-generated sample, misclassified as AI-generated with confidence 2.0429614
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i71]" time="0.583"><properties><property name="score" value="0.4319729" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i72]" time="0.390"><properties><property name="score" value="0.16179284" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i73]" time="1.660"><properties><property name="score" value="0.19028988" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i74]" time="0.334"><properties><property name="score" value="0.5833506" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i75]" time="0.717"><properties><property name="score" value="0.15488304" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i76]" time="0.466"><properties><property name="score" value="0.04358892" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i77]" time="0.352"><properties><property name="score" value="0.22468832" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600428 [1340] (title: An Adaptive Rat) is a human-generated sample, misclassified as AI-generated with confidence 0.22468832 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600428 [1340] (title: An Adaptive Rat) is a human-generated sample, misclassified as AI-generated with confidence 0.22468832
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i78]" time="0.425"><properties><property name="score" value="1.2643808" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600431 [1019] (title: Rotation and Pr) is a human-generated sample, misclassified as AI-generated with confidence 1.2643808 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600431 [1019] (title: Rotation and Pr) is a human-generated sample, misclassified as AI-generated with confidence 1.2643808
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i79]" time="0.331"><properties><property name="score" value="0.21326469" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600447 [1036] (title: Tone Correction) is a human-generated sample, misclassified as AI-generated with confidence 0.21326469 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600447 [1036] (title: Tone Correction) is a human-generated sample, misclassified as AI-generated with confidence 0.21326469
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i80]" time="0.375"><properties><property name="score" value="0.10829749" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i81]" time="0.350"><properties><property name="score" value="0.5277755" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i82]" time="0.300"><properties><property name="score" value="0.36012486" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i83]" time="0.319"><properties><property name="score" value="0.85910666" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i84]" time="0.308"><properties><property name="score" value="0.071853474" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i85]" time="0.319"><properties><property name="score" value="0.4239797" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600486 [1312] (title: A Fast Multi-Ma) is a human-generated sample, misclassified as AI-generated with confidence 0.4239797 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600486 [1312] (title: A Fast Multi-Ma) is a human-generated sample, misclassified as AI-generated with confidence 0.4239797
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i86]" time="0.263"><properties><property name="score" value="1.0926619" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600501 [1252] (title: Multi-frame Ima) is a human-generated sample, misclassified as AI-generated with confidence 1.0926619 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600501 [1252] (title: Multi-frame Ima) is a human-generated sample, misclassified as AI-generated with confidence 1.0926619
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i87]" time="0.294"><properties><property name="score" value="0.44918808" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600504 [1174] (title: An Object-Based) is a human-generated sample, misclassified as AI-generated with confidence 0.44918808 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600504 [1174] (title: An Object-Based) is a human-generated sample, misclassified as AI-generated with confidence 0.44918808
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i88]" time="0.349"><properties><property name="score" value="0.19779663" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600505 [1747] (title: The Event-Drive) is a human-generated sample, misclassified as AI-generated with confidence 0.19779663 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600505 [1747] (title: The Event-Drive) is a human-generated sample, misclassified as AI-generated with confidence 0.19779663
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i89]" time="0.389"><properties><property name="score" value="0.8293892" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600508 [1537] (title: A Raspberry Pi ) is a human-generated sample, misclassified as AI-generated with confidence 0.8293892 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600508 [1537] (title: A Raspberry Pi ) is a human-generated sample, misclassified as AI-generated with confidence 0.8293892
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i90]" time="0.403"><properties><property name="score" value="0.38365427" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600509 [1294] (title: The Detection o) is a human-generated sample, misclassified as AI-generated with confidence 0.38365427 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600509 [1294] (title: The Detection o) is a human-generated sample, misclassified as AI-generated with confidence 0.38365427
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i91]" time="0.276"><properties><property name="score" value="0.66522557" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600519 [1124] (title: Outage Performa) is a human-generated sample, misclassified as AI-generated with confidence 0.66522557 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600519 [1124] (title: Outage Performa) is a human-generated sample, misclassified as AI-generated with confidence 0.66522557
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i92]" time="0.306"><properties><property name="score" value="0.08425352" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i93]" time="0.321"><properties><property name="score" value="0.79538286" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i94]" time="0.351"><properties><property name="score" value="0.642163" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600542 [1409] (title: Optimal Smart I) is a human-generated sample, misclassified as AI-generated with confidence 0.642163 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600542 [1409] (title: Optimal Smart I) is a human-generated sample, misclassified as AI-generated with confidence 0.642163
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i95]" time="0.323"><properties><property name="score" value="0.85190016" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600543 [1153] (title: Real-Time Simul) is a human-generated sample, misclassified as AI-generated with confidence 0.85190016 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600543 [1153] (title: Real-Time Simul) is a human-generated sample, misclassified as AI-generated with confidence 0.85190016
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i96]" time="0.412"><properties><property name="score" value="0.37882385" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600545 [1001] (title: A Search Space ) is a human-generated sample, misclassified as AI-generated with confidence 0.37882385 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600545 [1001] (title: A Search Space ) is a human-generated sample, misclassified as AI-generated with confidence 0.37882385
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i97]" time="0.308"><properties><property name="score" value="0.077714376" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i98]" time="0.303"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i99]" time="0.274"><properties><property name="score" value="0.62239784" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600571 [1393] (title: Appropriate Tol) is a human-generated sample, misclassified as AI-generated with confidence 0.62239784 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600571 [1393] (title: Appropriate Tol) is a human-generated sample, misclassified as AI-generated with confidence 0.62239784
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i100]" time="0.336"><properties><property name="score" value="0.8249242" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600584 [1150] (title: Minimization of) is a human-generated sample, misclassified as AI-generated with confidence 0.8249242 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600584 [1150] (title: Minimization of) is a human-generated sample, misclassified as AI-generated with confidence 0.8249242
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i101]" time="0.355"><properties><property name="score" value="0.263328" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600595 [1239] (title: An Artificial N) is a human-generated sample, misclassified as AI-generated with confidence 0.263328 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600595 [1239] (title: An Artificial N) is a human-generated sample, misclassified as AI-generated with confidence 0.263328
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i102]" time="0.352"><properties><property name="score" value="0.33637396" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i103]" time="0.323"><properties><property name="score" value="0.5536582" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600617 [1062] (title: Geometrically M) is a human-generated sample, misclassified as AI-generated with confidence 0.5536582 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600617 [1062] (title: Geometrically M) is a human-generated sample, misclassified as AI-generated with confidence 0.5536582
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i104]" time="0.285"><properties><property name="score" value="0.32320353" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600635 [1401] (title: MILP Model for ) is a human-generated sample, misclassified as AI-generated with confidence 0.32320353 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600635 [1401] (title: MILP Model for ) is a human-generated sample, misclassified as AI-generated with confidence 0.32320353
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i105]" time="0.270"><properties><property name="score" value="0.21225177" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i106]" time="0.689"><properties><property name="score" value="0.49862882" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600657 [1012] (title: Effect of Solar) is a human-generated sample, misclassified as AI-generated with confidence 0.49862882 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600657 [1012] (title: Effect of Solar) is a human-generated sample, misclassified as AI-generated with confidence 0.49862882
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i107]" time="0.317"><properties><property name="score" value="0.7527631" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i108]" time="0.351"><properties><property name="score" value="0.6214843" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600675 [1559] (title: A Dynamic State) is a human-generated sample, misclassified as AI-generated with confidence 0.6214843 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600675 [1559] (title: A Dynamic State) is a human-generated sample, misclassified as AI-generated with confidence 0.6214843
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i109]" time="0.406"><properties><property name="score" value="1.2675198" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600681 [1118] (title: Least-Cost Join) is a human-generated sample, misclassified as AI-generated with confidence 1.2675198 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600681 [1118] (title: Least-Cost Join) is a human-generated sample, misclassified as AI-generated with confidence 1.2675198
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i110]" time="0.307"><properties><property name="score" value="0.43320435" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600713 [1298] (title: Using PPG Signa) is a human-generated sample, misclassified as AI-generated with confidence 0.43320435 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600713 [1298] (title: Using PPG Signa) is a human-generated sample, misclassified as AI-generated with confidence 0.43320435
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i111]" time="0.284"><properties><property name="score" value="0.21360624" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600717 [1009] (title: Deterministic P) is a human-generated sample, misclassified as AI-generated with confidence 0.21360624 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600717 [1009] (title: Deterministic P) is a human-generated sample, misclassified as AI-generated with confidence 0.21360624
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i112]" time="0.287"><properties><property name="score" value="0.67968285" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i113]" time="0.328"><properties><property name="score" value="1.0311917" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600727 [1458] (title: Three-Dimension) is a human-generated sample, misclassified as AI-generated with confidence 1.0311917 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600727 [1458] (title: Three-Dimension) is a human-generated sample, misclassified as AI-generated with confidence 1.0311917
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i114]" time="0.331"><properties><property name="score" value="0.08710522" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600730 [1483] (title: High-Performanc) is a human-generated sample, misclassified as AI-generated with confidence 0.08710522 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600730 [1483] (title: High-Performanc) is a human-generated sample, misclassified as AI-generated with confidence 0.08710522
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i115]" time="0.315"><properties><property name="score" value="0.018039158" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i116]" time="0.296"><properties><property name="score" value="0.14450566" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i117]" time="0.352"><properties><property name="score" value="0.2087696" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i118]" time="0.346"><properties><property name="score" value="0.2482344" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i119]" time="0.347"><properties><property name="score" value="0.08240387" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600738 [1441] (title: Enhancing Cloud) is a human-generated sample, misclassified as AI-generated with confidence 0.08240387 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600738 [1441] (title: Enhancing Cloud) is a human-generated sample, misclassified as AI-generated with confidence 0.08240387
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i120]" time="0.300"><properties><property name="score" value="0.2847748" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600750 [1117] (title: Security and Pr) is a human-generated sample, misclassified as AI-generated with confidence 0.2847748 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600750 [1117] (title: Security and Pr) is a human-generated sample, misclassified as AI-generated with confidence 0.2847748
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i121]" time="0.325"><properties><property name="score" value="0.12475284" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600752 [1145] (title: Active Learning) is a human-generated sample, misclassified as AI-generated with confidence 0.12475284 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600752 [1145] (title: Active Learning) is a human-generated sample, misclassified as AI-generated with confidence 0.12475284
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i122]" time="0.292"><properties><property name="score" value="1.1463637" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i123]" time="0.387"><properties><property name="score" value="0.7556953" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i124]" time="0.311"><properties><property name="score" value="0.011379632" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i125]" time="0.413"><properties><property name="score" value="0.63536924" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i126]" time="0.361"><properties><property name="score" value="0.23779307" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600779 [1202] (title: Privacy-Preserv) is a human-generated sample, misclassified as AI-generated with confidence 0.23779307 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600779 [1202] (title: Privacy-Preserv) is a human-generated sample, misclassified as AI-generated with confidence 0.23779307
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i127]" time="0.340"><properties><property name="score" value="0.57953584" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i128]" time="0.417"><properties><property name="score" value="0.30392566" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600781 [1205] (title: Proactive Cache) is a human-generated sample, misclassified as AI-generated with confidence 0.30392566 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600781 [1205] (title: Proactive Cache) is a human-generated sample, misclassified as AI-generated with confidence 0.30392566
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i129]" time="0.418"><properties><property name="score" value="0.113301046" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600783 [1017] (title: Privacy of Thin) is a human-generated sample, misclassified as AI-generated with confidence 0.11330105 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600783 [1017] (title: Privacy of Thin) is a human-generated sample, misclassified as AI-generated with confidence 0.11330105
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i130]" time="0.449"><properties><property name="score" value="0.97919285" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i131]" time="0.358"><properties><property name="score" value="0.6761058" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600788 [1815] (title: Communication s) is a human-generated sample, misclassified as AI-generated with confidence 0.6761058 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600788 [1815] (title: Communication s) is a human-generated sample, misclassified as AI-generated with confidence 0.6761058
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i132]" time="0.298"><properties><property name="score" value="0.020194504" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i133]" time="0.486"><properties><property name="score" value="0.5307242" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i134]" time="0.300"><properties><property name="score" value="0.7392568" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600819 [1087] (title: Small Parts Cla) is a human-generated sample, misclassified as AI-generated with confidence 0.7392568 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600819 [1087] (title: Small Parts Cla) is a human-generated sample, misclassified as AI-generated with confidence 0.7392568
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i135]" time="0.277"><properties><property name="score" value="0.6914189" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i136]" time="0.308"><properties><property name="score" value="1.2786443" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i137]" time="0.289"><properties><property name="score" value="0.89456654" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600828 [1160] (title: IoT-based Water) is a human-generated sample, misclassified as AI-generated with confidence 0.89456654 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600828 [1160] (title: IoT-based Water) is a human-generated sample, misclassified as AI-generated with confidence 0.89456654
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i138]" time="0.305"><properties><property name="score" value="0.40499032" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600837 [1051] (title: IoT Based Poult) is a human-generated sample, misclassified as AI-generated with confidence 0.40499032 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600837 [1051] (title: IoT Based Poult) is a human-generated sample, misclassified as AI-generated with confidence 0.40499032
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i139]" time="0.268"><properties><property name="score" value="0.278445" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i140]" time="0.262"><properties><property name="score" value="1.0814891" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i141]" time="0.293"><properties><property name="score" value="0.18040343" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i142]" time="0.274"><properties><property name="score" value="1.6454265" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600852 [1156] (title: Speaker Recogni) is a human-generated sample, misclassified as AI-generated with confidence 1.6454265 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600852 [1156] (title: Speaker Recogni) is a human-generated sample, misclassified as AI-generated with confidence 1.6454265
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i143]" time="0.446"><properties><property name="score" value="0.94250846" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600855 [1078] (title: Potential Level) is a human-generated sample, misclassified as AI-generated with confidence 0.94250846 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600855 [1078] (title: Potential Level) is a human-generated sample, misclassified as AI-generated with confidence 0.94250846
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i144]" time="0.297"><properties><property name="score" value="0.49498782" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600856 [1501] (title: Generative mode) is a human-generated sample, misclassified as AI-generated with confidence 0.49498782 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600856 [1501] (title: Generative mode) is a human-generated sample, misclassified as AI-generated with confidence 0.49498782
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i145]" time="0.271"><properties><property name="score" value="0.003125862" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i146]" time="0.284"><properties><property name="score" value="0.106054954" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i147]" time="0.419"><properties><property name="score" value="0.026065517" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i148]" time="0.283"><properties><property name="score" value="0.9280986" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i149]" time="0.287"><properties><property name="score" value="0.3841762" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600862 [1211] (title: Large Data Down) is a human-generated sample, misclassified as AI-generated with confidence 0.3841762 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600862 [1211] (title: Large Data Down) is a human-generated sample, misclassified as AI-generated with confidence 0.3841762
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i150]" time="0.256"><properties><property name="score" value="0.84554917" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i151]" time="0.276"><properties><property name="score" value="0.23075087" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600867 [1018] (title: Applying Intell) is a human-generated sample, misclassified as AI-generated with confidence 0.23075087 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600867 [1018] (title: Applying Intell) is a human-generated sample, misclassified as AI-generated with confidence 0.23075087
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i152]" time="0.278"><properties><property name="score" value="0.794241" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600869 [1273] (title: Flood Modelling) is a human-generated sample, misclassified as AI-generated with confidence 0.794241 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600869 [1273] (title: Flood Modelling) is a human-generated sample, misclassified as AI-generated with confidence 0.794241
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i153]" time="0.280"><properties><property name="score" value="0.02463375" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i154]" time="0.323"><properties><property name="score" value="0.5308558" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600879 [1032] (title: A Configurable ) is a human-generated sample, misclassified as AI-generated with confidence 0.5308558 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600879 [1032] (title: A Configurable ) is a human-generated sample, misclassified as AI-generated with confidence 0.5308558
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i155]" time="0.305"><properties><property name="score" value="0.03949189" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i156]" time="0.306"><properties><property name="score" value="0.16926554" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i157]" time="0.286"><properties><property name="score" value="2.2057722" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600890 [1328] (title: Opportunistic W) is a human-generated sample, misclassified as AI-generated with confidence 2.2057722 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600890 [1328] (title: Opportunistic W) is a human-generated sample, misclassified as AI-generated with confidence 2.2057722
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i158]" time="0.262"><properties><property name="score" value="0.1394603" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i159]" time="0.257"><properties><property name="score" value="0.3100189" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i160]" time="0.271"><properties><property name="score" value="0.11663987" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i161]" time="0.293"><properties><property name="score" value="0.16733319" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i162]" time="0.291"><properties><property name="score" value="0.8681525" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i163]" time="0.294"><properties><property name="score" value="0.4896823" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600912 [1064] (title: Automatic mass ) is a human-generated sample, misclassified as AI-generated with confidence 0.4896823 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600912 [1064] (title: Automatic mass ) is a human-generated sample, misclassified as AI-generated with confidence 0.4896823
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i164]" time="0.280"><properties><property name="score" value="1.187183" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i165]" time="0.286"><properties><property name="score" value="0.98466057" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i166]" time="0.311"><properties><property name="score" value="0.4412976" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600924 [1049] (title: SEECSSim - A Pa) is a human-generated sample, misclassified as AI-generated with confidence 0.4412976 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600924 [1049] (title: SEECSSim - A Pa) is a human-generated sample, misclassified as AI-generated with confidence 0.4412976
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i167]" time="0.313"><properties><property name="score" value="0.9755149" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i168]" time="0.288"><properties><property name="score" value="0.94478065" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i169]" time="0.320"><properties><property name="score" value="0.02143912" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i170]" time="0.291"><properties><property name="score" value="0.31779733" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i171]" time="0.294"><properties><property name="score" value="0.39030612" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8600998 [1517] (title: Adaptive Event ) is a human-generated sample, misclassified as AI-generated with confidence 0.39030612 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8600998 [1517] (title: Adaptive Event ) is a human-generated sample, misclassified as AI-generated with confidence 0.39030612
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i172]" time="0.289"><properties><property name="score" value="0.6933974" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i173]" time="0.295"><properties><property name="score" value="0.189478" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601014 [1153] (title: A Comprehensive) is a human-generated sample, misclassified as AI-generated with confidence 0.189478 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601014 [1153] (title: A Comprehensive) is a human-generated sample, misclassified as AI-generated with confidence 0.189478
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i174]" time="0.286"><properties><property name="score" value="0.30835676" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i175]" time="0.279"><properties><property name="score" value="0.550288" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601020 [1131] (title: A Platform for ) is a human-generated sample, misclassified as AI-generated with confidence 0.550288 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601020 [1131] (title: A Platform for ) is a human-generated sample, misclassified as AI-generated with confidence 0.550288
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i176]" time="0.302"><properties><property name="score" value="0.22209279" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i177]" time="0.257"><properties><property name="score" value="0.79973555" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i178]" time="0.306"><properties><property name="score" value="0.4015386" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i179]" time="0.285"><properties><property name="score" value="0.93291914" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601095 [1495] (title: A Multi-Criteri) is a human-generated sample, misclassified as AI-generated with confidence 0.93291914 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601095 [1495] (title: A Multi-Criteri) is a human-generated sample, misclassified as AI-generated with confidence 0.93291914
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i180]" time="0.307"><properties><property name="score" value="0.19560422" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i181]" time="0.302"><properties><property name="score" value="0.4624425" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i182]" time="0.308"><properties><property name="score" value="0.17399707" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601184 [1673] (title: A Cooperation A) is a human-generated sample, misclassified as AI-generated with confidence 0.17399707 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601184 [1673] (title: A Cooperation A) is a human-generated sample, misclassified as AI-generated with confidence 0.17399707
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i183]" time="0.308"><properties><property name="score" value="0.030100834" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i184]" time="0.285"><properties><property name="score" value="0.20136902" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601186 [1242] (title: A Survey of Ste) is a human-generated sample, misclassified as AI-generated with confidence 0.20136902 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601186 [1242] (title: A Survey of Ste) is a human-generated sample, misclassified as AI-generated with confidence 0.20136902
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i185]" time="0.454"><properties><property name="score" value="0.019732919" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i186]" time="1.081"><properties><property name="score" value="1.3240657" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i187]" time="0.329"><properties><property name="score" value="0.25374427" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601196 [1429] (title: An Active Learn) is a human-generated sample, misclassified as AI-generated with confidence 0.25374427 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601196 [1429] (title: An Active Learn) is a human-generated sample, misclassified as AI-generated with confidence 0.25374427
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i188]" time="0.389"><properties><property name="score" value="0.02488792" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i189]" time="0.277"><properties><property name="score" value="0.35807183" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i190]" time="0.327"><properties><property name="score" value="1.2548246" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601218 [1012] (title: Detecting and R) is a human-generated sample, misclassified as AI-generated with confidence 1.2548246 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601218 [1012] (title: Detecting and R) is a human-generated sample, misclassified as AI-generated with confidence 1.2548246
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i191]" time="0.339"><properties><property name="score" value="0.9992099" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i192]" time="0.320"><properties><property name="score" value="0.34046805" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i193]" time="0.289"><properties><property name="score" value="0.22508784" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i194]" time="0.290"><properties><property name="score" value="0.36308393" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i195]" time="0.284"><properties><property name="score" value="0.23624013" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i196]" time="0.353"><properties><property name="score" value="0.21479763" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601249 [1545] (title: The Value Persp) is a human-generated sample, misclassified as AI-generated with confidence 0.21479763 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601249 [1545] (title: The Value Persp) is a human-generated sample, misclassified as AI-generated with confidence 0.21479763
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i197]" time="0.293"><properties><property name="score" value="0.88456523" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601250 [1410] (title: A Framework to ) is a human-generated sample, misclassified as AI-generated with confidence 0.88456523 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601250 [1410] (title: A Framework to ) is a human-generated sample, misclassified as AI-generated with confidence 0.88456523
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i198]" time="0.334"><properties><property name="score" value="0.0844938" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601260 [1306] (title: Improving Class) is a human-generated sample, misclassified as AI-generated with confidence 0.0844938 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601260 [1306] (title: Improving Class) is a human-generated sample, misclassified as AI-generated with confidence 0.0844938
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i199]" time="0.274"><properties><property name="score" value="0.15109494" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i200]" time="0.437"><properties><property name="score" value="1.2944726" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601262 [1620] (title: The Effects of ) is a human-generated sample, misclassified as AI-generated with confidence 1.2944726 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601262 [1620] (title: The Effects of ) is a human-generated sample, misclassified as AI-generated with confidence 1.2944726
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i201]" time="0.324"><properties><property name="score" value="0.106914036" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601271 [1462] (title: Employment Law ) is a human-generated sample, misclassified as AI-generated with confidence 0.10691404 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601271 [1462] (title: Employment Law ) is a human-generated sample, misclassified as AI-generated with confidence 0.10691404
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i202]" time="0.323"><properties><property name="score" value="0.28221682" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601272 [1113] (title: Design of an Au) is a human-generated sample, misclassified as AI-generated with confidence 0.28221682 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601272 [1113] (title: Design of an Au) is a human-generated sample, misclassified as AI-generated with confidence 0.28221682
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i203]" time="0.278"><properties><property name="score" value="0.20911933" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601277 [1005] (title: Asymptotic Anal) is a human-generated sample, misclassified as AI-generated with confidence 0.20911933 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601277 [1005] (title: Asymptotic Anal) is a human-generated sample, misclassified as AI-generated with confidence 0.20911933
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i204]" time="0.290"><properties><property name="score" value="0.6517461" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601280 [1292] (title: The Experimenta) is a human-generated sample, misclassified as AI-generated with confidence 0.6517461 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601280 [1292] (title: The Experimenta) is a human-generated sample, misclassified as AI-generated with confidence 0.6517461
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i205]" time="0.304"><properties><property name="score" value="0.78683734" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601291 [1168] (title: Improving Assoc) is a human-generated sample, misclassified as AI-generated with confidence 0.78683734 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601291 [1168] (title: Improving Assoc) is a human-generated sample, misclassified as AI-generated with confidence 0.78683734
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i206]" time="0.427"><properties><property name="score" value="0.565756" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601298 [1489] (title: Services and Ap) is a human-generated sample, misclassified as AI-generated with confidence 0.565756 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601298 [1489] (title: Services and Ap) is a human-generated sample, misclassified as AI-generated with confidence 0.565756
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i207]" time="0.322"><properties><property name="score" value="0.058953345" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i208]" time="0.300"><properties><property name="score" value="0.58796096" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i209]" time="0.290"><properties><property name="score" value="0.5080081" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i210]" time="0.270"><properties><property name="score" value="0.3380891" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i211]" time="0.293"><properties><property name="score" value="0.2016192" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601324 [1166] (title: GAN-Based Semi-) is a human-generated sample, misclassified as AI-generated with confidence 0.2016192 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601324 [1166] (title: GAN-Based Semi-) is a human-generated sample, misclassified as AI-generated with confidence 0.2016192
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i212]" time="0.271"><properties><property name="score" value="0.4407868" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i213]" time="0.292"><properties><property name="score" value="1.0949731" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i214]" time="0.322"><properties><property name="score" value="0.46331605" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i215]" time="0.344"><properties><property name="score" value="0.33864063" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601345 [1234] (title: Active Object D) is a human-generated sample, misclassified as AI-generated with confidence 0.33864063 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601345 [1234] (title: Active Object D) is a human-generated sample, misclassified as AI-generated with confidence 0.33864063
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i216]" time="0.334"><properties><property name="score" value="0.17662464" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i217]" time="0.318"><properties><property name="score" value="0.5567184" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i218]" time="0.359"><properties><property name="score" value="0.20556632" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601356 [1184] (title: Identification ) is a human-generated sample, misclassified as AI-generated with confidence 0.20556632 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601356 [1184] (title: Identification ) is a human-generated sample, misclassified as AI-generated with confidence 0.20556632
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i219]" time="0.408"><properties><property name="score" value="0.034900177" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i220]" time="0.328"><properties><property name="score" value="1.2313335" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i221]" time="0.303"><properties><property name="score" value="0.71313584" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i222]" time="0.366"><properties><property name="score" value="0.068262026" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i223]" time="0.324"><properties><property name="score" value="1.4694997" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601379 [1136] (title: Stiffness Contr) is a human-generated sample, misclassified as AI-generated with confidence 1.4694997 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601379 [1136] (title: Stiffness Contr) is a human-generated sample, misclassified as AI-generated with confidence 1.4694997
