{"id":"W4318595373","doi":"10.9734/jsrr/2023/v29i11720","title":"Policy Review: Academic Cheating in Online Examinations during the COVID-19 Pandemic","year":2023,"lang":"en","type":"article","venue":"Journal of Scientific Research and Reports","topic":"Smart Systems and Machine Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Cheating; Pandemic; Academic integrity; Coronavirus disease 2019 (COVID-19); Misconduct; Isolation (microbiology); Academic dishonesty; Psychology; Mainstream; The Internet; Medical education; Internet privacy; Public relations; Political science; Computer science; Medicine; Social psychology; World Wide Web; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02471008,0.00006983931,0.0001851713,0.001193768,0.0008132908,0.0002654079,0.0005151943,0.00004605536,0.000004282522],"category_scores_gemma":[0.007141577,0.00004188345,0.00005108883,0.003650009,0.000212346,0.0004310769,0.0004257735,0.001008631,0.000003532251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001558181,"about_ca_system_score_gemma":0.0008000198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001528499,"about_ca_topic_score_gemma":0.00006231335,"domain_scores_codex":[0.9970129,0.0003891622,0.0007695389,0.0002803726,0.001142465,0.0004055389],"domain_scores_gemma":[0.9981496,0.0004856921,0.000405338,0.0003572614,0.0003338477,0.