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i224]" time="0.335"><properties><property name="score" value="0.11317956" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i225]" time="0.401"><properties><property name="score" value="0.33582175" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i226]" time="0.341"><properties><property name="score" value="0.21386006" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i227]" time="0.307"><properties><property name="score" value="0.24936092" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i228]" time="0.299"><properties><property name="score" value="0.7322651" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601451 [1328] (title: Evaluation of P) is a human-generated sample, misclassified as AI-generated with confidence 0.7322651 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601451 [1328] (title: Evaluation of P) is a human-generated sample, misclassified as AI-generated with confidence 0.7322651
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i229]" time="0.292"><properties><property name="score" value="1.5973018" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i230]" time="0.315"><properties><property name="score" value="0.09811767" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601472 [1208] (title: Information Dec) is a human-generated sample, misclassified as AI-generated with confidence 0.09811767 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601472 [1208] (title: Information Dec) is a human-generated sample, misclassified as AI-generated with confidence 0.09811767
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i231]" time="0.337"><properties><property name="score" value="1.404128" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i232]" time="0.299"><properties><property name="score" value="0.28761104" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i233]" time="0.275"><properties><property name="score" value="1.9897557" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601497 [1656] (title: Estimation of P) is a human-generated sample, misclassified as AI-generated with confidence 1.9897557 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601497 [1656] (title: Estimation of P) is a human-generated sample, misclassified as AI-generated with confidence 1.9897557
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i234]" time="0.288"><properties><property name="score" value="1.1236458" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601526 [1248] (title: The Use of Non-) is a human-generated sample, misclassified as AI-generated with confidence 1.1236458 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601526 [1248] (title: The Use of Non-) is a human-generated sample, misclassified as AI-generated with confidence 1.1236458
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i235]" time="0.320"><properties><property name="score" value="0.6563801" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i236]" time="0.308"><properties><property name="score" value="0.3671258" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601547 [1581] (title: Bridging the Ga) is a human-generated sample, misclassified as AI-generated with confidence 0.3671258 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601547 [1581] (title: Bridging the Ga) is a human-generated sample, misclassified as AI-generated with confidence 0.3671258
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i237]" time="0.294"><properties><property name="score" value="0.40933606" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i238]" time="0.348"><properties><property name="score" value="0.49926567" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i239]" time="0.285"><properties><property name="score" value="1.1312103" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i240]" time="0.281"><properties><property name="score" value="0.5338558" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i241]" time="0.293"><properties><property name="score" value="0.5268859" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601588 [1229] (title: An Equivalent M) is a human-generated sample, misclassified as AI-generated with confidence 0.5268859 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601588 [1229] (title: An Equivalent M) is a human-generated sample, misclassified as AI-generated with confidence 0.5268859
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i242]" time="0.329"><properties><property name="score" value="0.01007491" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i243]" time="0.367"><properties><property name="score" value="0.77608293" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601654 [1295] (title: Equivalent Mode) is a human-generated sample, misclassified as AI-generated with confidence 0.77608293 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601654 [1295] (title: Equivalent Mode) is a human-generated sample, misclassified as AI-generated with confidence 0.77608293
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i244]" time="0.358"><properties><property name="score" value="0.6266418" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601668 [1183] (title: Decision Tree-b) is a human-generated sample, misclassified as AI-generated with confidence 0.6266418 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601668 [1183] (title: Decision Tree-b) is a human-generated sample, misclassified as AI-generated with confidence 0.6266418
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i245]" time="0.379"><properties><property name="score" value="0.16795315" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i246]" time="0.412"><properties><property name="score" value="0.008080281" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i247]" time="0.358"><properties><property name="score" value="0.17300534" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i248]" time="0.362"><properties><property name="score" value="0.5628502" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601701 [1797] (title: IoT Sensor Netw) is a human-generated sample, misclassified as AI-generated with confidence 0.5628502 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601701 [1797] (title: IoT Sensor Netw) is a human-generated sample, misclassified as AI-generated with confidence 0.5628502
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i249]" time="0.345"><properties><property name="score" value="0.70300466" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i250]" time="0.330"><properties><property name="score" value="0.7177403" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601711 [1189] (title: Analysis of Onl) is a human-generated sample, misclassified as AI-generated with confidence 0.7177403 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601711 [1189] (title: Analysis of Onl) is a human-generated sample, misclassified as AI-generated with confidence 0.7177403
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i251]" time="0.310"><properties><property name="score" value="0.61939174" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601731 [1273] (title: A Simplified In) is a human-generated sample, misclassified as AI-generated with confidence 0.61939174 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601731 [1273] (title: A Simplified In) is a human-generated sample, misclassified as AI-generated with confidence 0.61939174
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i252]" time="0.315"><properties><property name="score" value="0.0927923" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601739 [1146] (title: A Novel Methodo) is a human-generated sample, misclassified as AI-generated with confidence 0.0927923 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601739 [1146] (title: A Novel Methodo) is a human-generated sample, misclassified as AI-generated with confidence 0.0927923
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i253]" time="0.584"><properties><property name="score" value="0.113395244" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i254]" time="0.264"><properties><property name="score" value="1.4567217" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i255]" time="0.323"><properties><property name="score" value="0.20144303" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i256]" time="0.275"><properties><property name="score" value="0.76972765" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601799 [2455] (title: Fast Amplitude ) is a human-generated sample, misclassified as AI-generated with confidence 0.76972765 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601799 [2455] (title: Fast Amplitude ) is a human-generated sample, misclassified as AI-generated with confidence 0.76972765
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i257]" time="0.245"><properties><property name="score" value="0.5535174" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i258]" time="0.293"><properties><property name="score" value="0.060936198" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i259]" time="0.370"><properties><property name="score" value="0.102400675" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i260]" time="0.303"><properties><property name="score" value="0.34431264" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601825 [1214] (title: Operation and M) is a human-generated sample, misclassified as AI-generated with confidence 0.34431264 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601825 [1214] (title: Operation and M) is a human-generated sample, misclassified as AI-generated with confidence 0.34431264
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i261]" time="0.293"><properties><property name="score" value="0.3054286" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i262]" time="0.337"><properties><property name="score" value="0.5931288" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i263]" time="0.292"><properties><property name="score" value="0.8599846" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601833 [1262] (title: An Image Recogn) is a human-generated sample, misclassified as AI-generated with confidence 0.8599846 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601833 [1262] (title: An Image Recogn) is a human-generated sample, misclassified as AI-generated with confidence 0.8599846
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i264]" time="0.316"><properties><property name="score" value="1.3415132" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i265]" time="0.305"><properties><property name="score" value="0.31396034" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i266]" time="0.284"><properties><property name="score" value="0.20685075" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i267]" time="0.310"><properties><property name="score" value="0.1352714" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i268]" time="0.326"><properties><property name="score" value="1.2057436" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i269]" time="0.306"><properties><property name="score" value="0.85521734" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i270]" time="0.297"><properties><property name="score" value="0.41742882" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601896 [1239] (title: Experimental Re) is a human-generated sample, misclassified as AI-generated with confidence 0.41742882 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601896 [1239] (title: Experimental Re) is a human-generated sample, misclassified as AI-generated with confidence 0.41742882
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i271]" time="0.308"><properties><property name="score" value="0.38896608" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i272]" time="0.279"><properties><property name="score" value="0.135266" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i273]" time="0.282"><properties><property name="score" value="0.23570167" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i274]" time="0.277"><properties><property name="score" value="0.20107111" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601913 [1657] (title: Roadmap for Des) is a human-generated sample, misclassified as AI-generated with confidence 0.20107111 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601913 [1657] (title: Roadmap for Des) is a human-generated sample, misclassified as AI-generated with confidence 0.20107111
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i275]" time="1.275"><properties><property name="score" value="0.12941407" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601928 [1616] (title: Internet of Thi) is a human-generated sample, misclassified as AI-generated with confidence 0.12941407 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601928 [1616] (title: Internet of Thi) is a human-generated sample, misclassified as AI-generated with confidence 0.12941407
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i276]" time="0.285"><properties><property name="score" value="0.06992689" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i277]" time="0.480"><properties><property name="score" value="0.12020778" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601934 [1339] (title: Intelligent Mob) is a human-generated sample, misclassified as AI-generated with confidence 0.12020778 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601934 [1339] (title: Intelligent Mob) is a human-generated sample, misclassified as AI-generated with confidence 0.12020778
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i278]" time="0.293"><properties><property name="score" value="0.7000142" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8601945 [1456] (title: Cascading Failu) is a human-generated sample, misclassified as AI-generated with confidence 0.7000142 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8601945 [1456] (title: Cascading Failu) is a human-generated sample, misclassified as AI-generated with confidence 0.7000142
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i279]" time="0.286"><properties><property name="score" value="0.76164925" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602022 [1029] (title: Development and) is a human-generated sample, misclassified as AI-generated with confidence 0.76164925 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602022 [1029] (title: Development and) is a human-generated sample, misclassified as AI-generated with confidence 0.76164925
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i280]" time="0.294"><properties><property name="score" value="0.5240061" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602034 [1046] (title: Engineering Sim) is a human-generated sample, misclassified as AI-generated with confidence 0.5240061 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602034 [1046] (title: Engineering Sim) is a human-generated sample, misclassified as AI-generated with confidence 0.5240061
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i281]" time="0.420"><properties><property name="score" value="0.4054209" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602075 [1327] (title: Robust Algorith) is a human-generated sample, misclassified as AI-generated with confidence 0.4054209 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602075 [1327] (title: Robust Algorith) is a human-generated sample, misclassified as AI-generated with confidence 0.4054209
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i282]" time="0.448"><properties><property name="score" value="0.09142539" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i283]" time="0.292"><properties><property name="score" value="0.0056807334" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i284]" time="0.308"><properties><property name="score" value="0.13081302" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i285]" time="0.267"><properties><property name="score" value="0.52873766" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602101 [1152] (title: Optimal Control) is a human-generated sample, misclassified as AI-generated with confidence 0.52873766 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602101 [1152] (title: Optimal Control) is a human-generated sample, misclassified as AI-generated with confidence 0.52873766
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i286]" time="0.271"><properties><property name="score" value="0.24792889" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i287]" time="0.271"><properties><property name="score" value="0.03760794" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i288]" time="0.314"><properties><property name="score" value="0.15808874" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602122 [1066] (title: Growth Height P) is a human-generated sample, misclassified as AI-generated with confidence 0.15808874 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602122 [1066] (title: Growth Height P) is a human-generated sample, misclassified as AI-generated with confidence 0.15808874
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i289]" time="0.294"><properties><property name="score" value="0.2726651" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602140 [1000] (title: Identification ) is a human-generated sample, misclassified as AI-generated with confidence 0.2726651 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602140 [1000] (title: Identification ) is a human-generated sample, misclassified as AI-generated with confidence 0.2726651
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i290]" time="0.312"><properties><property name="score" value="0.5769374" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602141 [1187] (title: A Fault Line De) is a human-generated sample, misclassified as AI-generated with confidence 0.5769374 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602141 [1187] (title: A Fault Line De) is a human-generated sample, misclassified as AI-generated with confidence 0.5769374
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i291]" time="0.273"><properties><property name="score" value="0.36760768" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i292]" time="0.333"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i293]" time="0.283"><properties><property name="score" value="0.5180569" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602149 [1353] (title: Research on Ima) is a human-generated sample, misclassified as AI-generated with confidence 0.5180569 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602149 [1353] (title: Research on Ima) is a human-generated sample, misclassified as AI-generated with confidence 0.5180569
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i294]" time="0.470"><properties><property name="score" value="0.36935863" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i295]" time="0.279"><properties><property name="score" value="0.53583395" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i296]" time="0.315"><properties><property name="score" value="0.4330459" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602195 [1019] (title: Classification ) is a human-generated sample, misclassified as AI-generated with confidence 0.4330459 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602195 [1019] (title: Classification ) is a human-generated sample, misclassified as AI-generated with confidence 0.4330459
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i297]" time="0.291"><properties><property name="score" value="0.5656857" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602202 [1201] (title: Research on tra) is a human-generated sample, misclassified as AI-generated with confidence 0.5656857 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602202 [1201] (title: Research on tra) is a human-generated sample, misclassified as AI-generated with confidence 0.5656857
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i298]" time="0.305"><properties><property name="score" value="0.36179528" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602218 [1392] (title: New Generation ) is a human-generated sample, misclassified as AI-generated with confidence 0.36179528 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602218 [1392] (title: New Generation ) is a human-generated sample, misclassified as AI-generated with confidence 0.36179528
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i299]" time="0.283"><properties><property name="score" value="0.2866977" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602223 [1429] (title: Partial Dischar) is a human-generated sample, misclassified as AI-generated with confidence 0.2866977 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602223 [1429] (title: Partial Dischar) is a human-generated sample, misclassified as AI-generated with confidence 0.2866977
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i300]" time="0.267"><properties><property name="score" value="0.24123219" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i301]" time="0.326"><properties><property name="score" value="0.28917992" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602234 [1510] (title: A New Generaliz) is a human-generated sample, misclassified as AI-generated with confidence 0.28917992 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602234 [1510] (title: A New Generaliz) is a human-generated sample, misclassified as AI-generated with confidence 0.28917992
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i302]" time="0.322"><properties><property name="score" value="0.12380386" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i303]" time="0.312"><properties><property name="score" value="0.38197646" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602255 [1631] (title: Method of T-Con) is a human-generated sample, misclassified as AI-generated with confidence 0.38197646 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602255 [1631] (title: Method of T-Con) is a human-generated sample, misclassified as AI-generated with confidence 0.38197646
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i304]" time="0.309"><properties><property name="score" value="0.36035144" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i305]" time="0.270"><properties><property name="score" value="1.0258781" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i306]" time="0.263"><properties><property name="score" value="0.4378451" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602280 [1231] (title: Optimal control) is a human-generated sample, misclassified as AI-generated with confidence 0.4378451 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602280 [1231] (title: Optimal control) is a human-generated sample, misclassified as AI-generated with confidence 0.4378451
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i307]" time="0.277"><properties><property name="score" value="0.86849433" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i308]" time="0.310"><properties><property name="score" value="0.92657024" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i309]" time="0.270"><properties><property name="score" value="0.08779939" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602293 [1398] (title: Research on Fau) is a human-generated sample, misclassified as AI-generated with confidence 0.08779939 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602293 [1398] (title: Research on Fau) is a human-generated sample, misclassified as AI-generated with confidence 0.08779939
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i310]" time="0.279"><properties><property name="score" value="0.463091" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602297 [1028] (title: Infrared Image ) is a human-generated sample, misclassified as AI-generated with confidence 0.463091 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602297 [1028] (title: Infrared Image ) is a human-generated sample, misclassified as AI-generated with confidence 0.463091
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i311]" time="0.316"><properties><property name="score" value="0.39370167" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i312]" time="0.322"><properties><property name="score" value="0.87993616" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602316 [1309] (title: Fast Electromag) is a human-generated sample, misclassified as AI-generated with confidence 0.87993616 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602316 [1309] (title: Fast Electromag) is a human-generated sample, misclassified as AI-generated with confidence 0.87993616
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i313]" time="0.323"><properties><property name="score" value="0.18180154" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i314]" time="0.437"><properties><property name="score" value="0.16158882" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i315]" time="0.289"><properties><property name="score" value="0.7873088" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i316]" time="0.305"><properties><property name="score" value="0.37139863" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i317]" time="0.303"><properties><property name="score" value="0.5378096" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i318]" time="0.273"><properties><property name="score" value="2.7480383" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602453 [1393] (title: Volunteers Dile) is a human-generated sample, misclassified as AI-generated with confidence 2.7480383 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602453 [1393] (title: Volunteers Dile) is a human-generated sample, misclassified as AI-generated with confidence 2.7480383
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i319]" time="0.273"><properties><property name="score" value="1.3597906" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602457 [1512] (title: Ratio-Based Mul) is a human-generated sample, misclassified as AI-generated with confidence 1.3597906 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602457 [1512] (title: Ratio-Based Mul) is a human-generated sample, misclassified as AI-generated with confidence 1.3597906
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i320]" time="0.273"><properties><property name="score" value="0.2615254" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602459 [1088] (title: Software Define) is a human-generated sample, misclassified as AI-generated with confidence 0.2615254 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602459 [1088] (title: Software Define) is a human-generated sample, misclassified as AI-generated with confidence 0.2615254
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i321]" time="0.349"><properties><property name="score" value="0.58625674" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i322]" time="0.333"><properties><property name="score" value="0.36151195" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i323]" time="0.358"><properties><property name="score" value="0.25645435" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i324]" time="0.277"><properties><property name="score" value="0.29706526" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i325]" time="0.271"><properties><property name="score" value="1.0842237" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602515 [1379] (title: Algorithmic and) is a human-generated sample, misclassified as AI-generated with confidence 1.0842237 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602515 [1379] (title: Algorithmic and) is a human-generated sample, misclassified as AI-generated with confidence 1.0842237
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i326]" time="0.301"><properties><property name="score" value="0.16810997" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i327]" time="0.796"><properties><property name="score" value="0.020784514" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602533 [1418] (title: A Methodologica) is a human-generated sample, misclassified as AI-generated with confidence 0.02078451 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602533 [1418] (title: A Methodologica) is a human-generated sample, misclassified as AI-generated with confidence 0.02078451
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i328]" time="0.255"><properties><property name="score" value="0.2468124" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602640 [1496] (title: Tools for the D) is a human-generated sample, misclassified as AI-generated with confidence 0.2468124 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602640 [1496] (title: Tools for the D) is a human-generated sample, misclassified as AI-generated with confidence 0.2468124
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i329]" time="0.319"><properties><property name="score" value="0.24691616" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602647 [1103] (title: Electromagnetic) is a human-generated sample, misclassified as AI-generated with confidence 0.24691616 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602647 [1103] (title: Electromagnetic) is a human-generated sample, misclassified as AI-generated with confidence 0.24691616
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i330]" time="0.276"><properties><property name="score" value="0.14646044" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602709 [1266] (title: Two-Cascade Ext) is a human-generated sample, misclassified as AI-generated with confidence 0.14646044 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602709 [1266] (title: Two-Cascade Ext) is a human-generated sample, misclassified as AI-generated with confidence 0.14646044
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i331]" time="0.296"><properties><property name="score" value="0.17875522" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i332]" time="0.280"><properties><property name="score" value="0.56488556" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i333]" time="0.302"><properties><property name="score" value="0.8451587" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i334]" time="0.277"><properties><property name="score" value="0.13791344" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602766 [1696] (title: Application of ) is a human-generated sample, misclassified as AI-generated with confidence 0.13791344 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602766 [1696] (title: Application of ) is a human-generated sample, misclassified as AI-generated with confidence 0.13791344
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i335]" time="0.258"><properties><property name="score" value="0.118853904" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i336]" time="0.372"><properties><property name="score" value="1.0830874" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i337]" time="0.337"><properties><property name="score" value="0.68447465" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602773 [1119] (title: Vegetation Effe) is a human-generated sample, misclassified as AI-generated with confidence 0.68447465 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602773 [1119] (title: Vegetation Effe) is a human-generated sample, misclassified as AI-generated with confidence 0.68447465
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i338]" time="0.331"><properties><property name="score" value="0.24209698" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602796 [1070] (title: The Selecting o) is a human-generated sample, misclassified as AI-generated with confidence 0.24209698 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602796 [1070] (title: The Selecting o) is a human-generated sample, misclassified as AI-generated with confidence 0.24209698
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i339]" time="0.297"><properties><property name="score" value="0.0990056" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602810 [1537] (title: A Heuristic Alg) is a human-generated sample, misclassified as AI-generated with confidence 0.0990056 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602810 [1537] (title: A Heuristic Alg) is a human-generated sample, misclassified as AI-generated with confidence 0.0990056
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i340]" time="0.304"><properties><property name="score" value="0.3042736" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i341]" time="0.417"><properties><property name="score" value="0.9663066" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602855 [1248] (title: A Placement-Awa) is a human-generated sample, misclassified as AI-generated with confidence 0.9663066 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602855 [1248] (title: A Placement-Awa) is a human-generated sample, misclassified as AI-generated with confidence 0.9663066
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i342]" time="0.320"><properties><property name="score" value="0.24704649" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i343]" time="0.337"><properties><property name="score" value="0.062000293" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602866 [1170] (title: Graphical Simul) is a human-generated sample, misclassified as AI-generated with confidence 0.06200029 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602866 [1170] (title: Graphical Simul) is a human-generated sample, misclassified as AI-generated with confidence 0.06200029
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i344]" time="0.271"><properties><property name="score" value="0.57894135" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i345]" time="0.280"><properties><property name="score" value="1.6448197" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i346]" time="0.293"><properties><property name="score" value="0.1994371" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i347]" time="0.258"><properties><property name="score" value="0.19994037" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602898 [1314] (title: Recognition and) is a human-generated sample, misclassified as AI-generated with confidence 0.19994037 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602898 [1314] (title: Recognition and) is a human-generated sample, misclassified as AI-generated with confidence 0.19994037
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i348]" time="0.318"><properties><property name="score" value="0.9697719" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i349]" time="0.317"><properties><property name="score" value="0.20179778" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602930 [1299] (title: Fuzzy Multi-Cas) is a human-generated sample, misclassified as AI-generated with confidence 0.20179778 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602930 [1299] (title: Fuzzy Multi-Cas) is a human-generated sample, misclassified as AI-generated with confidence 0.20179778
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i350]" time="0.334"><properties><property name="score" value="0.57935315" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8602972 [1040] (title: Using Genetic A) is a human-generated sample, misclassified as AI-generated with confidence 0.57935315 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8602972 [1040] (title: Using Genetic A) is a human-generated sample, misclassified as AI-generated with confidence 0.57935315
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i351]" time="0.303"><properties><property name="score" value="0.5162415" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i352]" time="0.272"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i353]" time="0.376"><properties><property name="score" value="0.22979136" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i354]" time="0.284"><properties><property name="score" value="0.6668131" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603032 [1287] (title: Improving the C) is a human-generated sample, misclassified as AI-generated with confidence 0.6668131 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603032 [1287] (title: Improving the C) is a human-generated sample, misclassified as AI-generated with confidence 0.6668131
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i355]" time="0.284"><properties><property name="score" value="0.47164112" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603034 [1327] (title: Analysis of Usi) is a human-generated sample, misclassified as AI-generated with confidence 0.47164112 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603034 [1327] (title: Analysis of Usi) is a human-generated sample, misclassified as AI-generated with confidence 0.47164112
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i356]" time="0.291"><properties><property name="score" value="0.81829464" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i357]" time="0.342"><properties><property name="score" value="0.22693874" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i358]" time="0.313"><properties><property name="score" value="0.53793883" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603068 [1048] (title: A Psycholinguis) is a human-generated sample, misclassified as AI-generated with confidence 0.53793883 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603068 [1048] (title: A Psycholinguis) is a human-generated sample, misclassified as AI-generated with confidence 0.53793883
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i359]" time="0.281"><properties><property name="score" value="1.0602449" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603147 [1397] (title: UPSARA: A Model) is a human-generated sample, misclassified as AI-generated with confidence 1.0602449 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603147 [1397] (title: UPSARA: A Model) is a human-generated sample, misclassified as AI-generated with confidence 1.0602449
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i360]" time="0.286"><properties><property name="score" value="0.6373402" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i361]" time="0.392"><properties><property name="score" value="0.30789858" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i362]" time="0.317"><properties><property name="score" value="0.42358932" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603151 [1388] (title: Pattern-Based D) is a human-generated sample, misclassified as AI-generated with confidence 0.42358932 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603151 [1388] (title: Pattern-Based D) is a human-generated sample, misclassified as AI-generated with confidence 0.42358932
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i363]" time="0.308"><properties><property name="score" value="0.17190085" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i364]" time="0.310"><properties><property name="score" value="0.23773275" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i365]" time="0.316"><properties><property name="score" value="0.42952076" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603154 [1026] (title: Pacer: Automate) is a human-generated sample, misclassified as AI-generated with confidence 0.42952076 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603154 [1026] (title: Pacer: Automate) is a human-generated sample, misclassified as AI-generated with confidence 0.42952076
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i366]" time="0.381"><properties><property name="score" value="0.07242401" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i367]" time="0.383"><properties><property name="score" value="0.57755643" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603156 [1584] (title: Task Runtime Pr) is a human-generated sample, misclassified as AI-generated with confidence 0.57755643 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603156 [1584] (title: Task Runtime Pr) is a human-generated sample, misclassified as AI-generated with confidence 0.57755643
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i368]" time="0.412"><properties><property name="score" value="0.35021913" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i369]" time="0.424"><properties><property name="score" value="1.6299348" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i370]" time="0.342"><properties><property name="score" value="0.42658523" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603159 [1080] (title: Joint Load-Bala) is a human-generated sample, misclassified as AI-generated with confidence 0.42658523 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603159 [1080] (title: Joint Load-Bala) is a human-generated sample, misclassified as AI-generated with confidence 0.42658523
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i371]" time="0.394"><properties><property name="score" value="0.8229581" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603160 [1604] (title: Ensemble-Based ) is a human-generated sample, misclassified as AI-generated with confidence 0.8229581 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603160 [1604] (title: Ensemble-Based ) is a human-generated sample, misclassified as AI-generated with confidence 0.8229581
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i372]" time="0.364"><properties><property name="score" value="0.103783555" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i373]" time="0.331"><properties><property name="score" value="0.33898786" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603164 [1456] (title: Two Efficient Q) is a human-generated sample, misclassified as AI-generated with confidence 0.33898786 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603164 [1456] (title: Two Efficient Q) is a human-generated sample, misclassified as AI-generated with confidence 0.33898786
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i374]" time="0.461"><properties><property name="score" value="0.086591825" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i375]" time="0.443"><properties><property name="score" value="0.2865053" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i376]" time="0.428"><properties><property name="score" value="0.8905464" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i377]" time="0.287"><properties><property name="score" value="0.56709427" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603172 [1020] (title: A Multi-Cloud M) is a human-generated sample, misclassified as AI-generated with confidence 0.56709427 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603172 [1020] (title: A Multi-Cloud M) is a human-generated sample, misclassified as AI-generated with confidence 0.56709427
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i378]" time="0.333"><properties><property name="score" value="0.55403894" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i379]" time="0.299"><properties><property name="score" value="0.4371533" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i380]" time="0.296"><properties><property name="score" value="0.533204" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i381]" time="0.281"><properties><property name="score" value="1.0081822" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603196 [1102] (title: PredJoule: A Ti) is a human-generated sample, misclassified as AI-generated with confidence 1.0081822 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603196 [1102] (title: PredJoule: A Ti) is a human-generated sample, misclassified as AI-generated with confidence 1.0081822
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i382]" time="0.297"><properties><property name="score" value="0.12807383" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i383]" time="0.330"><properties><property name="score" value="0.5085288" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i384]" time="0.288"><properties><property name="score" value="0.46868342" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i385]" time="0.268"><properties><property name="score" value="0.10771893" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i386]" time="0.332"><properties><property name="score" value="0.48224756" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603211 [1209] (title: Work-in-Progres) is a human-generated sample, misclassified as AI-generated with confidence 0.48224756 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603211 [1209] (title: Work-in-Progres) is a human-generated sample, misclassified as AI-generated with confidence 0.48224756
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i387]" time="0.299"><properties><property name="score" value="0.49821234" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i388]" time="0.268"><properties><property name="score" value="0.062466964" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603250 [1703] (title: Tradeoffs Using) is a human-generated sample, misclassified as AI-generated with confidence 0.06246696 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603250 [1703] (title: Tradeoffs Using) is a human-generated sample, misclassified as AI-generated with confidence 0.06246696
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i389]" time="0.312"><properties><property name="score" value="1.0498333" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603251 [1460] (title: A Robust Iris S) is a human-generated sample, misclassified as AI-generated with confidence 1.0498333 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603251 [1460] (title: A Robust Iris S) is a human-generated sample, misclassified as AI-generated with confidence 1.0498333
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i390]" time="0.322"><properties><property name="score" value="1.0769058" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603252 [1239] (title: Harnessing AI f) is a human-generated sample, misclassified as AI-generated with confidence 1.0769058 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603252 [1239] (title: Harnessing AI f) is a human-generated sample, misclassified as AI-generated with confidence 1.0769058
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i391]" time="0.275"><properties><property name="score" value="0.05941246" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i392]" time="0.314"><properties><property name="score" value="0.48497707" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i393]" time="0.258"><properties><property name="score" value="0.58859426" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i394]" time="0.284"><properties><property name="score" value="0.4322159" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603261 [1054] (title: Content-Based E) is a human-generated sample, misclassified as AI-generated with confidence 0.4322159 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603261 [1054] (title: Content-Based E) is a human-generated sample, misclassified as AI-generated with confidence 0.4322159
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i395]" time="0.291"><properties><property name="score" value="0.7725294" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603262 [1229] (title: Improved Image ) is a human-generated sample, misclassified as AI-generated with confidence 0.7725294 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603262 [1229] (title: Improved Image ) is a human-generated sample, misclassified as AI-generated with confidence 0.7725294
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i396]" time="0.290"><properties><property name="score" value="0.56959724" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603265 [1147] (title: SC-Conv: Sparse) is a human-generated sample, misclassified as AI-generated with confidence 0.56959724 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603265 [1147] (title: SC-Conv: Sparse) is a human-generated sample, misclassified as AI-generated with confidence 0.56959724
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i397]" time="0.273"><properties><property name="score" value="0.81946015" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603266 [1010] (title: Deep Reinforcem) is a human-generated sample, misclassified as AI-generated with confidence 0.81946015 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603266 [1010] (title: Deep Reinforcem) is a human-generated sample, misclassified as AI-generated with confidence 0.81946015
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i398]" time="0.295"><properties><property name="score" value="0.23177528" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i399]" time="0.334"><properties><property name="score" value="1.1260828" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603272 [1166] (title: NR-GVQM: A No R) is a human-generated sample, misclassified as AI-generated with confidence 1.1260828 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603272 [1166] (title: NR-GVQM: A No R) is a human-generated sample, misclassified as AI-generated with confidence 1.1260828
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i400]" time="0.342"><properties><property name="score" value="1.7353963" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603275 [1623] (title: Audio-Visual Em) is a human-generated sample, misclassified as AI-generated with confidence 1.7353963 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603275 [1623] (title: Audio-Visual Em) is a human-generated sample, misclassified as AI-generated with confidence 1.7353963
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i401]" time="0.347"><properties><property name="score" value="0.0" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i402]" time="0.318"><properties><property name="score" value="0.12415707" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i403]" time="0.278"><properties><property name="score" value="0.15428218" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603293 [1055] (title: IceBreaker: Sol) is a human-generated sample, misclassified as AI-generated with confidence 0.15428218 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603293 [1055] (title: IceBreaker: Sol) is a human-generated sample, misclassified as AI-generated with confidence 0.15428218
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i404]" time="0.285"><properties><property name="score" value="1.2270172" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603294 [1108] (title: Towards Improve) is a human-generated sample, misclassified as AI-generated with confidence 1.2270172 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603294 [1108] (title: Towards Improve) is a human-generated sample, misclassified as AI-generated with confidence 1.2270172
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i405]" time="0.322"><properties><property name="score" value="0.81932145" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603296 [1633] (title: Supporting Know) is a human-generated sample, misclassified as AI-generated with confidence 0.81932145 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603296 [1633] (title: Supporting Know) is a human-generated sample, misclassified as AI-generated with confidence 0.81932145
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i406]" time="0.345"><properties><property name="score" value="0.6997523" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i407]" time="0.310"><properties><property name="score" value="0.18328282" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i408]" time="0.273"><properties><property name="score" value="0.85832816" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603305 [1348] (title: Discriminative ) is a human-generated sample, misclassified as AI-generated with confidence 0.85832816 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603305 [1348] (title: Discriminative ) is a human-generated sample, misclassified as AI-generated with confidence 0.85832816
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i409]" time="0.311"><properties><property name="score" value="1.1481842" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i410]" time="0.270"><properties><property name="score" value="1.5850618" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i411]" time="0.283"><properties><property name="score" value="0.120818846" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603319 [1935] (title: Cluster-Based A) is a human-generated sample, misclassified as AI-generated with confidence 0.12081885 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603319 [1935] (title: Cluster-Based A) is a human-generated sample, misclassified as AI-generated with confidence 0.12081885
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i412]" time="0.281"><properties><property name="score" value="0.268319" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i413]" time="0.293"><properties><property name="score" value="0.3582928" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603326 [1146] (title: A Method Using ) is a human-generated sample, misclassified as AI-generated with confidence 0.3582928 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603326 [1146] (title: A Method Using ) is a human-generated sample, misclassified as AI-generated with confidence 0.3582928
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i414]" time="0.277"><properties><property name="score" value="0.24435355" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603328 [1048] (title: An Age-State-De) is a human-generated sample, misclassified as AI-generated with confidence 0.24435355 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603328 [1048] (title: An Age-State-De) is a human-generated sample, misclassified as AI-generated with confidence 0.24435355
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i415]" time="0.281"><properties><property name="score" value="0.24652527" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603329 [1756] (title: The Security An) is a human-generated sample, misclassified as AI-generated with confidence 0.24652527 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603329 [1756] (title: The Security An) is a human-generated sample, misclassified as AI-generated with confidence 0.24652527
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i416]" time="0.296"><properties><property name="score" value="0.63795966" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i417]" time="0.287"><properties><property name="score" value="0.20084405" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i418]" time="0.292"><properties><property name="score" value="0.085533984" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603339 [1151] (title: An Integrated M) is a human-generated sample, misclassified as AI-generated with confidence 0.08553398 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603339 [1151] (title: An Integrated M) is a human-generated sample, misclassified as AI-generated with confidence 0.08553398
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i419]" time="0.324"><properties><property name="score" value="0.19474372" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603340 [1234] (title: Research on the) is a human-generated sample, misclassified as AI-generated with confidence 0.19474372 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603340 [1234] (title: Research on the) is a human-generated sample, misclassified as AI-generated with confidence 0.19474372
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i420]" time="0.338"><properties><property name="score" value="0.18892244" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603342 [1375] (title: An Improved Bin) is a human-generated sample, misclassified as AI-generated with confidence 0.18892244 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603342 [1375] (title: An Improved Bin) is a human-generated sample, misclassified as AI-generated with confidence 0.18892244
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i421]" time="0.395"><properties><property name="score" value="0.5503139" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603350 [1527] (title: Modeling Resear) is a human-generated sample, misclassified as AI-generated with confidence 0.5503139 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603350 [1527] (title: Modeling Resear) is a human-generated sample, misclassified as AI-generated with confidence 0.5503139
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i422]" time="0.296"><properties><property name="score" value="0.7262619" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603351 [1156] (title: Real-Time Bayes) is a human-generated sample, misclassified as AI-generated with confidence 0.7262619 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603351 [1156] (title: Real-Time Bayes) is a human-generated sample, misclassified as AI-generated with confidence 0.7262619
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i423]" time="0.301"><properties><property name="score" value="0.31476718" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i424]" time="0.380"><properties><property name="score" value="0.6605566" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i425]" time="0.343"><properties><property name="score" value="1.2120488" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i426]" time="0.324"><properties><property name="score" value="0.84021026" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603371 [1342] (title: Fault Detection) is a human-generated sample, misclassified as AI-generated with confidence 0.84021026 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603371 [1342] (title: Fault Detection) is a human-generated sample, misclassified as AI-generated with confidence 0.84021026
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i427]" time="0.306"><properties><property name="score" value="0.065163076" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603374 [1201] (title: Research of Pro) is a human-generated sample, misclassified as AI-generated with confidence 0.06516308 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603374 [1201] (title: Research of Pro) is a human-generated sample, misclassified as AI-generated with confidence 0.06516308
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i428]" time="0.361"><properties><property name="score" value="0.57460904" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603375 [1669] (title: Bearing Fault D) is a human-generated sample, misclassified as AI-generated with confidence 0.57460904 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603375 [1669] (title: Bearing Fault D) is a human-generated sample, misclassified as AI-generated with confidence 0.57460904
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i429]" time="0.332"><properties><property name="score" value="0.21535198" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603379 [1047] (title: A Health Manage) is a human-generated sample, misclassified as AI-generated with confidence 0.21535198 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603379 [1047] (title: A Health Manage) is a human-generated sample, misclassified as AI-generated with confidence 0.21535198
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i430]" time="0.361"><properties><property name="score" value="0.29825673" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i431]" time="0.321"><properties><property name="score" value="0.7315494" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603395 [1141] (title: Remaining Usefu) is a human-generated sample, misclassified as AI-generated with confidence 0.7315494 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603395 [1141] (title: Remaining Usefu) is a human-generated sample, misclassified as AI-generated with confidence 0.7315494
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i432]" time="0.322"><properties><property name="score" value="1.5620341" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603398 [1406] (title: Diesel Engine F) is a human-generated sample, misclassified as AI-generated with confidence 1.5620341 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603398 [1406] (title: Diesel Engine F) is a human-generated sample, misclassified as AI-generated with confidence 1.5620341
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i433]" time="0.287"><properties><property name="score" value="0.20734212" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603401 [1015] (title: Analysis of Rad) is a human-generated sample, misclassified as AI-generated with confidence 0.20734212 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603401 [1015] (title: Analysis of Rad) is a human-generated sample, misclassified as AI-generated with confidence 0.20734212
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i434]" time="0.311"><properties><property name="score" value="0.33368665" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603403 [1034] (title: Remaining Usefu) is a human-generated sample, misclassified as AI-generated with confidence 0.33368665 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603403 [1034] (title: Remaining Usefu) is a human-generated sample, misclassified as AI-generated with confidence 0.33368665
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i435]" time="0.331"><properties><property name="score" value="0.25689632" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i436]" time="0.348"><properties><property name="score" value="0.34027347" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603412 [1049] (title: Fault Diagnosis) is a human-generated sample, misclassified as AI-generated with confidence 0.34027347 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603412 [1049] (title: Fault Diagnosis) is a human-generated sample, misclassified as AI-generated with confidence 0.34027347
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i437]" time="0.308"><properties><property name="score" value="0.41940176" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i438]" time="0.293"><properties><property name="score" value="0.14437178" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603426 [1172] (title: Lifetime Evalua) is a human-generated sample, misclassified as AI-generated with confidence 0.14437178 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603426 [1172] (title: Lifetime Evalua) is a human-generated sample, misclassified as AI-generated with confidence 0.14437178
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i439]" time="0.368"><properties><property name="score" value="0.19119836" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603428 [1035] (title: A Method of Cal) is a human-generated sample, misclassified as AI-generated with confidence 0.19119836 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603428 [1035] (title: A Method of Cal) is a human-generated sample, misclassified as AI-generated with confidence 0.19119836
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i440]" time="0.992"><properties><property name="score" value="0.3322717" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i441]" time="0.324"><properties><property name="score" value="0.56408405" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i442]" time="0.334"><properties><property name="score" value="1.7761954" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i443]" time="0.314"><properties><property name="score" value="0.11942653" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603447 [1093] (title: Bearing Feature) is a human-generated sample, misclassified as AI-generated with confidence 0.11942653 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603447 [1093] (title: Bearing Feature) is a human-generated sample, misclassified as AI-generated with confidence 0.11942653
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i444]" time="0.285"><properties><property name="score" value="0.1777839" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603448 [1074] (title: Ball Screw Stab) is a human-generated sample, misclassified as AI-generated with confidence 0.1777839 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603448 [1074] (title: Ball Screw Stab) is a human-generated sample, misclassified as AI-generated with confidence 0.1777839
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i445]" time="0.444"><properties><property name="score" value="0.2083397" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603465 [1214] (title: Root Cause Iden) is a human-generated sample, misclassified as AI-generated with confidence 0.2083397 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603465 [1214] (title: Root Cause Iden) is a human-generated sample, misclassified as AI-generated with confidence 0.2083397
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i446]" time="0.298"><properties><property name="score" value="0.7210044" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603469 [1177] (title: Remaining Usefu) is a human-generated sample, misclassified as AI-generated with confidence 0.7210044 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603469 [1177] (title: Remaining Usefu) is a human-generated sample, misclassified as AI-generated with confidence 0.7210044
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i447]" time="0.354"><properties><property name="score" value="1.1229074" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i448]" time="0.363"><properties><property name="score" value="0.15886872" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i449]" time="0.373"><properties><property name="score" value="1.1011517" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i450]" time="0.399"><properties><property name="score" value="0.19128208" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603490 [1246] (title: Unsupervised Ge) is a human-generated sample, misclassified as AI-generated with confidence 0.19128208 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603490 [1246] (title: Unsupervised Ge) is a human-generated sample, misclassified as AI-generated with confidence 0.19128208
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i451]" time="0.343"><properties><property name="score" value="0.3905475" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603491 [1203] (title: Analyzing Accel) is a human-generated sample, misclassified as AI-generated with confidence 0.3905475 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603491 [1203] (title: Analyzing Accel) is a human-generated sample, misclassified as AI-generated with confidence 0.3905475
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i452]" time="0.404"><properties><property name="score" value="0.2846676" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603493 [1088] (title: PSO Optimized A) is a human-generated sample, misclassified as AI-generated with confidence 0.2846676 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603493 [1088] (title: PSO Optimized A) is a human-generated sample, misclassified as AI-generated with confidence 0.2846676
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i453]" time="0.535"><properties><property name="score" value="0.34682313" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i454]" time="0.377"><properties><property name="score" value="0.17641883" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i455]" time="0.382"><properties><property name="score" value="0.5276804" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603525 [1089] (title: Bearing Fault D) is a human-generated sample, misclassified as AI-generated with confidence 0.5276804 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603525 [1089] (title: Bearing Fault D) is a human-generated sample, misclassified as AI-generated with confidence 0.5276804
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i456]" time="0.562"><properties><property name="score" value="0.81658703" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i457]" time="0.425"><properties><property name="score" value="0.4183309" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i458]" time="0.348"><properties><property name="score" value="0.19970539" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603532 [2256] (title: Analyzing Data ) is a human-generated sample, misclassified as AI-generated with confidence 0.19970539 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603532 [2256] (title: Analyzing Data ) is a human-generated sample, misclassified as AI-generated with confidence 0.19970539
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i459]" time="0.355"><properties><property name="score" value="0.6716736" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i460]" time="0.359"><properties><property name="score" value="0.27902123" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603555 [1417] (title: Using Hybrid Se) is a human-generated sample, misclassified as AI-generated with confidence 0.27902123 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603555 [1417] (title: Using Hybrid Se) is a human-generated sample, misclassified as AI-generated with confidence 0.27902123
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i461]" time="0.334"><properties><property name="score" value="0.40556884" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i462]" time="0.351"><properties><property name="score" value="0.3608431" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603582 [1017] (title: Evolutionary Al) is a human-generated sample, misclassified as AI-generated with confidence 0.3608431 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603582 [1017] (title: Evolutionary Al) is a human-generated sample, misclassified as AI-generated with confidence 0.3608431
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i463]" time="0.384"><properties><property name="score" value="0.40178844" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i464]" time="0.322"><properties><property name="score" value="0.12511437" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603589 [1262] (title: Application of ) is a human-generated sample, misclassified as AI-generated with confidence 0.12511437 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603589 [1262] (title: Application of ) is a human-generated sample, misclassified as AI-generated with confidence 0.12511437
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i465]" time="0.317"><properties><property name="score" value="0.08165612" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603595 [1434] (title: Modeling Identi) is a human-generated sample, misclassified as AI-generated with confidence 0.08165612 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603595 [1434] (title: Modeling Identi) is a human-generated sample, misclassified as AI-generated with confidence 0.08165612
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i466]" time="0.337"><properties><property name="score" value="0.08676278" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i467]" time="0.368"><properties><property name="score" value="0.87034065" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603612 [1360] (title: Continuous and ) is a human-generated sample, misclassified as AI-generated with confidence 0.87034065 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603612 [1360] (title: Continuous and ) is a human-generated sample, misclassified as AI-generated with confidence 0.87034065
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i468]" time="0.299"><properties><property name="score" value="0.06753396" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i469]" time="0.308"><properties><property name="score" value="0.3690975" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603627 [1115] (title: Cloudlet-based ) is a human-generated sample, misclassified as AI-generated with confidence 0.3690975 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603627 [1115] (title: Cloudlet-based ) is a human-generated sample, misclassified as AI-generated with confidence 0.3690975
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i470]" time="0.285"><properties><property name="score" value="0.13855836" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i471]" time="0.305"><properties><property name="score" value="0.4037212" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603638 [1404] (title: Efficacy Studie) is a human-generated sample, misclassified as AI-generated with confidence 0.4037212 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603638 [1404] (title: Efficacy Studie) is a human-generated sample, misclassified as AI-generated with confidence 0.4037212
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i472]" time="0.423"><properties><property name="score" value="1.0713959" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i473]" time="0.307"><properties><property name="score" value="0.6983126" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603663 [1025] (title: Towards the Dis) is a human-generated sample, misclassified as AI-generated with confidence 0.6983126 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603663 [1025] (title: Towards the Dis) is a human-generated sample, misclassified as AI-generated with confidence 0.6983126
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i474]" time="0.274"><properties><property name="score" value="0.21841635" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i475]" time="0.276"><properties><property name="score" value="0.38667572" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603676 [1269] (title: Radio Source Lo) is a human-generated sample, misclassified as AI-generated with confidence 0.38667572 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603676 [1269] (title: Radio Source Lo) is a human-generated sample, misclassified as AI-generated with confidence 0.38667572
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i476]" time="0.284"><properties><property name="score" value="0.18482767" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603689 [1050] (title: Cellular Automa) is a human-generated sample, misclassified as AI-generated with confidence 0.18482767 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603689 [1050] (title: Cellular Automa) is a human-generated sample, misclassified as AI-generated with confidence 0.18482767
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i477]" time="0.271"><properties><property name="score" value="1.219678" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603700 [1284] (title: Efficient Vehic) is a human-generated sample, misclassified as AI-generated with confidence 1.219678 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603700 [1284] (title: Efficient Vehic) is a human-generated sample, misclassified as AI-generated with confidence 1.219678
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i478]" time="0.315"><properties><property name="score" value="0.22190085" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i479]" time="0.312"><properties><property name="score" value="0.39380717" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i480]" time="0.304"><properties><property name="score" value="0.95304954" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603727 [1603] (title: MOCA: Multi-Obj) is a human-generated sample, misclassified as AI-generated with confidence 0.95304954 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603727 [1603] (title: MOCA: Multi-Obj) is a human-generated sample, misclassified as AI-generated with confidence 0.95304954
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i481]" time="0.285"><properties><property name="score" value="0.1691178" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603728 [1406] (title: Insulator Detec) is a human-generated sample, misclassified as AI-generated with confidence 0.1691178 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603728 [1406] (title: Insulator Detec) is a human-generated sample, misclassified as AI-generated with confidence 0.1691178
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i482]" time="0.285"><properties><property name="score" value="0.46825743" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603733 [1787] (title: Device-to-Devic) is a human-generated sample, misclassified as AI-generated with confidence 0.46825743 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603733 [1787] (title: Device-to-Devic) is a human-generated sample, misclassified as AI-generated with confidence 0.46825743
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i483]" time="0.309"><properties><property name="score" value="0.17104077" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i484]" time="0.293"><properties><property name="score" value="0.89623576" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i485]" time="0.290"><properties><property name="score" value="0.562671" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603743 [1882] (title: Code-Partitioni) is a human-generated sample, misclassified as AI-generated with confidence 0.562671 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603743 [1882] (title: Code-Partitioni) is a human-generated sample, misclassified as AI-generated with confidence 0.562671
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i486]" time="0.281"><properties><property name="score" value="0.8591834" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603746 [1235] (title: A Novel Approac) is a human-generated sample, misclassified as AI-generated with confidence 0.8591834 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603746 [1235] (title: A Novel Approac) is a human-generated sample, misclassified as AI-generated with confidence 0.8591834
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i487]" time="0.274"><properties><property name="score" value="0.5371795" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603748 [1178] (title: Lagrangian Rela) is a human-generated sample, misclassified as AI-generated with confidence 0.5371795 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603748 [1178] (title: Lagrangian Rela) is a human-generated sample, misclassified as AI-generated with confidence 0.5371795
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i488]" time="0.383"><properties><property name="score" value="0.1465381" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i489]" time="0.368"><properties><property name="score" value="1.5998156" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i490]" time="0.271"><properties><property name="score" value="0.2602087" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603753 [1281] (title: Machine-Learnin) is a human-generated sample, misclassified as AI-generated with confidence 0.2602087 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603753 [1281] (title: Machine-Learnin) is a human-generated sample, misclassified as AI-generated with confidence 0.2602087
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i491]" time="0.293"><properties><property name="score" value="0.31138113" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i492]" time="0.284"><properties><property name="score" value="0.33147827" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i493]" time="0.394"><properties><property name="score" value="0.1588785" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603773 [1069] (title: Single-Scatter ) is a human-generated sample, misclassified as AI-generated with confidence 0.1588785 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603773 [1069] (title: Single-Scatter ) is a human-generated sample, misclassified as AI-generated with confidence 0.1588785
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i494]" time="0.296"><properties><property name="score" value="0.11379843" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i495]" time="0.260"><properties><property name="score" value="0.0033419144" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i496]" time="0.303"><properties><property name="score" value="0.05971663" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603777 [1259] (title: Secure Communic) is a human-generated sample, misclassified as AI-generated with confidence 0.05971663 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603777 [1259] (title: Secure Communic) is a human-generated sample, misclassified as AI-generated with confidence 0.05971663
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i497]" time="0.301"><properties><property name="score" value="0.06977604" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i498]" time="0.282"><properties><property name="score" value="0.297312" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_human_jsonl[i499]" time="0.315"><properties><property name="score" value="0.672789" /></properties><failure message="AssertionError: samples/ieee-init.jsonl:8603788 [1387] (title: An Ensemble Mod) is a human-generated sample, misclassified as AI-generated with confidence 0.672789 assert 'AI' == 'Human' - Human + AI">E AssertionError: samples/ieee-init.jsonl:8603788 [1387] (title: An Ensemble Mod) is a human-generated sample, misclassified as AI-generated with confidence 0.672789
|
||
assert 'AI' == 'Human'
|
||
- Human
|
||
+ AI</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i0]" time="0.260"><properties><property name="score" value="0.090211734" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i1]" time="0.311"><properties><property name="score" value="0.28528655" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i2]" time="0.275"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600029 (title: A Social Bots Detection Model Based on Deep Learni) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600029 (title: A Social Bots Detection Model Based on Deep Learni) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i3]" time="0.284"><properties><property name="score" value="0.133518" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i4]" time="0.307"><properties><property name="score" value="0.07625148" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i5]" time="0.290"><properties><property name="score" value="0.036626298" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i6]" time="0.400"><properties><property name="score" value="0.6063074" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i7]" time="0.319"><properties><property name="score" value="0.05233661" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i8]" time="0.318"><properties><property name="score" value="0.06810811" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i9]" time="0.289"><properties><property name="score" value="1.1920365" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600079 (title: Noise Suppression Threshold Channel Estimation Met) is an LLM-generated sample, misclassified as human-generated with confidence 1.1920365 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600079 (title: Noise Suppression Threshold Channel Estimation Met) is an LLM-generated sample, misclassified as human-generated with confidence 1.1920365
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i10]" time="0.293"><properties><property name="score" value="0.10289643" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i11]" time="0.285"><properties><property name="score" value="0.18938558" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i12]" time="0.310"><properties><property name="score" value="0.14141151" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i13]" time="0.419"><properties><property name="score" value="0.19799438" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i14]" time="0.344"><properties><property name="score" value="0.021403741" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i15]" time="0.300"><properties><property name="score" value="0.036574733" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i16]" time="0.317"><properties><property name="score" value="0.058643658" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i17]" time="0.263"><properties><property name="score" value="0.04771511" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i18]" time="0.284"><properties><property name="score" value="0.053263076" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i19]" time="0.296"><properties><property name="score" value="0.1030786" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i20]" time="0.290"><properties><property name="score" value="0.062861435" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i21]" time="0.305"><properties><property name="score" value="0.0726901" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i22]" time="0.287"><properties><property name="score" value="0.13071105" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i23]" time="0.286"><properties><property name="score" value="0.088205025" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i24]" time="0.273"><properties><property name="score" value="0.0076182648" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i25]" time="0.278"><properties><property name="score" value="0.066820376" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i26]" time="0.293"><properties><property name="score" value="2.7712986" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600156 (title: A Novel Clustering Algorithm Based on Mobility for) is an LLM-generated sample, misclassified as human-generated with confidence 2.7712986 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600156 (title: A Novel Clustering Algorithm Based on Mobility for) is an LLM-generated sample, misclassified as human-generated with confidence 2.7712986
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i27]" time="0.303"><properties><property name="score" value="0.21589728" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i28]" time="0.454"><properties><property name="score" value="2.2497706" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600165 (title: Adaptive Unequal Clustering Using an Improved LEAC) is an LLM-generated sample, misclassified as human-generated with confidence 2.2497706 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600165 (title: Adaptive Unequal Clustering Using an Improved LEAC) is an LLM-generated sample, misclassified as human-generated with confidence 2.2497706
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i29]" time="0.264"><properties><property name="score" value="0.04254268" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i30]" time="0.307"><properties><property name="score" value="0.060428448" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i31]" time="0.269"><properties><property name="score" value="0.06297493" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i32]" time="0.310"><properties><property name="score" value="0.080222614" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i33]" time="0.293"><properties><property name="score" value="0.04227254" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i34]" time="0.309"><properties><property name="score" value="0.029109733" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i35]" time="0.290"><properties><property name="score" value="2.1313663" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600201 (title: Control and Management of Optical Networks Using O) is an LLM-generated sample, misclassified as human-generated with confidence 2.1313663 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600201 (title: Control and Management of Optical Networks Using O) is an LLM-generated sample, misclassified as human-generated with confidence 2.1313663
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i36]" time="0.266"><properties><property name="score" value="0.05868203" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i37]" time="0.338"><properties><property name="score" value="2.334294" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600206 (title: A 3D Placement of Unmanned Aerial Vehicle Base Sta) is an LLM-generated sample, misclassified as human-generated with confidence 2.334294 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600206 (title: A 3D Placement of Unmanned Aerial Vehicle Base Sta) is an LLM-generated sample, misclassified as human-generated with confidence 2.334294
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i38]" time="0.283"><properties><property name="score" value="0.0138093745" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i39]" time="0.310"><properties><property name="score" value="0.008376198" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i40]" time="0.288"><properties><property name="score" value="0.16033302" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i41]" time="0.309"><properties><property name="score" value="0.01073959" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i42]" time="0.286"><properties><property name="score" value="0.21559614" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i43]" time="0.280"><properties><property name="score" value="0.15879019" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i44]" time="0.307"><properties><property name="score" value="0.012063282" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i45]" time="0.296"><properties><property name="score" value="0.032347564" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i46]" time="0.291"><properties><property name="score" value="0.14882934" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i47]" time="0.616"><properties><property name="score" value="0.13193925" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i48]" time="0.526"><properties><property name="score" value="0.10867144" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i49]" time="0.526"><properties><property name="score" value="0.3135334" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i50]" time="0.566"><properties><property name="score" value="0.01828571" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i51]" time="0.264"><properties><property name="score" value="0.01108168" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i52]" time="0.279"><properties><property name="score" value="0.06672581" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i53]" time="0.270"><properties><property name="score" value="0.13175191" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i54]" time="0.270"><properties><property name="score" value="0.08647554" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i55]" time="0.305"><properties><property name="score" value="0.14347906" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i56]" time="0.274"><properties><property name="score" value="0.28466627" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i57]" time="0.336"><properties><property name="score" value="0.11394291" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i58]" time="0.292"><properties><property name="score" value="0.015549793" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i59]" time="0.337"><properties><property name="score" value="0.08872805" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i60]" time="0.273"><properties><property name="score" value="0.13110572" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i61]" time="1.300"><properties><property name="score" value="0.06832469" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i62]" time="0.278"><properties><property name="score" value="0.08614676" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i63]" time="0.316"><properties><property name="score" value="0.048655037" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i64]" time="0.273"><properties><property name="score" value="0.23620933" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i65]" time="0.390"><properties><property name="score" value="0.12659243" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i66]" time="0.321"><properties><property name="score" value="0.03232694" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i67]" time="0.270"><properties><property name="score" value="1.3562062" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600438 (title: The Research of Photoplethysmography Morphology: D) is an LLM-generated sample, misclassified as human-generated with confidence 1.3562062 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600438 (title: The Research of Photoplethysmography Morphology: D) is an LLM-generated sample, misclassified as human-generated with confidence 1.3562062
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i68]" time="0.282"><properties><property name="score" value="0.12522542" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i69]" time="0.416"><properties><property name="score" value="0.069932766" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i70]" time="0.302"><properties><property name="score" value="0.15983698" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i71]" time="0.296"><properties><property name="score" value="0.06170303" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i72]" time="0.288"><properties><property name="score" value="0.12040293" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i73]" time="0.353"><properties><property name="score" value="0.1405529" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i74]" time="0.292"><properties><property name="score" value="0.03768289" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i75]" time="0.323"><properties><property name="score" value="0.09990712" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i76]" time="0.341"><properties><property name="score" value="1.9903619" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600475 (title: A Cascade Calibration of Near-Field Source Gain an) is an LLM-generated sample, misclassified as human-generated with confidence 1.9903619 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600475 (title: A Cascade Calibration of Near-Field Source Gain an) is an LLM-generated sample, misclassified as human-generated with confidence 1.9903619
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i77]" time="0.428"><properties><property name="score" value="0.04462454" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i78]" time="0.524"><properties><property name="score" value="0.24452426" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i79]" time="0.525"><properties><property name="score" value="0.16232812" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i80]" time="0.454"><properties><property name="score" value="0.07012992" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i81]" time="0.393"><properties><property name="score" value="0.4714883" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i82]" time="0.379"><properties><property name="score" value="0.14616378" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i83]" time="0.394"><properties><property name="score" value="0.04014519" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i84]" time="0.452"><properties><property name="score" value="0.42691174" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i85]" time="0.473"><properties><property name="score" value="0.40834233" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600535 (title: Text Recognition from Silent Lip Movement Video) is an LLM-generated sample, misclassified as human-generated with confidence 0.40834233 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600535 (title: Text Recognition from Silent Lip Movement Video) is an LLM-generated sample, misclassified as human-generated with confidence 0.40834233
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i86]" time="0.476"><properties><property name="score" value="2.4192963" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600536 (title: Convolution Neural Network based Transfer Learning) is an LLM-generated sample, misclassified as human-generated with confidence 2.4192963 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600536 (title: Convolution Neural Network based Transfer Learning) is an LLM-generated sample, misclassified as human-generated with confidence 2.4192963
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i87]" time="0.418"><properties><property name="score" value="0.05943314" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i88]" time="0.363"><properties><property name="score" value="0.051168747" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i89]" time="0.391"><properties><property name="score" value="0.05995342" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i90]" time="0.357"><properties><property name="score" value="0.114430726" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i91]" time="0.322"><properties><property name="score" value="0.046675555" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i92]" time="0.519"><properties><property name="score" value="0.3890741" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i93]" time="0.329"><properties><property name="score" value="0.06891558" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i94]" time="0.389"><properties><property name="score" value="0.024347702" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i95]" time="0.318"><properties><property name="score" value="0.14801256" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i96]" time="0.346"><properties><property name="score" value="1.6076994" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600733 (title: An Outlier-Insensitive Unmixing Algorithm With Spa) is an LLM-generated sample, misclassified as human-generated with confidence 1.6076994 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600733 (title: An Outlier-Insensitive Unmixing Algorithm With Spa) is an LLM-generated sample, misclassified as human-generated with confidence 1.6076994
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i97]" time="0.336"><properties><property name="score" value="1.7855073" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600737 (title: Disturbance Observer-Based Fault-Tolerant Adaptive) is an LLM-generated sample, misclassified as human-generated with confidence 1.7855073 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600737 (title: Disturbance Observer-Based Fault-Tolerant Adaptive) is an LLM-generated sample, misclassified as human-generated with confidence 1.7855073
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i98]" time="0.546"><properties><property name="score" value="0.0748969" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i99]" time="0.597"><properties><property name="score" value="0.011438838" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i100]" time="0.718"><properties><property name="score" value="0.04975726" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i101]" time="0.693"><properties><property name="score" value="0.12844138" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i102]" time="0.481"><properties><property name="score" value="0.011780686" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i103]" time="0.501"><properties><property name="score" value="0.030771146" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i104]" time="0.565"><properties><property name="score" value="0.052357208" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i105]" time="0.487"><properties><property name="score" value="0.024467962" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i106]" time="0.545"><properties><property name="score" value="0.08010805" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i107]" time="0.373"><properties><property name="score" value="0.09998088" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i108]" time="0.390"><properties><property name="score" value="0.05732697" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i109]" time="0.427"><properties><property name="score" value="0.1265164" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i110]" time="0.362"><properties><property name="score" value="0.13146411" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i111]" time="0.323"><properties><property name="score" value="0.12217288" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i112]" time="0.291"><properties><property name="score" value="3.3997178" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600860 (title: The Industrial IoT for Nusantara) is an LLM-generated sample, misclassified as human-generated with confidence 3.3997178 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600860 (title: The Industrial IoT for Nusantara) is an LLM-generated sample, misclassified as human-generated with confidence 3.3997178
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i113]" time="0.296"><properties><property name="score" value="0.25602257" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i114]" time="0.311"><properties><property name="score" value="0.12057573" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i115]" time="0.343"><properties><property name="score" value="0.029736398" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i116]" time="0.423"><properties><property name="score" value="0.021293953" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i117]" time="0.346"><properties><property name="score" value="0.03175015" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i118]" time="0.324"><properties><property name="score" value="0.025325658" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i119]" time="0.399"><properties><property name="score" value="3.0113003" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8600914 (title: Naive Bayes Multi-Label Classification Approach fo) is an LLM-generated sample, misclassified as human-generated with confidence 3.0113003 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8600914 (title: Naive Bayes Multi-Label Classification Approach fo) is an LLM-generated sample, misclassified as human-generated with confidence 3.0113003
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i120]" time="0.637"><properties><property name="score" value="0.116632834" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i121]" time="0.503"><properties><property name="score" value="0.19529781" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i122]" time="0.641"><properties><property name="score" value="0.07031906" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i123]" time="0.362"><properties><property name="score" value="0.1590439" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i124]" time="0.363"><properties><property name="score" value="0.09129255" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i125]" time="0.373"><properties><property name="score" value="0.032116607" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i126]" time="0.381"><properties><property name="score" value="0.04871893" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i127]" time="0.358"><properties><property name="score" value="0.020298148" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i128]" time="0.340"><properties><property name="score" value="0.07227118" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i129]" time="0.399"><properties><property name="score" value="0.22935216" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i130]" time="0.383"><properties><property name="score" value="0.05873329" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i131]" time="0.457"><properties><property name="score" value="0.039193686" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i132]" time="0.364"><properties><property name="score" value="0.091175534" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i133]" time="0.437"><properties><property name="score" value="0.21822555" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i134]" time="0.451"><properties><property name="score" value="0.25789317" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i135]" time="0.382"><properties><property name="score" value="0.29855722" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i136]" time="0.490"><properties><property name="score" value="1.9517579" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601191 (title: An Adaptive Collection Scheme-Based Matrix Complet) is an LLM-generated sample, misclassified as human-generated with confidence 1.9517579 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601191 (title: An Adaptive Collection Scheme-Based Matrix Complet) is an LLM-generated sample, misclassified as human-generated with confidence 1.9517579
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i137]" time="0.407"><properties><property name="score" value="2.7728763" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601196 (title: An Active Learning Method Based on Uncertainty and) is an LLM-generated sample, misclassified as human-generated with confidence 2.7728763 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601196 (title: An Active Learning Method Based on Uncertainty and) is an LLM-generated sample, misclassified as human-generated with confidence 2.7728763
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i138]" time="0.403"><properties><property name="score" value="0.07327804" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i139]" time="0.601"><properties><property name="score" value="0.25254866" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i140]" time="0.376"><properties><property name="score" value="0.02645426" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i141]" time="0.361"><properties><property name="score" value="1.50888" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601226 (title: Wireless Communication Technologies in Internet of) is an LLM-generated sample, misclassified as human-generated with confidence 1.50888 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601226 (title: Wireless Communication Technologies in Internet of) is an LLM-generated sample, misclassified as human-generated with confidence 1.50888
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i142]" time="0.385"><properties><property name="score" value="0.03742297" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i143]" time="0.371"><properties><property name="score" value="0.3079687" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i144]" time="0.353"><properties><property name="score" value="0.08651656" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i145]" time="0.369"><properties><property name="score" value="0.038426884" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i146]" time="0.423"><properties><property name="score" value="0.06406692" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i147]" time="0.416"><properties><property name="score" value="2.7092056" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601282 (title: A Hybrid Recommendation Technique for Big Data Sys) is an LLM-generated sample, misclassified as human-generated with confidence 2.7092056 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601282 (title: A Hybrid Recommendation Technique for Big Data Sys) is an LLM-generated sample, misclassified as human-generated with confidence 2.7092056
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i148]" time="0.340"><properties><property name="score" value="0.10603687" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i149]" time="0.350"><properties><property name="score" value="0.07197061" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i150]" time="0.327"><properties><property name="score" value="0.11354987" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i151]" time="0.339"><properties><property name="score" value="0.07221122" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i152]" time="2.803"><properties><property name="score" value="0.028709041" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i153]" time="0.349"><properties><property name="score" value="0.14652146" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i154]" time="0.296"><properties><property name="score" value="0.044412155" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i155]" time="0.319"><properties><property name="score" value="0.041726947" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i156]" time="0.286"><properties><property name="score" value="0.025605442" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i157]" time="0.328"><properties><property name="score" value="0.1287757" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i158]" time="0.302"><properties><property name="score" value="0.5043374" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i159]" time="0.324"><properties><property name="score" value="0.09534984" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i160]" time="0.407"><properties><property name="score" value="0.05258781" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i161]" time="0.344"><properties><property name="score" value="0.018274903" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i162]" time="0.404"><properties><property name="score" value="0.032118946" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i163]" time="0.443"><properties><property name="score" value="0.015069537" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i164]" time="0.382"><properties><property name="score" value="0.02756435" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i165]" time="0.442"><properties><property name="score" value="2.8686423" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601666 (title: A Fast Searching Method for Cascading Failure Patt) is an LLM-generated sample, misclassified as human-generated with confidence 2.8686423 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601666 (title: A Fast Searching Method for Cascading Failure Patt) is an LLM-generated sample, misclassified as human-generated with confidence 2.8686423
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i166]" time="0.373"><properties><property name="score" value="0.115207605" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i167]" time="2.729"><properties><property name="score" value="0.15032758" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i168]" time="0.356"><properties><property name="score" value="0.114365436" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i169]" time="0.294"><properties><property name="score" value="0.022845585" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i170]" time="0.293"><properties><property name="score" value="0.04611327" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i171]" time="0.293"><properties><property name="score" value="2.0177896" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601773 (title: Online Gaussian Process Regression for Short-term ) is an LLM-generated sample, misclassified as human-generated with confidence 2.0177896 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601773 (title: Online Gaussian Process Regression for Short-term ) is an LLM-generated sample, misclassified as human-generated with confidence 2.0177896
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i172]" time="0.297"><properties><property name="score" value="0.23002411" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i173]" time="0.360"><properties><property name="score" value="3.2721717" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8601830 (title: On-line management method of protection setting in) is an LLM-generated sample, misclassified as human-generated with confidence 3.2721717 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8601830 (title: On-line management method of protection setting in) is an LLM-generated sample, misclassified as human-generated with confidence 3.2721717
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i174]" time="0.297"><properties><property name="score" value="0.011774413" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i175]" time="0.347"><properties><property name="score" value="0.13986865" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i176]" time="0.322"><properties><property name="score" value="0.59945625" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i177]" time="0.347"><properties><property name="score" value="0.3488943" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i178]" time="0.326"><properties><property name="score" value="0.0672515" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i179]" time="0.331"><properties><property name="score" value="0.09055909" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i180]" time="0.321"><properties><property name="score" value="0.027622009" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i181]" time="0.390"><properties><property name="score" value="0.065135844" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i182]" time="0.315"><properties><property name="score" value="0.07900383" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i183]" time="0.275"><properties><property name="score" value="0.048710547" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i184]" time="0.407"><properties><property name="score" value="0.05616934" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i185]" time="0.312"><properties><property name="score" value="0.06242801" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i186]" time="0.292"><properties><property name="score" value="0.055681344" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i187]" time="0.269"><properties><property name="score" value="0.018701624" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i188]" time="0.284"><properties><property name="score" value="0.04614049" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i189]" time="0.301"><properties><property name="score" value="0.10277356" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i190]" time="0.328"><properties><property name="score" value="0.047525764" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i191]" time="0.881"><properties><property name="score" value="0.055367384" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i192]" time="0.261"><properties><property name="score" value="0.081840016" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i193]" time="0.285"><properties><property name="score" value="0.13227059" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i194]" time="0.330"><properties><property name="score" value="0.054222494" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i195]" time="0.356"><properties><property name="score" value="1.2793052" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8602223 (title: Partial Discharge Data Augmentation of High Voltag) is an LLM-generated sample, misclassified as human-generated with confidence 1.2793052 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8602223 (title: Partial Discharge Data Augmentation of High Voltag) is an LLM-generated sample, misclassified as human-generated with confidence 1.2793052
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i196]" time="0.279"><properties><property name="score" value="0.02331098" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i197]" time="0.294"><properties><property name="score" value="0.278207" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i198]" time="0.308"><properties><property name="score" value="0.100717805" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i199]" time="0.366"><properties><property name="score" value="0.011924173" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i200]" time="0.348"><properties><property name="score" value="0.15759277" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i201]" time="0.376"><properties><property name="score" value="0.4441974" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8602306 (title: Capacitor Voltage Balancing Control Algorithm for ) is an LLM-generated sample, misclassified as human-generated with confidence 0.4441974 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8602306 (title: Capacitor Voltage Balancing Control Algorithm for ) is an LLM-generated sample, misclassified as human-generated with confidence 0.4441974
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i202]" time="0.318"><properties><property name="score" value="0.25336763" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i203]" time="0.316"><properties><property name="score" value="0.049163043" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i204]" time="0.306"><properties><property name="score" value="0.2012002" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i205]" time="0.366"><properties><property name="score" value="0.14967453" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i206]" time="0.350"><properties><property name="score" value="0.07596443" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i207]" time="0.332"><properties><property name="score" value="0.071089014" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i208]" time="0.359"><properties><property name="score" value="1.9905794" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8602462 (title: Learning Dual Geometric Low-Rank Structure for Sem) is an LLM-generated sample, misclassified as human-generated with confidence 1.9905794 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8602462 (title: Learning Dual Geometric Low-Rank Structure for Sem) is an LLM-generated sample, misclassified as human-generated with confidence 1.9905794
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i209]" time="0.307"><properties><property name="score" value="0.11011729" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i210]" time="0.310"><properties><property name="score" value="0.114009775" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i211]" time="0.281"><properties><property name="score" value="0.04482917" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i212]" time="0.303"><properties><property name="score" value="0.06584619" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i213]" time="0.313"><properties><property name="score" value="0.057633214" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i214]" time="0.367"><properties><property name="score" value="0.057822652" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i215]" time="0.300"><properties><property name="score" value="0.039108083" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i216]" time="0.330"><properties><property name="score" value="0.016574945" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i217]" time="0.365"><properties><property name="score" value="0.07334994" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i218]" time="0.305"><properties><property name="score" value="0.10613741" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i219]" time="0.278"><properties><property name="score" value="1.0627639" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8602759 (title: A Large Scale FDTD Analysis of Propagation Charact) is an LLM-generated sample, misclassified as human-generated with confidence 1.0627639 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8602759 (title: A Large Scale FDTD Analysis of Propagation Charact) is an LLM-generated sample, misclassified as human-generated with confidence 1.0627639
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i220]" time="0.281"><properties><property name="score" value="0.01563667" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i221]" time="0.327"><properties><property name="score" value="0.04094665" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i222]" time="0.295"><properties><property name="score" value="0.012959981" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i223]" time="0.288"><properties><property name="score" value="0.096210726" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i224]" time="0.289"><properties><property name="score" value="0.042440314" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i225]" time="0.267"><properties><property name="score" value="0.013079303" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i226]" time="0.301"><properties><property name="score" value="0.09559503" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i227]" time="0.333"><properties><property name="score" value="0.3769115" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i228]" time="0.326"><properties><property name="score" value="0.013408964" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i229]" time="0.302"><properties><property name="score" value="0.009930542" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i230]" time="0.354"><properties><property name="score" value="1.6686984" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8602994 (title: Semantic-based Automated Reasoning for AWS Access ) is an LLM-generated sample, misclassified as human-generated with confidence 1.6686984 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8602994 (title: Semantic-based Automated Reasoning for AWS Access ) is an LLM-generated sample, misclassified as human-generated with confidence 1.6686984
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i231]" time="0.287"><properties><property name="score" value="0.014020974" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i232]" time="0.332"><properties><property name="score" value="2.4204814" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603148 (title: Hierarchical and Frequency-Aware Model Predictive ) is an LLM-generated sample, misclassified as human-generated with confidence 2.4204814 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603148 (title: Hierarchical and Frequency-Aware Model Predictive ) is an LLM-generated sample, misclassified as human-generated with confidence 2.4204814
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i233]" time="0.312"><properties><property name="score" value="0.09033275" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i234]" time="0.342"><properties><property name="score" value="0.31578642" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i235]" time="0.304"><properties><property name="score" value="0.06000855" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i236]" time="0.306"><properties><property name="score" value="0.049931437" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i237]" time="0.323"><properties><property name="score" value="0.03872777" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i238]" time="0.295"><properties><property name="score" value="0.1015962" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i239]" time="0.304"><properties><property name="score" value="0.051107142" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i240]" time="0.296"><properties><property name="score" value="0.02403341" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i241]" time="0.309"><properties><property name="score" value="0.10818882" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i242]" time="0.377"><properties><property name="score" value="0.027819939" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i243]" time="0.392"><properties><property name="score" value="0.12679945" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i244]" time="0.380"><properties><property name="score" value="0.0443258" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i245]" time="0.372"><properties><property name="score" value="1.1213791" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603251 (title: A Robust Iris Segmentation Using Fully Convolution) is an LLM-generated sample, misclassified as human-generated with confidence 1.1213791 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603251 (title: A Robust Iris Segmentation Using Fully Convolution) is an LLM-generated sample, misclassified as human-generated with confidence 1.1213791
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i246]" time="0.317"><properties><property name="score" value="0.097731926" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i247]" time="1.336"><properties><property name="score" value="0.029781535" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i248]" time="0.309"><properties><property name="score" value="0.079249755" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i249]" time="0.784"><properties><property name="score" value="0.10749825" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i250]" time="0.307"><properties><property name="score" value="0.31869283" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i251]" time="0.318"><properties><property name="score" value="2.7675912" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603298 (title: 3D Convolutional Network Based Foreground Feature ) is an LLM-generated sample, misclassified as human-generated with confidence 2.7675912 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603298 (title: 3D Convolutional Network Based Foreground Feature ) is an LLM-generated sample, misclassified as human-generated with confidence 2.7675912
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i252]" time="0.302"><properties><property name="score" value="0.13113637" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i253]" time="1.023"><properties><property name="score" value="0.26752803" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i254]" time="0.592"><properties><property name="score" value="0.16892675" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i255]" time="0.983"><properties><property name="score" value="0.2681036" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i256]" time="0.324"><properties><property name="score" value="0.046370275" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i257]" time="0.452"><properties><property name="score" value="0.024249928" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i258]" time="0.323"><properties><property name="score" value="0.13808587" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i259]" time="0.419"><properties><property name="score" value="0.21377407" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i260]" time="0.284"><properties><property name="score" value="0.08673124" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i261]" time="0.351"><properties><property name="score" value="0.22749494" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i262]" time="0.334"><properties><property name="score" value="0.04125519" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i263]" time="0.313"><properties><property name="score" value="0.12394486" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i264]" time="0.273"><properties><property name="score" value="0.19418031" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i265]" time="0.311"><properties><property name="score" value="0.32963425" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i266]" time="0.297"><properties><property name="score" value="0.116315074" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i267]" time="0.294"><properties><property name="score" value="0.009507186" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i268]" time="0.296"><properties><property name="score" value="0.042545483" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i269]" time="0.310"><properties><property name="score" value="0.110127605" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i270]" time="0.339"><properties><property name="score" value="0.29410145" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i271]" time="0.269"><properties><property name="score" value="0.08362499" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i272]" time="0.298"><properties><property name="score" value="0.17346571" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i273]" time="0.256"><properties><property name="score" value="0.07654073" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i274]" time="0.262"><properties><property name="score" value="0.17572041" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i275]" time="0.292"><properties><property name="score" value="0.4191994" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i276]" time="0.290"><properties><property name="score" value="0.20001827" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i277]" time="0.513"><properties><property name="score" value="2.2283437" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603496 (title: Reliability Analysis of Phased Mission System Base) is an LLM-generated sample, misclassified as human-generated with confidence 2.2283437 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603496 (title: Reliability Analysis of Phased Mission System Base) is an LLM-generated sample, misclassified as human-generated with confidence 2.2283437
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i278]" time="0.298"><properties><property name="score" value="0.12699915" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i279]" time="0.293"><properties><property name="score" value="0.08799971" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i280]" time="0.310"><properties><property name="score" value="0.3208963" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i281]" time="0.316"><properties><property name="score" value="2.128612" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603525 (title: Bearing Fault Diagnosis Using Hyper-Laplacian Prio) is an LLM-generated sample, misclassified as human-generated with confidence 2.128612 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603525 (title: Bearing Fault Diagnosis Using Hyper-Laplacian Prio) is an LLM-generated sample, misclassified as human-generated with confidence 2.128612
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i282]" time="0.310"><properties><property name="score" value="0.037009154" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i283]" time="0.357"><properties><property name="score" value="0.022666134" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i284]" time="0.307"><properties><property name="score" value="0.020451628" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i285]" time="0.293"><properties><property name="score" value="0.093562946" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i286]" time="0.294"><properties><property name="score" value="0.043310348" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i287]" time="0.303"><properties><property name="score" value="0.189619" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i288]" time="0.301"><properties><property name="score" value="0.07215081" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i289]" time="0.283"><properties><property name="score" value="0.043069866" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i290]" time="0.319"><properties><property name="score" value="0.061100736" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i291]" time="0.291"><properties><property name="score" value="0.05957206" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i292]" time="0.296"><properties><property name="score" value="0.015076797" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i293]" time="0.298"><properties><property name="score" value="0.03678422" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i294]" time="0.310"><properties><property name="score" value="0.04563914" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i295]" time="0.311"><properties><property name="score" value="2.1028109" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603669 (title: On the use of Wireless Sensor Networks in Preventa) is an LLM-generated sample, misclassified as human-generated with confidence 2.1028109 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603669 (title: On the use of Wireless Sensor Networks in Preventa) is an LLM-generated sample, misclassified as human-generated with confidence 2.1028109
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i296]" time="0.323"><properties><property name="score" value="0.12729643" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i297]" time="0.256"><properties><property name="score" value="0.04905956" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i298]" time="0.266"><properties><property name="score" value="0.08257611" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i299]" time="0.253"><properties><property name="score" value="0.034071784" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i300]" time="0.279"><properties><property name="score" value="0.05758479" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i301]" time="0.276"><properties><property name="score" value="0.040182725" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i302]" time="0.320"><properties><property name="score" value="0.07895423" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i303]" time="0.320"><properties><property name="score" value="0.64203274" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i304]" time="0.285"><properties><property name="score" value="0.120311104" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i305]" time="0.300"><properties><property name="score" value="0.1244352" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i306]" time="0.467"><properties><property name="score" value="0.41255608" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i307]" time="0.278"><properties><property name="score" value="0.073991664" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i308]" time="0.284"><properties><property name="score" value="0.12679641" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i309]" time="0.305"><properties><property name="score" value="0.14142202" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i310]" time="0.300"><properties><property name="score" value="0.06100259" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i311]" time="0.281"><properties><property name="score" value="1.97059" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8603816 (title: A Pareto-Based Estimation of Distribution Algorith) is an LLM-generated sample, misclassified as human-generated with confidence 1.97059 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8603816 (title: A Pareto-Based Estimation of Distribution Algorith) is an LLM-generated sample, misclassified as human-generated with confidence 1.97059
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i312]" time="0.248"><properties><property name="score" value="0.06750398" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i313]" time="0.273"><properties><property name="score" value="0.099134535" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i314]" time="0.256"><properties><property name="score" value="2.5454838" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604036 (title: Weld Bead Detection Based on 3D Geometric Features) is an LLM-generated sample, misclassified as human-generated with confidence 2.5454838 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604036 (title: Weld Bead Detection Based on 3D Geometric Features) is an LLM-generated sample, misclassified as human-generated with confidence 2.5454838
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i315]" time="0.286"><properties><property name="score" value="0.09593508" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i316]" time="0.282"><properties><property name="score" value="0.13270187" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i317]" time="0.354"><properties><property name="score" value="0.16357476" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i318]" time="0.448"><properties><property name="score" value="0.05444943" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i319]" time="0.363"><properties><property name="score" value="0.104827136" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i320]" time="0.309"><properties><property name="score" value="0.111550905" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i321]" time="0.292"><properties><property name="score" value="0.019963352" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i322]" time="0.350"><properties><property name="score" value="0.105608836" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i323]" time="0.276"><properties><property name="score" value="0.03983825" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i324]" time="0.508"><properties><property name="score" value="0.107724115" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i325]" time="0.353"><properties><property name="score" value="0.17143083" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i326]" time="0.363"><properties><property name="score" value="0.48273602" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i327]" time="0.353"><properties><property name="score" value="0.05444099" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i328]" time="0.331"><properties><property name="score" value="0.09871307" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i329]" time="0.322"><properties><property name="score" value="0.078128114" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i330]" time="0.333"><properties><property name="score" value="0.009756098" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i331]" time="0.358"><properties><property name="score" value="0.060313407" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i332]" time="0.491"><properties><property name="score" value="3.0095577" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604227 (title: Assessment of the Enterprise-University Interactio) is an LLM-generated sample, misclassified as human-generated with confidence 3.0095577 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604227 (title: Assessment of the Enterprise-University Interactio) is an LLM-generated sample, misclassified as human-generated with confidence 3.0095577
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i333]" time="0.654"><properties><property name="score" value="0.032094453" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i334]" time="0.653"><properties><property name="score" value="0.07927873" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i335]" time="0.444"><properties><property name="score" value="0.565185" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i336]" time="0.369"><properties><property name="score" value="0.007916493" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i337]" time="0.381"><properties><property name="score" value="0.057849117" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i338]" time="0.410"><properties><property name="score" value="0.10311289" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i339]" time="0.713"><properties><property name="score" value="0.020625146" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i340]" time="0.601"><properties><property name="score" value="0.018276786" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i341]" time="0.380"><properties><property name="score" value="0.05486674" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i342]" time="0.344"><properties><property name="score" value="0.011198368" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i343]" time="0.338"><properties><property name="score" value="0.16408797" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604306 (title: Data Mining of Wearable Devices Data) is an LLM-generated sample, misclassified as human-generated with confidence 0.16408797 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604306 (title: Data Mining of Wearable Devices Data) is an LLM-generated sample, misclassified as human-generated with confidence 0.16408797
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i344]" time="0.307"><properties><property name="score" value="0.024091477" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i345]" time="0.313"><properties><property name="score" value="0.044600293" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i346]" time="0.320"><properties><property name="score" value="0.047407076" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i347]" time="0.361"><properties><property name="score" value="0.064348355" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i348]" time="0.341"><properties><property name="score" value="0.055636168" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i349]" time="0.367"><properties><property name="score" value="0.060617976" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i350]" time="0.305"><properties><property name="score" value="1.0066643" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604490 (title: Autonomous Oil Spill Detection: Mission Planning f) is an LLM-generated sample, misclassified as human-generated with confidence 1.0066643 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604490 (title: Autonomous Oil Spill Detection: Mission Planning f) is an LLM-generated sample, misclassified as human-generated with confidence 1.0066643
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i351]" time="0.306"><properties><property name="score" value="2.2223895" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604534 (title: Nonsingular Sliding Mode Control and RBF Neural Ne) is an LLM-generated sample, misclassified as human-generated with confidence 2.2223895 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604534 (title: Nonsingular Sliding Mode Control and RBF Neural Ne) is an LLM-generated sample, misclassified as human-generated with confidence 2.2223895
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i352]" time="0.318"><properties><property name="score" value="0.031289563" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i353]" time="0.267"><properties><property name="score" value="0.12437317" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i354]" time="2.553"><properties><property name="score" value="0.05366059" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i355]" time="0.288"><properties><property name="score" value="1.423692" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604563 (title: Noncircularity-Exploitation to Design the Sparse A) is an LLM-generated sample, misclassified as human-generated with confidence 1.423692 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604563 (title: Noncircularity-Exploitation to Design the Sparse A) is an LLM-generated sample, misclassified as human-generated with confidence 1.423692
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i356]" time="0.281"><properties><property name="score" value="0.039563384" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i357]" time="0.248"><properties><property name="score" value="2.999791" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604614 (title: ELM and LOS Based Path Tracking for Autonomous Und) is an LLM-generated sample, misclassified as human-generated with confidence 2.999791 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604614 (title: ELM and LOS Based Path Tracking for Autonomous Und) is an LLM-generated sample, misclassified as human-generated with confidence 2.999791
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i358]" time="0.342"><properties><property name="score" value="1.8322308" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604616 (title: SAS Simulations with Procedural Texture and the Po) is an LLM-generated sample, misclassified as human-generated with confidence 1.8322308 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604616 (title: SAS Simulations with Procedural Texture and the Po) is an LLM-generated sample, misclassified as human-generated with confidence 1.8322308
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i359]" time="0.313"><properties><property name="score" value="0.092939846" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i360]" time="0.268"><properties><property name="score" value="0.086104535" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i361]" time="0.264"><properties><property name="score" value="0.018631725" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i362]" time="0.279"><properties><property name="score" value="2.4812694" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604685 (title: Mobile Acoustic Communications: Real Data Analysis) is an LLM-generated sample, misclassified as human-generated with confidence 2.4812694 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604685 (title: Mobile Acoustic Communications: Real Data Analysis) is an LLM-generated sample, misclassified as human-generated with confidence 2.4812694
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i363]" time="0.276"><properties><property name="score" value="1.5771414" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8604721 (title: Sparse Spatial Spectrum Estimation for Underwater ) is an LLM-generated sample, misclassified as human-generated with confidence 1.5771414 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8604721 (title: Sparse Spatial Spectrum Estimation for Underwater ) is an LLM-generated sample, misclassified as human-generated with confidence 1.5771414
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i364]" time="0.291"><properties><property name="score" value="0.17034376" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i365]" time="0.285"><properties><property name="score" value="0.22213873" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i366]" time="0.379"><properties><property name="score" value="0.33693242" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i367]" time="0.347"><properties><property name="score" value="0.1383137" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i368]" time="0.366"><properties><property name="score" value="0.32643172" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i369]" time="0.277"><properties><property name="score" value="0.015290299" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i370]" time="0.285"><properties><property name="score" value="1.5384" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8605769 (title: Realizing Edge Computing Connectivity with Open Vi) is an LLM-generated sample, misclassified as human-generated with confidence 1.5384 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8605769 (title: Realizing Edge Computing Connectivity with Open Vi) is an LLM-generated sample, misclassified as human-generated with confidence 1.5384
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i371]" time="0.312"><properties><property name="score" value="0.109747246" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i372]" time="0.329"><properties><property name="score" value="0.05875984" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i373]" time="0.423"><properties><property name="score" value="0.02364006" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i374]" time="0.371"><properties><property name="score" value="0.062972255" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i375]" time="0.393"><properties><property name="score" value="0.041658778" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i376]" time="0.419"><properties><property name="score" value="0.116857916" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i377]" time="0.346"><properties><property name="score" value="0.029910862" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i378]" time="0.320"><properties><property name="score" value="0.21223223" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i379]" time="0.331"><properties><property name="score" value="0.046925712" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i380]" time="0.382"><properties><property name="score" value="2.6774359" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8605798 (title: Towards Cloud Native Continuous Delivery: An Indus) is an LLM-generated sample, misclassified as human-generated with confidence 2.6774359 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8605798 (title: Towards Cloud Native Continuous Delivery: An Indus) is an LLM-generated sample, misclassified as human-generated with confidence 2.6774359
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i381]" time="0.369"><properties><property name="score" value="0.017240375" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i382]" time="0.340"><properties><property name="score" value="0.28965193" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i383]" time="0.405"><properties><property name="score" value="0.54527766" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i384]" time="0.287"><properties><property name="score" value="0.1465142" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i385]" time="0.395"><properties><property name="score" value="0.040516045" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i386]" time="0.365"><properties><property name="score" value="0.10683981" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i387]" time="0.349"><properties><property name="score" value="0.023415923" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i388]" time="0.353"><properties><property name="score" value="0.081245035" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i389]" time="0.322"><properties><property name="score" value="0.039558485" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i390]" time="0.308"><properties><property name="score" value="0.09076884" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i391]" time="0.317"><properties><property name="score" value="0.036818415" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i392]" time="0.311"><properties><property name="score" value="2.2064428" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8605995 (title: Detecting Social Bots on Twitter: A Literature Rev) is an LLM-generated sample, misclassified as human-generated with confidence 2.2064428 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8605995 (title: Detecting Social Bots on Twitter: A Literature Rev) is an LLM-generated sample, misclassified as human-generated with confidence 2.2064428
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i393]" time="0.296"><properties><property name="score" value="0.0452226" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i394]" time="0.345"><properties><property name="score" value="0.06985485" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i395]" time="0.283"><properties><property name="score" value="0.014197072" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i396]" time="0.273"><properties><property name="score" value="0.16475512" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i397]" time="0.308"><properties><property name="score" value="0.055200454" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i398]" time="0.380"><properties><property name="score" value="0.094054535" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i399]" time="0.272"><properties><property name="score" value="0.028562326" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i400]" time="0.287"><properties><property name="score" value="2.1563275" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606040 (title: Preemptive Diagnosis of Chronic Kidney Disease Usi) is an LLM-generated sample, misclassified as human-generated with confidence 2.1563275 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606040 (title: Preemptive Diagnosis of Chronic Kidney Disease Usi) is an LLM-generated sample, misclassified as human-generated with confidence 2.1563275
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i401]" time="0.357"><properties><property name="score" value="0.105365485" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i402]" time="0.400"><properties><property name="score" value="0.09533856" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i403]" time="0.423"><properties><property name="score" value="1.9353242" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606066 (title: Energy-Efficient Optimization for UAV-Aided Cellul) is an LLM-generated sample, misclassified as human-generated with confidence 1.9353242 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606066 (title: Energy-Efficient Optimization for UAV-Aided Cellul) is an LLM-generated sample, misclassified as human-generated with confidence 1.9353242
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i404]" time="0.349"><properties><property name="score" value="0.48377225" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i405]" time="0.314"><properties><property name="score" value="0.18628447" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i406]" time="0.368"><properties><property name="score" value="0.07926878" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i407]" time="0.260"><properties><property name="score" value="0.18412004" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i408]" time="0.295"><properties><property name="score" value="0.09437394" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i409]" time="1.252"><properties><property name="score" value="0.1791778" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i410]" time="0.323"><properties><property name="score" value="0.14025164" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i411]" time="0.287"><properties><property name="score" value="0.13159117" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i412]" time="0.282"><properties><property name="score" value="0.0095570125" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i413]" time="0.306"><properties><property name="score" value="0.07377335" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i414]" time="0.277"><properties><property name="score" value="1.7721443" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606185 (title: BLA: Blockchain-Assisted Lightweight Anonymous Aut) is an LLM-generated sample, misclassified as human-generated with confidence 1.7721443 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606185 (title: BLA: Blockchain-Assisted Lightweight Anonymous Aut) is an LLM-generated sample, misclassified as human-generated with confidence 1.7721443
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i415]" time="0.304"><properties><property name="score" value="1.6079619" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606211 (title: Dominant-Current Deep Learning Scheme for Electric) is an LLM-generated sample, misclassified as human-generated with confidence 1.6079619 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606211 (title: Dominant-Current Deep Learning Scheme for Electric) is an LLM-generated sample, misclassified as human-generated with confidence 1.6079619
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i416]" time="0.352"><properties><property name="score" value="2.4835758" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606229 (title: A Statistical Approach to Estimate Imbalance-Induc) is an LLM-generated sample, misclassified as human-generated with confidence 2.4835758 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606229 (title: A Statistical Approach to Estimate Imbalance-Induc) is an LLM-generated sample, misclassified as human-generated with confidence 2.4835758
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i417]" time="0.341"><properties><property name="score" value="1.9186052" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606230 (title: A Multi-User Mobile Computation Offloading and Tra) is an LLM-generated sample, misclassified as human-generated with confidence 1.9186052 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606230 (title: A Multi-User Mobile Computation Offloading and Tra) is an LLM-generated sample, misclassified as human-generated with confidence 1.9186052
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i418]" time="0.346"><properties><property name="score" value="0.04489756" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i419]" time="0.335"><properties><property name="score" value="0.27035204" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i420]" time="0.462"><properties><property name="score" value="0.030073067" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i421]" time="0.315"><properties><property name="score" value="0.11157777" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i422]" time="0.361"><properties><property name="score" value="0.021141384" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i423]" time="0.338"><properties><property name="score" value="0.38691002" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606278 (title: Inductive Validity Cores) is an LLM-generated sample, misclassified as human-generated with confidence 0.38691002 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606278 (title: Inductive Validity Cores) is an LLM-generated sample, misclassified as human-generated with confidence 0.38691002
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i424]" time="0.981"><properties><property name="score" value="0.032438066" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i425]" time="0.265"><properties><property name="score" value="0.043049082" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i426]" time="0.302"><properties><property name="score" value="2.1753507" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606339 (title: Prologue: AI&amp;I) is an LLM-generated sample, misclassified as human-generated with confidence 2.1753507 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606339 (title: Prologue: AI&amp;I) is an LLM-generated sample, misclassified as human-generated with confidence 2.1753507
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i427]" time="0.310"><properties><property name="score" value="0.0780462" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i428]" time="0.301"><properties><property name="score" value="0.020360742" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i429]" time="0.295"><properties><property name="score" value="0.033635814" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i430]" time="0.312"><properties><property name="score" value="0.08064928" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i431]" time="0.475"><properties><property name="score" value="0.19457412" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i432]" time="0.276"><properties><property name="score" value="0.09309258" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i433]" time="0.306"><properties><property name="score" value="0.022609983" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i434]" time="0.284"><properties><property name="score" value="0.034272537" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i435]" time="0.270"><properties><property name="score" value="0.15495013" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i436]" time="0.267"><properties><property name="score" value="0.6713899" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606551 (title: Remote Sensing Image Scene Classification Based on) is an LLM-generated sample, misclassified as human-generated with confidence 0.6713899 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606551 (title: Remote Sensing Image Scene Classification Based on) is an LLM-generated sample, misclassified as human-generated with confidence 0.6713899
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i437]" time="0.371"><properties><property name="score" value="0.034312326" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i438]" time="0.398"><properties><property name="score" value="0.019459153" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i439]" time="0.252"><properties><property name="score" value="2.1486135" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606662 (title: Projective Synchronization of Three Memristor Chao) is an LLM-generated sample, misclassified as human-generated with confidence 2.1486135 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606662 (title: Projective Synchronization of Three Memristor Chao) is an LLM-generated sample, misclassified as human-generated with confidence 2.1486135
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i440]" time="0.254"><properties><property name="score" value="0.014607717" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i441]" time="0.275"><properties><property name="score" value="0.34082052" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i442]" time="0.330"><properties><property name="score" value="0.24507877" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i443]" time="0.281"><properties><property name="score" value="0.31861144" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i444]" time="0.353"><properties><property name="score" value="0.12003706" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i445]" time="0.389"><properties><property name="score" value="0.3302171" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i446]" time="0.302"><properties><property name="score" value="0.013434094" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i447]" time="0.360"><properties><property name="score" value="0.025212998" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i448]" time="0.268"><properties><property name="score" value="0.12551117" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i449]" time="0.327"><properties><property name="score" value="0.17797503" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i450]" time="0.261"><properties><property name="score" value="0.8125815" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606802 (title: Joint Image Deblurring and Binarization for Licens) is an LLM-generated sample, misclassified as human-generated with confidence 0.8125815 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606802 (title: Joint Image Deblurring and Binarization for Licens) is an LLM-generated sample, misclassified as human-generated with confidence 0.8125815
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i451]" time="0.310"><properties><property name="score" value="0.488762" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i452]" time="0.380"><properties><property name="score" value="0.36045787" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i453]" time="0.339"><properties><property name="score" value="2.4097466" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606824 (title: Relation Extraction in Vietnamese Text via Piecewi) is an LLM-generated sample, misclassified as human-generated with confidence 2.4097466 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606824 (title: Relation Extraction in Vietnamese Text via Piecewi) is an LLM-generated sample, misclassified as human-generated with confidence 2.4097466
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i454]" time="0.270"><properties><property name="score" value="0.06148743" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i455]" time="0.298"><properties><property name="score" value="0.21774882" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i456]" time="0.309"><properties><property name="score" value="0.011861925" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i457]" time="0.273"><properties><property name="score" value="0.027161641" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i458]" time="0.301"><properties><property name="score" value="0.20463993" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i459]" time="0.280"><properties><property name="score" value="1.8900118" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606859 (title: An Effective Similarity Measure for Neighborhood-b) is an LLM-generated sample, misclassified as human-generated with confidence 1.8900118 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606859 (title: An Effective Similarity Measure for Neighborhood-b) is an LLM-generated sample, misclassified as human-generated with confidence 1.8900118
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i460]" time="0.316"><properties><property name="score" value="1.6376159" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8606871 (title: Fully Digital Background Calibration Technique for) is an LLM-generated sample, misclassified as human-generated with confidence 1.6376159 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8606871 (title: Fully Digital Background Calibration Technique for) is an LLM-generated sample, misclassified as human-generated with confidence 1.6376159
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i461]" time="0.300"><properties><property name="score" value="0.049599905" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i462]" time="0.295"><properties><property name="score" value="0.028537426" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i463]" time="0.296"><properties><property name="score" value="0.040081404" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i464]" time="0.344"><properties><property name="score" value="0.26183203" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i465]" time="0.290"><properties><property name="score" value="0.091932654" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i466]" time="0.270"><properties><property name="score" value="0.017985387" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i467]" time="0.295"><properties><property name="score" value="0.11411734" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i468]" time="0.341"><properties><property name="score" value="0.07839097" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i469]" time="0.260"><properties><property name="score" value="0.031082889" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i470]" time="0.288"><properties><property name="score" value="0.02424633" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i471]" time="0.286"><properties><property name="score" value="0.19608822" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i472]" time="0.285"><properties><property name="score" value="0.050860263" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i473]" time="0.312"><properties><property name="score" value="0.33934796" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i474]" time="0.278"><properties><property name="score" value="0.07569353" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i475]" time="0.291"><properties><property name="score" value="0.29607967" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i476]" time="0.334"><properties><property name="score" value="0.029022722" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i477]" time="0.279"><properties><property name="score" value="0.62794805" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i478]" time="0.435"><properties><property name="score" value="1.467606" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8607034 (title: Non-Blind Image Deblurring Method by the Total Var) is an LLM-generated sample, misclassified as human-generated with confidence 1.467606 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8607034 (title: Non-Blind Image Deblurring Method by the Total Var) is an LLM-generated sample, misclassified as human-generated with confidence 1.467606
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i479]" time="0.394"><properties><property name="score" value="0.08187747" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i480]" time="0.269"><properties><property name="score" value="0.10101924" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i481]" time="0.284"><properties><property name="score" value="0.043906506" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i482]" time="0.282"><properties><property name="score" value="0.38281626" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8607053 (title: Sequence-to-Sequence Acoustic Modeling for Voice C) is an LLM-generated sample, misclassified as human-generated with confidence 0.38281626 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8607053 (title: Sequence-to-Sequence Acoustic Modeling for Voice C) is an LLM-generated sample, misclassified as human-generated with confidence 0.38281626
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i483]" time="0.290"><properties><property name="score" value="0.05244452" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i484]" time="0.543"><properties><property name="score" value="0.033039223" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i485]" time="0.249"><properties><property name="score" value="0.053762168" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i486]" time="0.290"><properties><property name="score" value="0.09664473" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i487]" time="0.281"><properties><property name="score" value="0.06506135" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i488]" time="0.251"><properties><property name="score" value="0.0054671136" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i489]" time="0.335"><properties><property name="score" value="1.9768695" /></properties><failure message="AssertionError: samples/ieee-chatgpt-generation.jsonl:8607253 (title: Hierarchical Attention-Based Anomaly Detection Mod) is an LLM-generated sample, misclassified as human-generated with confidence 1.9768695 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-generation.jsonl:8607253 (title: Hierarchical Attention-Based Anomaly Detection Mod) is an LLM-generated sample, misclassified as human-generated with confidence 1.9768695
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i490]" time="0.301"><properties><property name="score" value="0.100475445" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i491]" time="0.262"><properties><property name="score" value="0.044984967" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i492]" time="0.326"><properties><property name="score" value="0.22567238" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i493]" time="0.297"><properties><property name="score" value="0.016358988" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i494]" time="0.297"><properties><property name="score" value="0.02086686" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i495]" time="0.280"><properties><property name="score" value="0.0548136" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i496]" time="0.290"><properties><property name="score" value="0.025794474" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i497]" time="0.269"><properties><property name="score" value="0.59563535" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i498]" time="0.385"><properties><property name="score" value="0.06793547" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_generation_jsonl[i499]" time="0.287"><properties><property name="score" value="0.04267691" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i0]" time="0.268"><properties><property name="score" value="0.10703251" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i1]" time="0.332"><properties><property name="score" value="0.11150627" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i2]" time="0.338"><properties><property name="score" value="0.7169914" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i3]" time="0.334"><properties><property name="score" value="0.67069715" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600036 (title: Pedestrian Detection and Attribute Analysis Progra) is an LLM-generated sample, misclassified as human-generated with confidence 0.67069715 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600036 (title: Pedestrian Detection and Attribute Analysis Progra) is an LLM-generated sample, misclassified as human-generated with confidence 0.67069715
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i4]" time="0.276"><properties><property name="score" value="0.3783355" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i5]" time="0.267"><properties><property name="score" value="0.59004164" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600042 (title: Large-Scale Image Geo- Tagging Using Affective Cla) is an LLM-generated sample, misclassified as human-generated with confidence 0.59004164 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600042 (title: Large-Scale Image Geo- Tagging Using Affective Cla) is an LLM-generated sample, misclassified as human-generated with confidence 0.59004164
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i6]" time="0.305"><properties><property name="score" value="0.5404352" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i7]" time="0.337"><properties><property name="score" value="0.042640895" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i8]" time="0.337"><properties><property name="score" value="0.39702523" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600080 (title: Identification of Coronary Artery Diseased Subject) is an LLM-generated sample, misclassified as human-generated with confidence 0.39702523 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600080 (title: Identification of Coronary Artery Diseased Subject) is an LLM-generated sample, misclassified as human-generated with confidence 0.39702523
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i9]" time="0.340"><properties><property name="score" value="1.1521935" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600082 (title: Matching Game Based User Access Algorithm in Energ) is an LLM-generated sample, misclassified as human-generated with confidence 1.1521935 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600082 (title: Matching Game Based User Access Algorithm in Energ) is an LLM-generated sample, misclassified as human-generated with confidence 1.1521935
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i10]" time="0.335"><properties><property name="score" value="0.019862296" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i11]" time="0.298"><properties><property name="score" value="2.0529666" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600090 (title: Research on Intrusion Detection Based on KPCA-BP N) is an LLM-generated sample, misclassified as human-generated with confidence 2.0529666 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600090 (title: Research on Intrusion Detection Based on KPCA-BP N) is an LLM-generated sample, misclassified as human-generated with confidence 2.0529666
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i12]" time="0.318"><properties><property name="score" value="0.45181772" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600091 (title: Improved Epoch Extraction Using Variational Mode D) is an LLM-generated sample, misclassified as human-generated with confidence 0.45181772 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600091 (title: Improved Epoch Extraction Using Variational Mode D) is an LLM-generated sample, misclassified as human-generated with confidence 0.45181772
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i13]" time="0.356"><properties><property name="score" value="0.94753087" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600094 (title: NLOS Detection and Mitigation for UWB/IMU Fusion S) is an LLM-generated sample, misclassified as human-generated with confidence 0.94753087 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600094 (title: NLOS Detection and Mitigation for UWB/IMU Fusion S) is an LLM-generated sample, misclassified as human-generated with confidence 0.94753087
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i14]" time="0.371"><properties><property name="score" value="1.5310607" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i15]" time="0.608"><properties><property name="score" value="1.9994333" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600099 (title: Ranking-based Collaborative Clustering for Heterog) is an LLM-generated sample, misclassified as human-generated with confidence 1.9994333 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600099 (title: Ranking-based Collaborative Clustering for Heterog) is an LLM-generated sample, misclassified as human-generated with confidence 1.9994333
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i16]" time="0.607"><properties><property name="score" value="0.2633225" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i17]" time="0.606"><properties><property name="score" value="0.12113562" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i18]" time="0.528"><properties><property name="score" value="0.05526804" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i19]" time="0.395"><properties><property name="score" value="0.2011182" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600123 (title: Semi-supervised Event Message Identification Syste) is an LLM-generated sample, misclassified as human-generated with confidence 0.2011182 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600123 (title: Semi-supervised Event Message Identification Syste) is an LLM-generated sample, misclassified as human-generated with confidence 0.2011182
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i20]" time="0.385"><properties><property name="score" value="0.5178056" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i21]" time="0.464"><properties><property name="score" value="0.07167474" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i22]" time="0.423"><properties><property name="score" value="2.1990037" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i23]" time="0.404"><properties><property name="score" value="0.95075804" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600139 (title: Lightweight Group Key Distribution Method Based on) is an LLM-generated sample, misclassified as human-generated with confidence 0.95075804 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600139 (title: Lightweight Group Key Distribution Method Based on) is an LLM-generated sample, misclassified as human-generated with confidence 0.95075804
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i24]" time="0.593"><properties><property name="score" value="0.16745952" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i25]" time="0.456"><properties><property name="score" value="0.40250587" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i26]" time="0.366"><properties><property name="score" value="0.1879529" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600153 (title: A New Combinatorial Design Based Data En-Route Fil) is an LLM-generated sample, misclassified as human-generated with confidence 0.1879529 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600153 (title: A New Combinatorial Design Based Data En-Route Fil) is an LLM-generated sample, misclassified as human-generated with confidence 0.1879529
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i27]" time="0.382"><properties><property name="score" value="0.18649836" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i28]" time="0.376"><properties><property name="score" value="0.10590552" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600165 (title: Adaptive Unequal Clustering Using an Improved LEAC) is an LLM-generated sample, misclassified as human-generated with confidence 0.10590552 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600165 (title: Adaptive Unequal Clustering Using an Improved LEAC) is an LLM-generated sample, misclassified as human-generated with confidence 0.10590552
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i29]" time="0.353"><properties><property name="score" value="0.16204058" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i30]" time="0.385"><properties><property name="score" value="0.38743922" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i31]" time="0.493"><properties><property name="score" value="0.45305467" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600190 (title: Manner of Articulation based Split Lattices for Ph) is an LLM-generated sample, misclassified as human-generated with confidence 0.45305467 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600190 (title: Manner of Articulation based Split Lattices for Ph) is an LLM-generated sample, misclassified as human-generated with confidence 0.45305467
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i32]" time="0.394"><properties><property name="score" value="0.49230626" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i33]" time="0.327"><properties><property name="score" value="2.339333" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600199 (title: Range Free Localization in Anisotropic Networks us) is an LLM-generated sample, misclassified as human-generated with confidence 2.339333 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600199 (title: Range Free Localization in Anisotropic Networks us) is an LLM-generated sample, misclassified as human-generated with confidence 2.339333
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i34]" time="0.348"><properties><property name="score" value="1.2379496" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600200 (title: Exploiting Class Hierarchies for Large-Scale Scene) is an LLM-generated sample, misclassified as human-generated with confidence 1.2379496 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600200 (title: Exploiting Class Hierarchies for Large-Scale Scene) is an LLM-generated sample, misclassified as human-generated with confidence 1.2379496
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i35]" time="0.374"><properties><property name="score" value="0.24640952" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i36]" time="0.410"><properties><property name="score" value="0.09066767" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600202 (title: Mridangam Artist Identification from Taniavartanam) is an LLM-generated sample, misclassified as human-generated with confidence 0.09066767 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600202 (title: Mridangam Artist Identification from Taniavartanam) is an LLM-generated sample, misclassified as human-generated with confidence 0.09066767
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i37]" time="0.358"><properties><property name="score" value="0.035649825" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i38]" time="0.356"><properties><property name="score" value="0.26629525" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i39]" time="0.355"><properties><property name="score" value="0.58687174" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i40]" time="0.336"><properties><property name="score" value="0.92487633" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i41]" time="0.322"><properties><property name="score" value="0.69715744" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i42]" time="0.320"><properties><property name="score" value="0.15816776" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i43]" time="0.313"><properties><property name="score" value="0.05151661" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i44]" time="0.354"><properties><property name="score" value="0.34236887" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i45]" time="0.333"><properties><property name="score" value="0.12835592" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i46]" time="0.314"><properties><property name="score" value="0.94020194" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600272 (title: Time-Sensitive Influence Maximization in Social Ne) is an LLM-generated sample, misclassified as human-generated with confidence 0.94020194 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600272 (title: Time-Sensitive Influence Maximization in Social Ne) is an LLM-generated sample, misclassified as human-generated with confidence 0.94020194
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i47]" time="0.337"><properties><property name="score" value="0.57610506" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600298 (title: Toward Secure and Scalable Computation in Internet) is an LLM-generated sample, misclassified as human-generated with confidence 0.57610506 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600298 (title: Toward Secure and Scalable Computation in Internet) is an LLM-generated sample, misclassified as human-generated with confidence 0.57610506
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i48]" time="0.480"><properties><property name="score" value="0.12538643" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i49]" time="0.326"><properties><property name="score" value="0.2130532" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i50]" time="0.333"><properties><property name="score" value="0.25327426" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600306 (title: A Two-Stage Attribute-Constraint Network for Video) is an LLM-generated sample, misclassified as human-generated with confidence 0.25327426 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600306 (title: A Two-Stage Attribute-Constraint Network for Video) is an LLM-generated sample, misclassified as human-generated with confidence 0.25327426
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i51]" time="0.417"><properties><property name="score" value="0.3447017" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600307 (title: Robust Hierarchical Learning for Non-Negative Matr) is an LLM-generated sample, misclassified as human-generated with confidence 0.3447017 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600307 (title: Robust Hierarchical Learning for Non-Negative Matr) is an LLM-generated sample, misclassified as human-generated with confidence 0.3447017
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i52]" time="0.401"><properties><property name="score" value="0.29092965" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i53]" time="0.292"><properties><property name="score" value="0.09763775" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600317 (title: Enabling Reproducible Research in Sensor-Based Tra) is an LLM-generated sample, misclassified as human-generated with confidence 0.09763775 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600317 (title: Enabling Reproducible Research in Sensor-Based Tra) is an LLM-generated sample, misclassified as human-generated with confidence 0.09763775
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i54]" time="0.304"><properties><property name="score" value="0.60667956" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i55]" time="0.324"><properties><property name="score" value="0.37093404" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600326 (title: Uplink Time Scheduling With Power Level Modulation) is an LLM-generated sample, misclassified as human-generated with confidence 0.37093404 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600326 (title: Uplink Time Scheduling With Power Level Modulation) is an LLM-generated sample, misclassified as human-generated with confidence 0.37093404
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i56]" time="0.287"><properties><property name="score" value="0.05482827" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i57]" time="0.306"><properties><property name="score" value="0.2684965" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i58]" time="0.261"><properties><property name="score" value="0.07201366" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600333 (title: Action-Stage Emphasized Spatiotemporal VLAD for Vi) is an LLM-generated sample, misclassified as human-generated with confidence 0.07201366 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600333 (title: Action-Stage Emphasized Spatiotemporal VLAD for Vi) is an LLM-generated sample, misclassified as human-generated with confidence 0.07201366
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i59]" time="0.328"><properties><property name="score" value="0.07228355" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i60]" time="0.354"><properties><property name="score" value="0.34024122" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i61]" time="0.276"><properties><property name="score" value="0.57849574" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i62]" time="0.422"><properties><property name="score" value="0.9240971" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i63]" time="0.300"><properties><property name="score" value="0.84102637" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600358 (title: A Low-Cost High-Speed Neuromorphic Hardware Based ) is an LLM-generated sample, misclassified as human-generated with confidence 0.84102637 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600358 (title: A Low-Cost High-Speed Neuromorphic Hardware Based ) is an LLM-generated sample, misclassified as human-generated with confidence 0.84102637
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i64]" time="0.332"><properties><property name="score" value="0.9624836" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i65]" time="0.335"><properties><property name="score" value="1.1476907" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i66]" time="0.306"><properties><property name="score" value="0.4280156" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i67]" time="0.373"><properties><property name="score" value="0.085026376" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i68]" time="0.321"><properties><property name="score" value="0.6955958" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i69]" time="0.298"><properties><property name="score" value="1.1744069" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i70]" time="0.267"><properties><property name="score" value="0.06989984" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600375 (title: Navion: A 2-mW Fully Integrated Real-Time Visual-I) is an LLM-generated sample, misclassified as human-generated with confidence 0.06989984 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600375 (title: Navion: A 2-mW Fully Integrated Real-Time Visual-I) is an LLM-generated sample, misclassified as human-generated with confidence 0.06989984
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i71]" time="0.323"><properties><property name="score" value="0.7579928" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600380 (title: Dynamic Texture Classification Using Unsupervised ) is an LLM-generated sample, misclassified as human-generated with confidence 0.7579928 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600380 (title: Dynamic Texture Classification Using Unsupervised ) is an LLM-generated sample, misclassified as human-generated with confidence 0.7579928
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i72]" time="0.298"><properties><property name="score" value="0.6283733" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600382 (title: A Deep Reinforcement Learning Network for Traffic ) is an LLM-generated sample, misclassified as human-generated with confidence 0.6283733 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600382 (title: A Deep Reinforcement Learning Network for Traffic ) is an LLM-generated sample, misclassified as human-generated with confidence 0.6283733
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i73]" time="0.271"><properties><property name="score" value="0.27841163" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600389 (title: Outlier Dirichlet Mixture Mechanism: Adversarial S) is an LLM-generated sample, misclassified as human-generated with confidence 0.27841163 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600389 (title: Outlier Dirichlet Mixture Mechanism: Adversarial S) is an LLM-generated sample, misclassified as human-generated with confidence 0.27841163
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i74]" time="0.285"><properties><property name="score" value="0.23924801" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600392 (title: Low Rank and Structured Modeling of High-Dimension) is an LLM-generated sample, misclassified as human-generated with confidence 0.23924801 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600392 (title: Low Rank and Structured Modeling of High-Dimension) is an LLM-generated sample, misclassified as human-generated with confidence 0.23924801
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i75]" time="0.378"><properties><property name="score" value="0.25028604" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i76]" time="0.328"><properties><property name="score" value="0.38688985" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600401 (title: HeadNet: An End-to-End Adaptive Relational Network) is an LLM-generated sample, misclassified as human-generated with confidence 0.38688985 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600401 (title: HeadNet: An End-to-End Adaptive Relational Network) is an LLM-generated sample, misclassified as human-generated with confidence 0.38688985
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i77]" time="0.352"><properties><property name="score" value="0.05110018" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600424 (title: Audiovisual Synchrony Detection with Optimized Aud) is an LLM-generated sample, misclassified as human-generated with confidence 0.05110018 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600424 (title: Audiovisual Synchrony Detection with Optimized Aud) is an LLM-generated sample, misclassified as human-generated with confidence 0.05110018
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i78]" time="0.313"><properties><property name="score" value="0.19805308" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i79]" time="0.298"><properties><property name="score" value="1.9722658" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600428 (title: An Adaptive Rate ECG Acquisition and Analysis for ) is an LLM-generated sample, misclassified as human-generated with confidence 1.9722658 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600428 (title: An Adaptive Rate ECG Acquisition and Analysis for ) is an LLM-generated sample, misclassified as human-generated with confidence 1.9722658
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i80]" time="0.376"><properties><property name="score" value="1.1131809" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i81]" time="0.338"><properties><property name="score" value="0.19972818" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i82]" time="0.337"><properties><property name="score" value="0.49529126" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600457 (title: A Generic Approach CNN-Based Camera Identification) is an LLM-generated sample, misclassified as human-generated with confidence 0.49529126 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600457 (title: A Generic Approach CNN-Based Camera Identification) is an LLM-generated sample, misclassified as human-generated with confidence 0.49529126
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i83]" time="0.348"><properties><property name="score" value="0.25499135" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600465 (title: A Novel Body Posture Recognition System on Bed) is an LLM-generated sample, misclassified as human-generated with confidence 0.25499135 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600465 (title: A Novel Body Posture Recognition System on Bed) is an LLM-generated sample, misclassified as human-generated with confidence 0.25499135
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i84]" time="0.407"><properties><property name="score" value="0.39147574" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i85]" time="0.328"><properties><property name="score" value="0.36510047" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i86]" time="0.447"><properties><property name="score" value="0.8415611" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i87]" time="0.395"><properties><property name="score" value="1.4270068" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600504 (title: An Object-Based Method Based on a Novel Statistica) is an LLM-generated sample, misclassified as human-generated with confidence 1.4270068 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600504 (title: An Object-Based Method Based on a Novel Statistica) is an LLM-generated sample, misclassified as human-generated with confidence 1.4270068
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i88]" time="0.334"><properties><property name="score" value="0.14281283" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i89]" time="0.352"><properties><property name="score" value="0.11269395" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i90]" time="0.416"><properties><property name="score" value="1.2291703" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600510 (title: Fire Detection in Infrared Video Surveillance Base) is an LLM-generated sample, misclassified as human-generated with confidence 1.2291703 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600510 (title: Fire Detection in Infrared Video Surveillance Base) is an LLM-generated sample, misclassified as human-generated with confidence 1.2291703
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i91]" time="0.344"><properties><property name="score" value="0.30377752" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i92]" time="0.314"><properties><property name="score" value="0.38806435" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i93]" time="0.321"><properties><property name="score" value="0.33743513" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i94]" time="0.294"><properties><property name="score" value="0.4061638" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i95]" time="0.275"><properties><property name="score" value="0.08615592" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i96]" time="0.278"><properties><property name="score" value="0.105240785" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i97]" time="0.269"><properties><property name="score" value="0.26610282" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i98]" time="0.284"><properties><property name="score" value="0.2878679" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600555 (title: SDP Based Unit Commitment Via Moment Relaxation) is an LLM-generated sample, misclassified as human-generated with confidence 0.2878679 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600555 (title: SDP Based Unit Commitment Via Moment Relaxation) is an LLM-generated sample, misclassified as human-generated with confidence 0.2878679
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i99]" time="0.276"><properties><property name="score" value="0.068354174" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i100]" time="1.362"><properties><property name="score" value="0.16474009" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i101]" time="0.484"><properties><property name="score" value="0.03308364" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i102]" time="0.264"><properties><property name="score" value="0.27040422" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i103]" time="0.256"><properties><property name="score" value="0.19290107" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i104]" time="0.289"><properties><property name="score" value="0.71231055" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i105]" time="0.303"><properties><property name="score" value="0.009863719" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i106]" time="0.291"><properties><property name="score" value="0.28297326" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i107]" time="0.291"><properties><property name="score" value="2.1959376" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600657 (title: Effect of Solar PV Penetration on Residential Ener) is an LLM-generated sample, misclassified as human-generated with confidence 2.1959376 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600657 (title: Effect of Solar PV Penetration on Residential Ener) is an LLM-generated sample, misclassified as human-generated with confidence 2.1959376
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i108]" time="0.278"><properties><property name="score" value="0.033054132" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i109]" time="0.328"><properties><property name="score" value="0.16401632" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i110]" time="0.311"><properties><property name="score" value="0.17261752" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i111]" time="0.335"><properties><property name="score" value="0.60763484" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600713 (title: Using PPG Signals and Wearable Devices for Atrial ) is an LLM-generated sample, misclassified as human-generated with confidence 0.60763484 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600713 (title: Using PPG Signals and Wearable Devices for Atrial ) is an LLM-generated sample, misclassified as human-generated with confidence 0.60763484
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i112]" time="0.435"><properties><property name="score" value="0.56882656" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i113]" time="0.309"><properties><property name="score" value="0.15866655" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i114]" time="0.301"><properties><property name="score" value="0.61185926" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i115]" time="0.280"><properties><property name="score" value="1.1489345" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600732 (title: A Novel Generative Model With Bounded-GAN for Reli) is an LLM-generated sample, misclassified as human-generated with confidence 1.1489345 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600732 (title: A Novel Generative Model With Bounded-GAN for Reli) is an LLM-generated sample, misclassified as human-generated with confidence 1.1489345
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i116]" time="0.292"><properties><property name="score" value="0.9325012" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600733 (title: An Outlier-Insensitive Unmixing Algorithm With Spa) is an LLM-generated sample, misclassified as human-generated with confidence 0.9325012 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600733 (title: An Outlier-Insensitive Unmixing Algorithm With Spa) is an LLM-generated sample, misclassified as human-generated with confidence 0.9325012
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i117]" time="0.445"><properties><property name="score" value="0.2596968" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i118]" time="0.294"><properties><property name="score" value="0.3358692" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600736 (title: Forecasting Traffic Volume at a Designated Cross-S) is an LLM-generated sample, misclassified as human-generated with confidence 0.3358692 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600736 (title: Forecasting Traffic Volume at a Designated Cross-S) is an LLM-generated sample, misclassified as human-generated with confidence 0.3358692
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i119]" time="0.268"><properties><property name="score" value="0.009838739" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i120]" time="0.339"><properties><property name="score" value="0.2989922" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600748 (title: Deploying the First PSTN-Based IoT Mechanism) is an LLM-generated sample, misclassified as human-generated with confidence 0.2989922 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600748 (title: Deploying the First PSTN-Based IoT Mechanism) is an LLM-generated sample, misclassified as human-generated with confidence 0.2989922
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i121]" time="0.347"><properties><property name="score" value="0.2028818" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i122]" time="0.349"><properties><property name="score" value="0.036890157" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i123]" time="0.325"><properties><property name="score" value="0.09999933" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i124]" time="0.374"><properties><property name="score" value="0.4765163" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600762 (title: Latent Factor-Based Recommenders Relying on Extend) is an LLM-generated sample, misclassified as human-generated with confidence 0.4765163 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600762 (title: Latent Factor-Based Recommenders Relying on Extend) is an LLM-generated sample, misclassified as human-generated with confidence 0.4765163
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i125]" time="0.316"><properties><property name="score" value="0.68185806" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i126]" time="0.333"><properties><property name="score" value="0.03006748" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i127]" time="0.310"><properties><property name="score" value="1.8560406" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600780 (title: Distributed Data Privacy Preservation in IoT Appli) is an LLM-generated sample, misclassified as human-generated with confidence 1.8560406 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600780 (title: Distributed Data Privacy Preservation in IoT Appli) is an LLM-generated sample, misclassified as human-generated with confidence 1.8560406
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i128]" time="0.340"><properties><property name="score" value="1.2590873" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600781 (title: Proactive Cache-Based Location Privacy Preserving ) is an LLM-generated sample, misclassified as human-generated with confidence 1.2590873 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600781 (title: Proactive Cache-Based Location Privacy Preserving ) is an LLM-generated sample, misclassified as human-generated with confidence 1.2590873
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i129]" time="0.344"><properties><property name="score" value="0.13439208" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i130]" time="0.369"><properties><property name="score" value="0.017556792" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i131]" time="0.346"><properties><property name="score" value="1.7668414" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600784 (title: Privacy-Preserving Tensor Analysis and Processing ) is an LLM-generated sample, misclassified as human-generated with confidence 1.7668414 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600784 (title: Privacy-Preserving Tensor Analysis and Processing ) is an LLM-generated sample, misclassified as human-generated with confidence 1.7668414
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i132]" time="0.371"><properties><property name="score" value="1.1216122" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600788 (title: Communication scheduling and remote estimation wit) is an LLM-generated sample, misclassified as human-generated with confidence 1.1216122 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600788 (title: Communication scheduling and remote estimation wit) is an LLM-generated sample, misclassified as human-generated with confidence 1.1216122
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i133]" time="0.522"><properties><property name="score" value="0.18915345" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600790 (title: Wireless acoustic sensor networks and edge computi) is an LLM-generated sample, misclassified as human-generated with confidence 0.18915345 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600790 (title: Wireless acoustic sensor networks and edge computi) is an LLM-generated sample, misclassified as human-generated with confidence 0.18915345
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i134]" time="0.432"><properties><property name="score" value="0.16197813" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i135]" time="0.362"><properties><property name="score" value="1.2060516" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600819 (title: Small Parts Classification with Flexible Machine V) is an LLM-generated sample, misclassified as human-generated with confidence 1.2060516 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600819 (title: Small Parts Classification with Flexible Machine V) is an LLM-generated sample, misclassified as human-generated with confidence 1.2060516
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i136]" time="0.364"><properties><property name="score" value="0.11520647" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i137]" time="0.322"><properties><property name="score" value="0.2446175" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i138]" time="0.295"><properties><property name="score" value="0.18593441" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i139]" time="0.412"><properties><property name="score" value="0.027210394" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i140]" time="0.280"><properties><property name="score" value="0.17282997" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i141]" time="0.343"><properties><property name="score" value="1.0401751" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i142]" time="0.290"><properties><property name="score" value="0.32727748" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i143]" time="0.298"><properties><property name="score" value="0.60097235" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600847 (title: Authentication of Aerial Input Numerals by Leap Mo) is an LLM-generated sample, misclassified as human-generated with confidence 0.60097235 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600847 (title: Authentication of Aerial Input Numerals by Leap Mo) is an LLM-generated sample, misclassified as human-generated with confidence 0.60097235
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i144]" time="0.284"><properties><property name="score" value="0.26085615" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i145]" time="0.264"><properties><property name="score" value="1.0615159" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i146]" time="0.309"><properties><property name="score" value="0.20303564" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i147]" time="0.258"><properties><property name="score" value="0.23191892" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i148]" time="0.291"><properties><property name="score" value="0.14263299" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i149]" time="0.274"><properties><property name="score" value="1.0754918" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600857 (title: A Vision Aid for the Visually Impaired using Commo) is an LLM-generated sample, misclassified as human-generated with confidence 1.0754918 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600857 (title: A Vision Aid for the Visually Impaired using Commo) is an LLM-generated sample, misclassified as human-generated with confidence 1.0754918
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i150]" time="0.297"><properties><property name="score" value="1.51381" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600858 (title: NPK Soil Nutrient Measurement Prototype Based on L) is an LLM-generated sample, misclassified as human-generated with confidence 1.51381 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600858 (title: NPK Soil Nutrient Measurement Prototype Based on L) is an LLM-generated sample, misclassified as human-generated with confidence 1.51381
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i151]" time="0.292"><properties><property name="score" value="0.3026124" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i152]" time="0.269"><properties><property name="score" value="0.71604276" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600860 (title: The Industrial IoT for Nusantara) is an LLM-generated sample, misclassified as human-generated with confidence 0.71604276 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600860 (title: The Industrial IoT for Nusantara) is an LLM-generated sample, misclassified as human-generated with confidence 0.71604276
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i153]" time="0.279"><properties><property name="score" value="0.8262683" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i154]" time="0.282"><properties><property name="score" value="0.7412469" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600863 (title: A new method for fast detection and pose estimatio) is an LLM-generated sample, misclassified as human-generated with confidence 0.7412469 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600863 (title: A new method for fast detection and pose estimatio) is an LLM-generated sample, misclassified as human-generated with confidence 0.7412469
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i155]" time="0.266"><properties><property name="score" value="0.25270343" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600877 (title: Vehicle and Pedestrian Recognition Using Multilaye) is an LLM-generated sample, misclassified as human-generated with confidence 0.25270343 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600877 (title: Vehicle and Pedestrian Recognition Using Multilaye) is an LLM-generated sample, misclassified as human-generated with confidence 0.25270343
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i156]" time="0.295"><properties><property name="score" value="0.046824586" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i157]" time="0.290"><properties><property name="score" value="0.042922582" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600884 (title: Sentiment Analysis on User Satisfaction Level of M) is an LLM-generated sample, misclassified as human-generated with confidence 0.04292258 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600884 (title: Sentiment Analysis on User Satisfaction Level of M) is an LLM-generated sample, misclassified as human-generated with confidence 0.04292258
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i158]" time="0.341"><properties><property name="score" value="0.6180129" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i159]" time="0.333"><properties><property name="score" value="0.045017887" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600890 (title: Opportunistic Wardriving Through Neighborhood Publ) is an LLM-generated sample, misclassified as human-generated with confidence 0.04501789 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600890 (title: Opportunistic Wardriving Through Neighborhood Publ) is an LLM-generated sample, misclassified as human-generated with confidence 0.04501789
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i160]" time="0.326"><properties><property name="score" value="0.22006796" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i161]" time="0.300"><properties><property name="score" value="0.022754729" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i162]" time="0.292"><properties><property name="score" value="0.08042633" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i163]" time="0.350"><properties><property name="score" value="1.3240201" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600895 (title: Realization of IPv6 connectivity via RS485 fieldbu) is an LLM-generated sample, misclassified as human-generated with confidence 1.3240201 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600895 (title: Realization of IPv6 connectivity via RS485 fieldbu) is an LLM-generated sample, misclassified as human-generated with confidence 1.3240201
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i164]" time="0.299"><properties><property name="score" value="1.3876404" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600904 (title: Smart Air Quality Monitoring System with LoRaWAN) is an LLM-generated sample, misclassified as human-generated with confidence 1.3876404 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600904 (title: Smart Air Quality Monitoring System with LoRaWAN) is an LLM-generated sample, misclassified as human-generated with confidence 1.3876404
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i165]" time="0.331"><properties><property name="score" value="0.69269574" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i166]" time="0.349"><properties><property name="score" value="0.21329905" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i167]" time="0.331"><properties><property name="score" value="0.14971067" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i168]" time="0.269"><properties><property name="score" value="0.06898225" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i169]" time="0.325"><properties><property name="score" value="0.11501011" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i170]" time="0.278"><properties><property name="score" value="0.04475942" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i171]" time="0.293"><properties><property name="score" value="0.092381075" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i172]" time="0.282"><properties><property name="score" value="0.12585072" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i173]" time="0.273"><properties><property name="score" value="0.4490595" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i174]" time="0.335"><properties><property name="score" value="0.050589684" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i175]" time="0.274"><properties><property name="score" value="0.7783596" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600936 (title: Reactive HLA-based Distributed Simulation Systems ) is an LLM-generated sample, misclassified as human-generated with confidence 0.7783596 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600936 (title: Reactive HLA-based Distributed Simulation Systems ) is an LLM-generated sample, misclassified as human-generated with confidence 0.7783596
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i176]" time="0.371"><properties><property name="score" value="0.02423387" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i177]" time="0.318"><properties><property name="score" value="0.40593195" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i178]" time="0.257"><properties><property name="score" value="0.15426661" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i179]" time="0.337"><properties><property name="score" value="1.1304812" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8600998 (title: Adaptive Event Driven Framework for Real Time Mult) is an LLM-generated sample, misclassified as human-generated with confidence 1.1304812 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8600998 (title: Adaptive Event Driven Framework for Real Time Mult) is an LLM-generated sample, misclassified as human-generated with confidence 1.1304812
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i180]" time="0.267"><properties><property name="score" value="0.013883772" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i181]" time="0.271"><properties><property name="score" value="2.3649929" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601011 (title: Machine Learning Aided Simulation of Public Transp) is an LLM-generated sample, misclassified as human-generated with confidence 2.3649929 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601011 (title: Machine Learning Aided Simulation of Public Transp) is an LLM-generated sample, misclassified as human-generated with confidence 2.3649929
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i182]" time="0.329"><properties><property name="score" value="0.12635724" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i183]" time="0.284"><properties><property name="score" value="0.98577005" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i184]" time="0.267"><properties><property name="score" value="0.99781394" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601027 (title: A Comprehensive Monitoring and Controlling System ) is an LLM-generated sample, misclassified as human-generated with confidence 0.99781394 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601027 (title: A Comprehensive Monitoring and Controlling System ) is an LLM-generated sample, misclassified as human-generated with confidence 0.99781394
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i185]" time="0.320"><properties><property name="score" value="0.16217418" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i186]" time="0.294"><properties><property name="score" value="0.2500822" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i187]" time="0.310"><properties><property name="score" value="0.028637644" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i188]" time="0.298"><properties><property name="score" value="0.28280032" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i189]" time="0.361"><properties><property name="score" value="0.068034485" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i190]" time="0.311"><properties><property name="score" value="0.3516343" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601150 (title: Device Classification for NILM using FIT-PS compar) is an LLM-generated sample, misclassified as human-generated with confidence 0.3516343 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601150 (title: Device Classification for NILM using FIT-PS compar) is an LLM-generated sample, misclassified as human-generated with confidence 0.3516343
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i191]" time="0.339"><properties><property name="score" value="0.071672626" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i192]" time="0.339"><properties><property name="score" value="0.8663685" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i193]" time="0.277"><properties><property name="score" value="0.3416962" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601184 (title: A Cooperation Analysis Method Using Internal and E) is an LLM-generated sample, misclassified as human-generated with confidence 0.3416962 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601184 (title: A Cooperation Analysis Method Using Internal and E) is an LLM-generated sample, misclassified as human-generated with confidence 0.3416962
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i194]" time="0.281"><properties><property name="score" value="0.3366278" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601185 (title: Hierarchical Facial Age Estimation Using Gaussian ) is an LLM-generated sample, misclassified as human-generated with confidence 0.3366278 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601185 (title: Hierarchical Facial Age Estimation Using Gaussian ) is an LLM-generated sample, misclassified as human-generated with confidence 0.3366278
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i195]" time="0.315"><properties><property name="score" value="1.1112841" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601186 (title: A Survey of Stereoscopic 3D Just Noticeable Differ) is an LLM-generated sample, misclassified as human-generated with confidence 1.1112841 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601186 (title: A Survey of Stereoscopic 3D Just Noticeable Differ) is an LLM-generated sample, misclassified as human-generated with confidence 1.1112841
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i196]" time="0.368"><properties><property name="score" value="0.3499432" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i197]" time="0.489"><properties><property name="score" value="1.5254644" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601192 (title: Study on Planetary Gear Degradation State Recognit) is an LLM-generated sample, misclassified as human-generated with confidence 1.5254644 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601192 (title: Study on Planetary Gear Degradation State Recognit) is an LLM-generated sample, misclassified as human-generated with confidence 1.5254644
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i198]" time="0.386"><properties><property name="score" value="0.37882817" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i199]" time="0.268"><properties><property name="score" value="0.18803857" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601202 (title: Delivery of an Interactive Audio Course on Fisheri) is an LLM-generated sample, misclassified as human-generated with confidence 0.18803857 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601202 (title: Delivery of an Interactive Audio Course on Fisheri) is an LLM-generated sample, misclassified as human-generated with confidence 0.18803857
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i200]" time="0.270"><properties><property name="score" value="0.4791758" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601218 (title: Detecting and Removing the Impulsive Noise in OFDM) is an LLM-generated sample, misclassified as human-generated with confidence 0.4791758 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601218 (title: Detecting and Removing the Impulsive Noise in OFDM) is an LLM-generated sample, misclassified as human-generated with confidence 0.4791758
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i201]" time="0.290"><properties><property name="score" value="0.039136596" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i202]" time="0.250"><properties><property name="score" value="0.6022907" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601232 (title: A Training Utility for Estimating the Bowling Spee) is an LLM-generated sample, misclassified as human-generated with confidence 0.6022907 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601232 (title: A Training Utility for Estimating the Bowling Spee) is an LLM-generated sample, misclassified as human-generated with confidence 0.6022907
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i203]" time="0.276"><properties><property name="score" value="0.2078581" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i204]" time="0.370"><properties><property name="score" value="0.6109958" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601236 (title: Business Analytics for Institutional Academic Mana) is an LLM-generated sample, misclassified as human-generated with confidence 0.6109958 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601236 (title: Business Analytics for Institutional Academic Mana) is an LLM-generated sample, misclassified as human-generated with confidence 0.6109958
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i205]" time="0.328"><properties><property name="score" value="0.47444856" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i206]" time="0.283"><properties><property name="score" value="0.21112965" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i207]" time="0.261"><properties><property name="score" value="0.11120272" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i208]" time="1.135"><properties><property name="score" value="0.21337578" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i209]" time="0.310"><properties><property name="score" value="0.030964168" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i210]" time="0.707"><properties><property name="score" value="0.24035299" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i211]" time="0.293"><properties><property name="score" value="0.032007053" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i212]" time="0.343"><properties><property name="score" value="0.59387183" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i213]" time="0.299"><properties><property name="score" value="0.07873424" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i214]" time="0.306"><properties><property name="score" value="0.15196745" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i215]" time="0.331"><properties><property name="score" value="0.08422603" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i216]" time="0.348"><properties><property name="score" value="0.04418655" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i217]" time="0.303"><properties><property name="score" value="0.4992106" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i218]" time="0.342"><properties><property name="score" value="0.03691551" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i219]" time="0.283"><properties><property name="score" value="0.3147368" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i220]" time="0.343"><properties><property name="score" value="0.10299362" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i221]" time="0.306"><properties><property name="score" value="0.18707922" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601303 (title: A Controllable Deflection Routing and Wavelength A) is an LLM-generated sample, misclassified as human-generated with confidence 0.18707922 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601303 (title: A Controllable Deflection Routing and Wavelength A) is an LLM-generated sample, misclassified as human-generated with confidence 0.18707922
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i222]" time="0.348"><properties><property name="score" value="0.077089496" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i223]" time="0.306"><properties><property name="score" value="1.1134473" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i224]" time="0.292"><properties><property name="score" value="0.5248034" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601319 (title: Deep Learning and Handcrafted Method Fusion: Highe) is an LLM-generated sample, misclassified as human-generated with confidence 0.5248034 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601319 (title: Deep Learning and Handcrafted Method Fusion: Highe) is an LLM-generated sample, misclassified as human-generated with confidence 0.5248034
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i225]" time="0.269"><properties><property name="score" value="0.5017639" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i226]" time="0.297"><properties><property name="score" value="0.9607342" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i227]" time="0.301"><properties><property name="score" value="0.07301621" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i228]" time="0.307"><properties><property name="score" value="1.1157353" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i229]" time="0.316"><properties><property name="score" value="1.3800912" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601345 (title: Active Object Detection With Multistep Action Pred) is an LLM-generated sample, misclassified as human-generated with confidence 1.3800912 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601345 (title: Active Object Detection With Multistep Action Pred) is an LLM-generated sample, misclassified as human-generated with confidence 1.3800912
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i230]" time="0.328"><properties><property name="score" value="0.21329197" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601346 (title: BLUEs and Reliability Analysis for General Censore) is an LLM-generated sample, misclassified as human-generated with confidence 0.21329197 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601346 (title: BLUEs and Reliability Analysis for General Censore) is an LLM-generated sample, misclassified as human-generated with confidence 0.21329197
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i231]" time="0.271"><properties><property name="score" value="0.89335835" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i232]" time="0.315"><properties><property name="score" value="0.25590682" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i233]" time="0.327"><properties><property name="score" value="0.023930054" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601358 (title: Secure and Privacy-Preserving Consensus) is an LLM-generated sample, misclassified as human-generated with confidence 0.02393005 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601358 (title: Secure and Privacy-Preserving Consensus) is an LLM-generated sample, misclassified as human-generated with confidence 0.02393005
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i234]" time="0.381"><properties><property name="score" value="0.15621127" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i235]" time="0.341"><properties><property name="score" value="0.054036" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i236]" time="0.312"><properties><property name="score" value="0.36130124" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i237]" time="0.260"><properties><property name="score" value="0.078895405" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601377 (title: Effective and Efficient Photo-Based PM2.5 Concentr) is an LLM-generated sample, misclassified as human-generated with confidence 0.07889541 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601377 (title: Effective and Efficient Photo-Based PM2.5 Concentr) is an LLM-generated sample, misclassified as human-generated with confidence 0.07889541
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i238]" time="0.284"><properties><property name="score" value="0.7471102" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i239]" time="0.289"><properties><property name="score" value="0.19692998" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i240]" time="0.266"><properties><property name="score" value="0.60823494" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601402 (title: Illumination-Invariance Optical Flow Estimation Us) is an LLM-generated sample, misclassified as human-generated with confidence 0.60823494 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601402 (title: Illumination-Invariance Optical Flow Estimation Us) is an LLM-generated sample, misclassified as human-generated with confidence 0.60823494
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i241]" time="0.315"><properties><property name="score" value="1.0497403" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601430 (title: Short-Term Forecast of Electricity Load for LLC &#) is an LLM-generated sample, misclassified as human-generated with confidence 1.0497403 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601430 (title: Short-Term Forecast of Electricity Load for LLC &#) is an LLM-generated sample, misclassified as human-generated with confidence 1.0497403
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i242]" time="0.349"><properties><property name="score" value="0.34707373" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601440 (title: Perspective Neural Network Algorithms for Dynamic ) is an LLM-generated sample, misclassified as human-generated with confidence 0.34707373 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601440 (title: Perspective Neural Network Algorithms for Dynamic ) is an LLM-generated sample, misclassified as human-generated with confidence 0.34707373
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i243]" time="0.309"><properties><property name="score" value="0.35377336" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i244]" time="0.302"><properties><property name="score" value="1.1558404" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601468 (title: Vehicles Cooperative Navigation Using GNSS for Coo) is an LLM-generated sample, misclassified as human-generated with confidence 1.1558404 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601468 (title: Vehicles Cooperative Navigation Using GNSS for Coo) is an LLM-generated sample, misclassified as human-generated with confidence 1.1558404
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i245]" time="0.276"><properties><property name="score" value="0.25057805" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i246]" time="0.273"><properties><property name="score" value="1.1297356" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601477 (title: Estimation of the Distribution Probability Density) is an LLM-generated sample, misclassified as human-generated with confidence 1.1297356 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601477 (title: Estimation of the Distribution Probability Density) is an LLM-generated sample, misclassified as human-generated with confidence 1.1297356
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i247]" time="0.319"><properties><property name="score" value="1.1705426" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i248]" time="0.273"><properties><property name="score" value="1.2747728" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i249]" time="0.378"><properties><property name="score" value="0.13146085" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i250]" time="0.293"><properties><property name="score" value="0.7523752" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i251]" time="0.321"><properties><property name="score" value="0.20002015" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i252]" time="0.308"><properties><property name="score" value="0.2747345" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i253]" time="0.316"><properties><property name="score" value="1.7123213" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601550 (title: A Novel Method of Wind Speed Prediction by Peephol) is an LLM-generated sample, misclassified as human-generated with confidence 1.7123213 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601550 (title: A Novel Method of Wind Speed Prediction by Peephol) is an LLM-generated sample, misclassified as human-generated with confidence 1.7123213
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i254]" time="0.305"><properties><property name="score" value="0.14138563" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i255]" time="0.306"><properties><property name="score" value="0.1364233" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i256]" time="0.312"><properties><property name="score" value="0.093870014" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i257]" time="0.338"><properties><property name="score" value="0.39586297" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i258]" time="0.276"><properties><property name="score" value="0.24807301" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i259]" time="0.367"><properties><property name="score" value="0.10071274" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i260]" time="0.310"><properties><property name="score" value="0.7374453" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i261]" time="0.408"><properties><property name="score" value="0.05997735" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i262]" time="0.383"><properties><property name="score" value="0.44655833" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i263]" time="0.365"><properties><property name="score" value="0.174652" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601668 (title: Decision Tree-based Real-time Emergency Control St) is an LLM-generated sample, misclassified as human-generated with confidence 0.174652 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601668 (title: Decision Tree-based Real-time Emergency Control St) is an LLM-generated sample, misclassified as human-generated with confidence 0.174652
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i264]" time="0.338"><properties><property name="score" value="1.0277203" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i265]" time="0.292"><properties><property name="score" value="1.4646399" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601677 (title: Train the Trainers: Medical Technology for the Sus) is an LLM-generated sample, misclassified as human-generated with confidence 1.4646399 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601677 (title: Train the Trainers: Medical Technology for the Sus) is an LLM-generated sample, misclassified as human-generated with confidence 1.4646399
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i266]" time="1.666"><properties><property name="score" value="2.0417156" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601701 (title: IoT Sensor Network Approach for Smart Farming: An ) is an LLM-generated sample, misclassified as human-generated with confidence 2.0417156 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601701 (title: IoT Sensor Network Approach for Smart Farming: An ) is an LLM-generated sample, misclassified as human-generated with confidence 2.0417156
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i267]" time="0.277"><properties><property name="score" value="0.09669778" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601703 (title: Optimal allocation of distributed reactive power c) is an LLM-generated sample, misclassified as human-generated with confidence 0.09669778 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601703 (title: Optimal allocation of distributed reactive power c) is an LLM-generated sample, misclassified as human-generated with confidence 0.09669778
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i268]" time="0.370"><properties><property name="score" value="0.5769255" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i269]" time="0.359"><properties><property name="score" value="0.10151432" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i270]" time="0.324"><properties><property name="score" value="0.03149265" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i271]" time="0.258"><properties><property name="score" value="0.17799476" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i272]" time="0.275"><properties><property name="score" value="0.025732214" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i273]" time="0.288"><properties><property name="score" value="0.20451136" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i274]" time="0.282"><properties><property name="score" value="0.17158875" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i275]" time="0.303"><properties><property name="score" value="0.21190462" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i276]" time="0.348"><properties><property name="score" value="0.4975876" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i277]" time="0.252"><properties><property name="score" value="0.0453245" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i278]" time="0.299"><properties><property name="score" value="0.2483099" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601829 (title: Fully Distributed Dynamic Optimal Power Flow of Ac) is an LLM-generated sample, misclassified as human-generated with confidence 0.2483099 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601829 (title: Fully Distributed Dynamic Optimal Power Flow of Ac) is an LLM-generated sample, misclassified as human-generated with confidence 0.2483099
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i279]" time="0.275"><properties><property name="score" value="0.058538996" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i280]" time="0.288"><properties><property name="score" value="1.0106319" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i281]" time="0.291"><properties><property name="score" value="0.022938099" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i282]" time="0.270"><properties><property name="score" value="0.22083168" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i283]" time="0.411"><properties><property name="score" value="0.34152427" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601876 (title: Toward Human-Centered Simulation Modeling for Crit) is an LLM-generated sample, misclassified as human-generated with confidence 0.34152427 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601876 (title: Toward Human-Centered Simulation Modeling for Crit) is an LLM-generated sample, misclassified as human-generated with confidence 0.34152427
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i284]" time="0.366"><properties><property name="score" value="1.1973118" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i285]" time="0.370"><properties><property name="score" value="0.3376666" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i286]" time="0.428"><properties><property name="score" value="0.15001576" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i287]" time="2.732"><properties><property name="score" value="0.52567625" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i288]" time="0.309"><properties><property name="score" value="0.87799805" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601908 (title: IoT-Based Precision Monitoring of Horticultural Cr) is an LLM-generated sample, misclassified as human-generated with confidence 0.87799805 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601908 (title: IoT-Based Precision Monitoring of Horticultural Cr) is an LLM-generated sample, misclassified as human-generated with confidence 0.87799805
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i289]" time="0.287"><properties><property name="score" value="0.6399524" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i290]" time="0.304"><properties><property name="score" value="1.1379833" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8601913 (title: Roadmap for Design of Surgical Equipment for Safe ) is an LLM-generated sample, misclassified as human-generated with confidence 1.1379833 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8601913 (title: Roadmap for Design of Surgical Equipment for Safe ) is an LLM-generated sample, misclassified as human-generated with confidence 1.1379833
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i291]" time="0.272"><properties><property name="score" value="0.087060556" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i292]" time="0.344"><properties><property name="score" value="1.159761" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i293]" time="0.309"><properties><property name="score" value="0.22235592" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i294]" time="0.324"><properties><property name="score" value="0.69996834" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i295]" time="0.365"><properties><property name="score" value="0.1422225" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i296]" time="0.295"><properties><property name="score" value="0.7381519" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i297]" time="0.285"><properties><property name="score" value="0.076200336" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i298]" time="0.291"><properties><property name="score" value="0.14441551" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i299]" time="0.378"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602075 (title: Robust Algorithm for Dress Recognition of Substati) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602075 (title: Robust Algorithm for Dress Recognition of Substati) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i300]" time="0.337"><properties><property name="score" value="0.16074169" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602084 (title: Research on Real Power Grid Security and Stability) is an LLM-generated sample, misclassified as human-generated with confidence 0.16074169 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602084 (title: Research on Real Power Grid Security and Stability) is an LLM-generated sample, misclassified as human-generated with confidence 0.16074169
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i301]" time="0.326"><properties><property name="score" value="0.29678717" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i302]" time="0.304"><properties><property name="score" value="1.0752455" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602088 (title: A Fast Algorithm to Calculate LMP Difference Cause) is an LLM-generated sample, misclassified as human-generated with confidence 1.0752455 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602088 (title: A Fast Algorithm to Calculate LMP Difference Cause) is an LLM-generated sample, misclassified as human-generated with confidence 1.0752455
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i303]" time="0.283"><properties><property name="score" value="0.1494533" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i304]" time="0.293"><properties><property name="score" value="0.216086" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i305]" time="0.294"><properties><property name="score" value="0.65345985" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i306]" time="0.387"><properties><property name="score" value="0.8982713" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i307]" time="0.280"><properties><property name="score" value="1.9105958" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602122 (title: Growth Height Prediction for the Trees under Overh) is an LLM-generated sample, misclassified as human-generated with confidence 1.9105958 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602122 (title: Growth Height Prediction for the Trees under Overh) is an LLM-generated sample, misclassified as human-generated with confidence 1.9105958
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i308]" time="0.295"><properties><property name="score" value="0.014399198" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i309]" time="0.305"><properties><property name="score" value="0.11218831" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i310]" time="0.284"><properties><property name="score" value="1.8480325" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602141 (title: A Fault Line Detection Method Based on VMD and Pha) is an LLM-generated sample, misclassified as human-generated with confidence 1.8480325 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602141 (title: A Fault Line Detection Method Based on VMD and Pha) is an LLM-generated sample, misclassified as human-generated with confidence 1.8480325
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i311]" time="0.302"><properties><property name="score" value="0.11024325" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i312]" time="0.309"><properties><property name="score" value="0.5000123" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602145 (title: Large-scale Power Grid Digital Parallel Simulation) is an LLM-generated sample, misclassified as human-generated with confidence 0.5000123 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602145 (title: Large-scale Power Grid Digital Parallel Simulation) is an LLM-generated sample, misclassified as human-generated with confidence 0.5000123
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i313]" time="0.313"><properties><property name="score" value="0.12039446" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i314]" time="0.325"><properties><property name="score" value="0.23093799" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i315]" time="0.311"><properties><property name="score" value="0.48076496" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i316]" time="0.315"><properties><property name="score" value="0.15060492" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i317]" time="0.309"><properties><property name="score" value="0.21065119" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i318]" time="0.322"><properties><property name="score" value="0.32572827" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i319]" time="0.422"><properties><property name="score" value="0.6704278" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i320]" time="0.300"><properties><property name="score" value="0.076651864" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i321]" time="0.266"><properties><property name="score" value="0.06500837" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i322]" time="0.300"><properties><property name="score" value="1.4351798" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602229 (title: Graph Computation based Power Flow for Large-Scale) is an LLM-generated sample, misclassified as human-generated with confidence 1.4351798 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602229 (title: Graph Computation based Power Flow for Large-Scale) is an LLM-generated sample, misclassified as human-generated with confidence 1.4351798
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i323]" time="0.305"><properties><property name="score" value="0.4803448" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i324]" time="0.323"><properties><property name="score" value="0.09846054" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i325]" time="0.311"><properties><property name="score" value="0.42828012" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i326]" time="0.286"><properties><property name="score" value="0.21324047" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i327]" time="0.353"><properties><property name="score" value="0.25956482" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i328]" time="0.292"><properties><property name="score" value="0.17657492" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i329]" time="0.302"><properties><property name="score" value="0.54230183" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i330]" time="0.307"><properties><property name="score" value="0.058415323" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i331]" time="0.350"><properties><property name="score" value="0.95801705" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602281 (title: A Novel Bus-bar Protection Principle Based on Mode) is an LLM-generated sample, misclassified as human-generated with confidence 0.95801705 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602281 (title: A Novel Bus-bar Protection Principle Based on Mode) is an LLM-generated sample, misclassified as human-generated with confidence 0.95801705
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i332]" time="0.333"><properties><property name="score" value="0.36176005" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i333]" time="0.288"><properties><property name="score" value="1.9853517" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602291 (title: Microgrid Intra-day Scheduling Considering Reactiv) is an LLM-generated sample, misclassified as human-generated with confidence 1.9853517 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602291 (title: Microgrid Intra-day Scheduling Considering Reactiv) is an LLM-generated sample, misclassified as human-generated with confidence 1.9853517
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i334]" time="0.295"><properties><property name="score" value="0.15541549" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i335]" time="0.293"><properties><property name="score" value="0.42284548" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i336]" time="0.317"><properties><property name="score" value="0.26977763" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602306 (title: Capacitor Voltage Balancing Control Algorithm for ) is an LLM-generated sample, misclassified as human-generated with confidence 0.26977763 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602306 (title: Capacitor Voltage Balancing Control Algorithm for ) is an LLM-generated sample, misclassified as human-generated with confidence 0.26977763
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i337]" time="0.355"><properties><property name="score" value="0.41023886" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602316 (title: Fast Electromagnetic Transient Model of Modular Mu) is an LLM-generated sample, misclassified as human-generated with confidence 0.41023886 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602316 (title: Fast Electromagnetic Transient Model of Modular Mu) is an LLM-generated sample, misclassified as human-generated with confidence 0.41023886
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i338]" time="0.349"><properties><property name="score" value="0.03362114" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i339]" time="0.290"><properties><property name="score" value="1.119267" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602351 (title: Spiked Population Model based Abnormal State Detec) is an LLM-generated sample, misclassified as human-generated with confidence 1.119267 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602351 (title: Spiked Population Model based Abnormal State Detec) is an LLM-generated sample, misclassified as human-generated with confidence 1.119267
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i340]" time="0.339"><properties><property name="score" value="1.4747751" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602424 (title: VLC and D2D Heterogeneous Network Optimization: A ) is an LLM-generated sample, misclassified as human-generated with confidence 1.4747751 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602424 (title: VLC and D2D Heterogeneous Network Optimization: A ) is an LLM-generated sample, misclassified as human-generated with confidence 1.4747751
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i341]" time="0.330"><properties><property name="score" value="0.20052518" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i342]" time="0.325"><properties><property name="score" value="0.39470404" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602443 (title: Uplink Performance Analysis in D2D-Enabled Millime) is an LLM-generated sample, misclassified as human-generated with confidence 0.39470404 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602443 (title: Uplink Performance Analysis in D2D-Enabled Millime) is an LLM-generated sample, misclassified as human-generated with confidence 0.39470404
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i343]" time="0.348"><properties><property name="score" value="0.20188612" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i344]" time="0.349"><properties><property name="score" value="0.46065748" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602453 (title: Volunteers Dilemma Game Inspired Broadcast Scheme ) is an LLM-generated sample, misclassified as human-generated with confidence 0.46065748 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602453 (title: Volunteers Dilemma Game Inspired Broadcast Scheme ) is an LLM-generated sample, misclassified as human-generated with confidence 0.46065748
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i345]" time="0.314"><properties><property name="score" value="0.036934253" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602457 (title: Ratio-Based Multitemporal SAR Images Denoising: RA) is an LLM-generated sample, misclassified as human-generated with confidence 0.03693425 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602457 (title: Ratio-Based Multitemporal SAR Images Denoising: RA) is an LLM-generated sample, misclassified as human-generated with confidence 0.03693425
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i346]" time="0.329"><properties><property name="score" value="0.1242876" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i347]" time="0.478"><properties><property name="score" value="0.40814057" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602462 (title: Learning Dual Geometric Low-Rank Structure for Sem) is an LLM-generated sample, misclassified as human-generated with confidence 0.40814057 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602462 (title: Learning Dual Geometric Low-Rank Structure for Sem) is an LLM-generated sample, misclassified as human-generated with confidence 0.40814057
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i348]" time="0.375"><properties><property name="score" value="0.7191784" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602463 (title: High Efficient Deep Feature Extraction and Classif) is an LLM-generated sample, misclassified as human-generated with confidence 0.7191784 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602463 (title: High Efficient Deep Feature Extraction and Classif) is an LLM-generated sample, misclassified as human-generated with confidence 0.7191784
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i349]" time="0.002"><properties><property name="score" value="0.0" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602482 (title: Distributed Complex of Diagnostics and Monitoring ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602482 (title: Distributed Complex of Diagnostics and Monitoring ) is an LLM-generated sample, misclassified as human-generated with confidence 0.0
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i350]" time="0.365"><properties><property name="score" value="0.13947393" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i351]" time="0.355"><properties><property name="score" value="1.4098604" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602499 (title: Expert Systems as a Tool to Improve Efficiency of ) is an LLM-generated sample, misclassified as human-generated with confidence 1.4098604 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602499 (title: Expert Systems as a Tool to Improve Efficiency of ) is an LLM-generated sample, misclassified as human-generated with confidence 1.4098604
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i352]" time="0.319"><properties><property name="score" value="0.63337576" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602501 (title: Methods for Increasing the Accuracy of Geoacoustic) is an LLM-generated sample, misclassified as human-generated with confidence 0.63337576 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602501 (title: Methods for Increasing the Accuracy of Geoacoustic) is an LLM-generated sample, misclassified as human-generated with confidence 0.63337576
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i353]" time="0.358"><properties><property name="score" value="0.0092959395" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i354]" time="0.318"><properties><property name="score" value="0.13063607" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i355]" time="0.328"><properties><property name="score" value="0.109724164" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i356]" time="0.323"><properties><property name="score" value="0.011088732" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i357]" time="0.323"><properties><property name="score" value="0.034029108" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i358]" time="0.336"><properties><property name="score" value="0.08482678" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i359]" time="0.310"><properties><property name="score" value="0.09956013" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i360]" time="0.325"><properties><property name="score" value="2.234747" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602680 (title: The Challenges in ML-Based Security for SDN) is an LLM-generated sample, misclassified as human-generated with confidence 2.234747 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602680 (title: The Challenges in ML-Based Security for SDN) is an LLM-generated sample, misclassified as human-generated with confidence 2.234747
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i361]" time="0.279"><properties><property name="score" value="0.02812384" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i362]" time="0.342"><properties><property name="score" value="0.7975276" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602709 (title: Two-Cascade Extremum Seeking Systems for Nonlinear) is an LLM-generated sample, misclassified as human-generated with confidence 0.7975276 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602709 (title: Two-Cascade Extremum Seeking Systems for Nonlinear) is an LLM-generated sample, misclassified as human-generated with confidence 0.7975276
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i363]" time="0.399"><properties><property name="score" value="0.20249543" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i364]" time="0.327"><properties><property name="score" value="1.9521031" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602750 (title: Experimental Validation of Super-Resolution Beamfo) is an LLM-generated sample, misclassified as human-generated with confidence 1.9521031 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602750 (title: Experimental Validation of Super-Resolution Beamfo) is an LLM-generated sample, misclassified as human-generated with confidence 1.9521031
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i365]" time="0.295"><properties><property name="score" value="0.006155485" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i366]" time="0.303"><properties><property name="score" value="0.525937" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i367]" time="0.285"><properties><property name="score" value="0.355214" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i368]" time="0.314"><properties><property name="score" value="0.6283134" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i369]" time="0.281"><properties><property name="score" value="0.09954432" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i370]" time="0.345"><properties><property name="score" value="0.13515042" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i371]" time="0.327"><properties><property name="score" value="0.07859495" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i372]" time="0.359"><properties><property name="score" value="0.16796535" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i373]" time="0.318"><properties><property name="score" value="0.054035492" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i374]" time="0.272"><properties><property name="score" value="0.79232216" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i375]" time="0.307"><properties><property name="score" value="0.1618035" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i376]" time="0.307"><properties><property name="score" value="0.10450423" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i377]" time="1.380"><properties><property name="score" value="0.024247859" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i378]" time="0.332"><properties><property name="score" value="0.03449086" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i379]" time="1.729"><properties><property name="score" value="0.20713241" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602890 (title: Intelligent Decision-Making Systems for Monitoring) is an LLM-generated sample, misclassified as human-generated with confidence 0.20713241 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602890 (title: Intelligent Decision-Making Systems for Monitoring) is an LLM-generated sample, misclassified as human-generated with confidence 0.20713241
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i380]" time="0.314"><properties><property name="score" value="0.02912532" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i381]" time="0.335"><properties><property name="score" value="0.34689808" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602894 (title: Development of Standalone Deep Learning Module for) is an LLM-generated sample, misclassified as human-generated with confidence 0.34689808 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602894 (title: Development of Standalone Deep Learning Module for) is an LLM-generated sample, misclassified as human-generated with confidence 0.34689808
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i382]" time="0.324"><properties><property name="score" value="2.0121899" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602898 (title: Recognition and Use of Emotions in Games) is an LLM-generated sample, misclassified as human-generated with confidence 2.0121899 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602898 (title: Recognition and Use of Emotions in Games) is an LLM-generated sample, misclassified as human-generated with confidence 2.0121899
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i383]" time="0.279"><properties><property name="score" value="1.1984314" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8602908 (title: A Forensic Pattern-Based Approach for Investigatio) is an LLM-generated sample, misclassified as human-generated with confidence 1.1984314 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8602908 (title: A Forensic Pattern-Based Approach for Investigatio) is an LLM-generated sample, misclassified as human-generated with confidence 1.1984314
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i384]" time="0.310"><properties><property name="score" value="0.048921842" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i385]" time="0.415"><properties><property name="score" value="0.06393653" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i386]" time="0.299"><properties><property name="score" value="0.16883704" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i387]" time="0.285"><properties><property name="score" value="0.4585455" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i388]" time="0.252"><properties><property name="score" value="0.027861185" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i389]" time="0.295"><properties><property name="score" value="0.7422148" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603018 (title: Post-Verification Debugging and Rectification of F) is an LLM-generated sample, misclassified as human-generated with confidence 0.7422148 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603018 (title: Post-Verification Debugging and Rectification of F) is an LLM-generated sample, misclassified as human-generated with confidence 0.7422148
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i390]" time="0.429"><properties><property name="score" value="0.107612476" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i391]" time="0.332"><properties><property name="score" value="0.5902821" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i392]" time="0.368"><properties><property name="score" value="0.22836034" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603101 (title: Transient Joule Heating in PrMnO3 RRAM enables ReL) is an LLM-generated sample, misclassified as human-generated with confidence 0.22836034 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603101 (title: Transient Joule Heating in PrMnO3 RRAM enables ReL) is an LLM-generated sample, misclassified as human-generated with confidence 0.22836034
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i393]" time="0.321"><properties><property name="score" value="0.9552038" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603147 (title: UPSARA: A Model-Driven Approach for Performance An) is an LLM-generated sample, misclassified as human-generated with confidence 0.9552038 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603147 (title: UPSARA: A Model-Driven Approach for Performance An) is an LLM-generated sample, misclassified as human-generated with confidence 0.9552038
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i394]" time="0.291"><properties><property name="score" value="0.5388713" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603148 (title: Hierarchical and Frequency-Aware Model Predictive ) is an LLM-generated sample, misclassified as human-generated with confidence 0.5388713 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603148 (title: Hierarchical and Frequency-Aware Model Predictive ) is an LLM-generated sample, misclassified as human-generated with confidence 0.5388713
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i395]" time="0.301"><properties><property name="score" value="0.6812958" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i396]" time="0.301"><properties><property name="score" value="0.02348579" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i397]" time="0.365"><properties><property name="score" value="0.5612571" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603152 (title: Combining VM Preemption Schemes to Improve Vertica) is an LLM-generated sample, misclassified as human-generated with confidence 0.5612571 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603152 (title: Combining VM Preemption Schemes to Improve Vertica) is an LLM-generated sample, misclassified as human-generated with confidence 0.5612571
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i398]" time="0.360"><properties><property name="score" value="0.94937" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603153 (title: Tromino: Demand and DRF Aware Multi-Tenant Queue M) is an LLM-generated sample, misclassified as human-generated with confidence 0.94937 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603153 (title: Tromino: Demand and DRF Aware Multi-Tenant Queue M) is an LLM-generated sample, misclassified as human-generated with confidence 0.94937
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i399]" time="0.289"><properties><property name="score" value="0.28543687" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i400]" time="0.296"><properties><property name="score" value="0.13678434" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603155 (title: Scheduling Scientific Workflows on Clouds Using a ) is an LLM-generated sample, misclassified as human-generated with confidence 0.13678434 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603155 (title: Scheduling Scientific Workflows on Clouds Using a ) is an LLM-generated sample, misclassified as human-generated with confidence 0.13678434
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i401]" time="0.337"><properties><property name="score" value="0.28759968" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603156 (title: Task Runtime Prediction in Scientific Workflows Us) is an LLM-generated sample, misclassified as human-generated with confidence 0.28759968 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603156 (title: Task Runtime Prediction in Scientific Workflows Us) is an LLM-generated sample, misclassified as human-generated with confidence 0.28759968
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i402]" time="0.368"><properties><property name="score" value="1.2224904" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603157 (title: Energy-Efficient and SLA-Aware Virtual Machine Sel) is an LLM-generated sample, misclassified as human-generated with confidence 1.2224904 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603157 (title: Energy-Efficient and SLA-Aware Virtual Machine Sel) is an LLM-generated sample, misclassified as human-generated with confidence 1.2224904
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i403]" time="0.269"><properties><property name="score" value="0.23327124" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i404]" time="0.335"><properties><property name="score" value="0.87515014" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603159 (title: Joint Load-Balancing and Energy-Aware Virtual Mach) is an LLM-generated sample, misclassified as human-generated with confidence 0.87515014 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603159 (title: Joint Load-Balancing and Energy-Aware Virtual Mach) is an LLM-generated sample, misclassified as human-generated with confidence 0.87515014
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i405]" time="0.278"><properties><property name="score" value="0.11434819" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i406]" time="0.304"><properties><property name="score" value="1.9304609" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i407]" time="0.276"><properties><property name="score" value="0.12965527" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i408]" time="0.343"><properties><property name="score" value="0.040751934" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i409]" time="0.401"><properties><property name="score" value="0.17370835" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i410]" time="0.317"><properties><property name="score" value="0.9671781" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603165 (title: Confluence: Adaptive Spatiotemporal Data Integrati) is an LLM-generated sample, misclassified as human-generated with confidence 0.9671781 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603165 (title: Confluence: Adaptive Spatiotemporal Data Integrati) is an LLM-generated sample, misclassified as human-generated with confidence 0.9671781
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i411]" time="0.371"><properties><property name="score" value="1.8088013" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603169 (title: Return on Investment for Three Cyberinfrastructure) is an LLM-generated sample, misclassified as human-generated with confidence 1.8088013 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603169 (title: Return on Investment for Three Cyberinfrastructure) is an LLM-generated sample, misclassified as human-generated with confidence 1.8088013
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i412]" time="0.334"><properties><property name="score" value="0.23065269" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i413]" time="0.370"><properties><property name="score" value="0.14396648" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i414]" time="0.305"><properties><property name="score" value="0.73401123" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i415]" time="0.331"><properties><property name="score" value="0.32183266" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603190 (title: RIM: Robust Intersection Management for Connected ) is an LLM-generated sample, misclassified as human-generated with confidence 0.32183266 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603190 (title: RIM: Robust Intersection Management for Connected ) is an LLM-generated sample, misclassified as human-generated with confidence 0.32183266
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i416]" time="0.357"><properties><property name="score" value="0.10267819" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i417]" time="0.320"><properties><property name="score" value="0.18454762" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i418]" time="0.330"><properties><property name="score" value="3.3594415" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603206 (title: Work-in-Progress: Real-Time Modeling for Intrusion) is an LLM-generated sample, misclassified as human-generated with confidence 3.3594415 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603206 (title: Work-in-Progress: Real-Time Modeling for Intrusion) is an LLM-generated sample, misclassified as human-generated with confidence 3.3594415
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i419]" time="0.421"><properties><property name="score" value="0.5042827" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i420]" time="0.386"><properties><property name="score" value="0.28997073" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603210 (title: Work-in-Progress: Towards Real-Time Smart City Com) is an LLM-generated sample, misclassified as human-generated with confidence 0.28997073 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603210 (title: Work-in-Progress: Towards Real-Time Smart City Com) is an LLM-generated sample, misclassified as human-generated with confidence 0.28997073
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i421]" time="0.578"><properties><property name="score" value="0.09604661" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i422]" time="0.360"><properties><property name="score" value="2.1536796" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603215 (title: A Generic Coq Proof of Typical Worst-Case Analysis) is an LLM-generated sample, misclassified as human-generated with confidence 2.1536796 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603215 (title: A Generic Coq Proof of Typical Worst-Case Analysis) is an LLM-generated sample, misclassified as human-generated with confidence 2.1536796
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i423]" time="0.352"><properties><property name="score" value="0.08525489" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i424]" time="0.373"><properties><property name="score" value="0.09727152" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i425]" time="0.325"><properties><property name="score" value="0.46922976" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i426]" time="0.328"><properties><property name="score" value="0.14493474" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i427]" time="0.337"><properties><property name="score" value="0.288101" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i428]" time="0.392"><properties><property name="score" value="0.41850388" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i429]" time="0.364"><properties><property name="score" value="1.509442" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603253 (title: Malignancy Classification of Lung Nodule Based on ) is an LLM-generated sample, misclassified as human-generated with confidence 1.509442 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603253 (title: Malignancy Classification of Lung Nodule Based on ) is an LLM-generated sample, misclassified as human-generated with confidence 1.509442
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i430]" time="0.294"><properties><property name="score" value="0.48456243" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i431]" time="0.295"><properties><property name="score" value="1.0008056" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603259 (title: REXplore: A Sketch Based Interactive Explorer for ) is an LLM-generated sample, misclassified as human-generated with confidence 1.0008056 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603259 (title: REXplore: A Sketch Based Interactive Explorer for ) is an LLM-generated sample, misclassified as human-generated with confidence 1.0008056
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i432]" time="0.324"><properties><property name="score" value="0.8182185" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603260 (title: Tile-Based Rate Assignment for 360-Degree Video Ba) is an LLM-generated sample, misclassified as human-generated with confidence 0.8182185 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603260 (title: Tile-Based Rate Assignment for 360-Degree Video Ba) is an LLM-generated sample, misclassified as human-generated with confidence 0.8182185
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i433]" time="0.299"><properties><property name="score" value="2.4530985" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603261 (title: Content-Based Effectiveness Prediction of Video Ad) is an LLM-generated sample, misclassified as human-generated with confidence 2.4530985 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603261 (title: Content-Based Effectiveness Prediction of Video Ad) is an LLM-generated sample, misclassified as human-generated with confidence 2.4530985
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i434]" time="0.279"><properties><property name="score" value="1.2430512" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i435]" time="0.652"><properties><property name="score" value="0.42063534" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i436]" time="0.325"><properties><property name="score" value="0.93276423" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603266 (title: Deep Reinforcement Learning with Parameterized Act) is an LLM-generated sample, misclassified as human-generated with confidence 0.93276423 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603266 (title: Deep Reinforcement Learning with Parameterized Act) is an LLM-generated sample, misclassified as human-generated with confidence 0.93276423
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i437]" time="0.345"><properties><property name="score" value="0.6396938" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i438]" time="0.323"><properties><property name="score" value="1.0797864" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i439]" time="0.304"><properties><property name="score" value="0.011135563" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603277 (title: MyLipper: A Personalized System for Speech Reconst) is an LLM-generated sample, misclassified as human-generated with confidence 0.01113556 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603277 (title: MyLipper: A Personalized System for Speech Reconst) is an LLM-generated sample, misclassified as human-generated with confidence 0.01113556
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i440]" time="0.384"><properties><property name="score" value="0.026996046" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i441]" time="0.344"><properties><property name="score" value="0.6907212" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i442]" time="0.325"><properties><property name="score" value="0.92547214" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603294 (title: Towards Improved Human Action Recognition Using Co) is an LLM-generated sample, misclassified as human-generated with confidence 0.92547214 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603294 (title: Towards Improved Human Action Recognition Using Co) is an LLM-generated sample, misclassified as human-generated with confidence 0.92547214
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i443]" time="0.308"><properties><property name="score" value="0.124267414" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i444]" time="0.334"><properties><property name="score" value="0.6099977" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i445]" time="0.411"><properties><property name="score" value="0.18039107" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i446]" time="0.314"><properties><property name="score" value="0.5231517" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i447]" time="0.280"><properties><property name="score" value="0.9647804" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603305 (title: Discriminative Robust Gaze Estimation Using Kernel) is an LLM-generated sample, misclassified as human-generated with confidence 0.9647804 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603305 (title: Discriminative Robust Gaze Estimation Using Kernel) is an LLM-generated sample, misclassified as human-generated with confidence 0.9647804
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i448]" time="0.939"><properties><property name="score" value="0.119195044" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i449]" time="0.265"><properties><property name="score" value="0.77348727" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i450]" time="0.274"><properties><property name="score" value="0.41398776" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i451]" time="0.269"><properties><property name="score" value="1.6070672" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603319 (title: Cluster-Based Anomaly Detection in Condition Monit) is an LLM-generated sample, misclassified as human-generated with confidence 1.6070672 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603319 (title: Cluster-Based Anomaly Detection in Condition Monit) is an LLM-generated sample, misclassified as human-generated with confidence 1.6070672
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i452]" time="0.316"><properties><property name="score" value="0.2484748" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603322 (title: A Class Incremental Learning Approach Based on Aut) is an LLM-generated sample, misclassified as human-generated with confidence 0.2484748 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603322 (title: A Class Incremental Learning Approach Based on Aut) is an LLM-generated sample, misclassified as human-generated with confidence 0.2484748
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i453]" time="0.280"><properties><property name="score" value="0.06660718" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i454]" time="0.336"><properties><property name="score" value="0.2649379" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i455]" time="0.311"><properties><property name="score" value="0.50920093" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603334 (title: Fault Diagnosis and RUL Prediction Strategy Based ) is an LLM-generated sample, misclassified as human-generated with confidence 0.50920093 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603334 (title: Fault Diagnosis and RUL Prediction Strategy Based ) is an LLM-generated sample, misclassified as human-generated with confidence 0.50920093
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i456]" time="0.325"><properties><property name="score" value="0.50837505" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i457]" time="0.291"><properties><property name="score" value="0.039983135" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i458]" time="0.294"><properties><property name="score" value="0.025420357" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i459]" time="0.286"><properties><property name="score" value="0.058274426" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i460]" time="0.291"><properties><property name="score" value="0.15721758" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i461]" time="0.311"><properties><property name="score" value="0.6286029" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603350 (title: Modeling Research of Electrochemical Migration Fai) is an LLM-generated sample, misclassified as human-generated with confidence 0.6286029 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603350 (title: Modeling Research of Electrochemical Migration Fai) is an LLM-generated sample, misclassified as human-generated with confidence 0.6286029
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i462]" time="0.314"><properties><property name="score" value="0.55899465" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i463]" time="0.299"><properties><property name="score" value="0.7454119" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i464]" time="0.335"><properties><property name="score" value="0.70098376" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i465]" time="0.399"><properties><property name="score" value="0.49269" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i466]" time="0.323"><properties><property name="score" value="0.71301115" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603371 (title: Fault Detection Method Based on the Condition Indi) is an LLM-generated sample, misclassified as human-generated with confidence 0.71301115 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603371 (title: Fault Detection Method Based on the Condition Indi) is an LLM-generated sample, misclassified as human-generated with confidence 0.71301115
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i467]" time="0.305"><properties><property name="score" value="0.05473446" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i468]" time="0.309"><properties><property name="score" value="0.53525215" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i469]" time="0.303"><properties><property name="score" value="0.46649423" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603378 (title: Remaining Useful Life Prediction of Wind Turbine G) is an LLM-generated sample, misclassified as human-generated with confidence 0.46649423 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603378 (title: Remaining Useful Life Prediction of Wind Turbine G) is an LLM-generated sample, misclassified as human-generated with confidence 0.46649423
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i470]" time="0.279"><properties><property name="score" value="0.23219606" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i471]" time="0.313"><properties><property name="score" value="0.05483771" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i472]" time="0.296"><properties><property name="score" value="0.058653582" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i473]" time="0.347"><properties><property name="score" value="0.1433851" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603394 (title: Application of Adaptive Mono-Stable Stochastic Res) is an LLM-generated sample, misclassified as human-generated with confidence 0.1433851 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603394 (title: Application of Adaptive Mono-Stable Stochastic Res) is an LLM-generated sample, misclassified as human-generated with confidence 0.1433851
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i474]" time="0.337"><properties><property name="score" value="0.3401196" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603395 (title: Remaining Useful Lifetime Prediction of Nonlinear ) is an LLM-generated sample, misclassified as human-generated with confidence 0.3401196 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603395 (title: Remaining Useful Lifetime Prediction of Nonlinear ) is an LLM-generated sample, misclassified as human-generated with confidence 0.3401196
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i475]" time="0.350"><properties><property name="score" value="0.3157611" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603398 (title: Diesel Engine Fault Diagnosis Based on Singular Va) is an LLM-generated sample, misclassified as human-generated with confidence 0.3157611 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603398 (title: Diesel Engine Fault Diagnosis Based on Singular Va) is an LLM-generated sample, misclassified as human-generated with confidence 0.3157611
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i476]" time="0.313"><properties><property name="score" value="0.09811898" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i477]" time="0.311"><properties><property name="score" value="0.45030457" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603406 (title: Fault Diagnosis of Asynchronous Motors Based on LS) is an LLM-generated sample, misclassified as human-generated with confidence 0.45030457 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603406 (title: Fault Diagnosis of Asynchronous Motors Based on LS) is an LLM-generated sample, misclassified as human-generated with confidence 0.45030457
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i478]" time="0.358"><properties><property name="score" value="0.9900666" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i479]" time="0.305"><properties><property name="score" value="0.19192785" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i480]" time="0.317"><properties><property name="score" value="0.2988849" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i481]" time="0.279"><properties><property name="score" value="0.8514557" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603424 (title: Optimization of Fault Monitoring Method Based on A) is an LLM-generated sample, misclassified as human-generated with confidence 0.8514557 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603424 (title: Optimization of Fault Monitoring Method Based on A) is an LLM-generated sample, misclassified as human-generated with confidence 0.8514557
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i482]" time="0.298"><properties><property name="score" value="0.13009413" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i483]" time="0.421"><properties><property name="score" value="0.96438235" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603431 (title: Three-Level Inverter Fault Detection and Diagnosis) is an LLM-generated sample, misclassified as human-generated with confidence 0.96438235 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603431 (title: Three-Level Inverter Fault Detection and Diagnosis) is an LLM-generated sample, misclassified as human-generated with confidence 0.96438235
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i484]" time="0.307"><properties><property name="score" value="0.828322" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i485]" time="0.295"><properties><property name="score" value="0.102498144" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i486]" time="0.323"><properties><property name="score" value="0.012945067" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i487]" time="0.326"><properties><property name="score" value="0.060821354" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i488]" time="0.297"><properties><property name="score" value="0.25208864" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i489]" time="0.319"><properties><property name="score" value="0.08966518" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i490]" time="0.296"><properties><property name="score" value="1.3090124" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603479 (title: A Method of Fault Diagnosis for Rotary Equipment B) is an LLM-generated sample, misclassified as human-generated with confidence 1.3090124 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603479 (title: A Method of Fault Diagnosis for Rotary Equipment B) is an LLM-generated sample, misclassified as human-generated with confidence 1.3090124
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i491]" time="0.316"><properties><property name="score" value="0.95881295" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i492]" time="0.288"><properties><property name="score" value="0.27146608" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i493]" time="0.334"><properties><property name="score" value="0.10262554" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i494]" time="0.311"><properties><property name="score" value="0.058529135" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i495]" time="0.329"><properties><property name="score" value="1.6621932" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603501 (title: Lithium-Ion Battery Remaining Useful Life Prognost) is an LLM-generated sample, misclassified as human-generated with confidence 1.6621932 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603501 (title: Lithium-Ion Battery Remaining Useful Life Prognost) is an LLM-generated sample, misclassified as human-generated with confidence 1.6621932
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i496]" time="0.329"><properties><property name="score" value="0.3417071" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i497]" time="0.317"><properties><property name="score" value="0.3724472" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603512 (title: Condition Based Monitoring of Machine Using Mamdan) is an LLM-generated sample, misclassified as human-generated with confidence 0.3724472 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603512 (title: Condition Based Monitoring of Machine Using Mamdan) is an LLM-generated sample, misclassified as human-generated with confidence 0.3724472
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i498]" time="0.398"><properties><property name="score" value="0.7195723" /></properties></testcase><testcase classname="test_openai_detect" name="test_cheat_polish_jsonl[i499]" time="0.440"><properties><property name="score" value="0.73901725" /></properties><failure message="AssertionError: samples/ieee-chatgpt-polish.jsonl:8603529 (title: Application of Variational Auto-Encoder in Mechani) is an LLM-generated sample, misclassified as human-generated with confidence 0.73901725 assert 'Human' == 'AI' - AI + Human">E AssertionError: samples/ieee-chatgpt-polish.jsonl:8603529 (title: Application of Variational Auto-Encoder in Mechani) is an LLM-generated sample, misclassified as human-generated with confidence 0.73901725
|
||
assert 'Human' == 'AI'
|
||
- AI
|
||
+ Human</failure></testcase></testsuite></testsuites> |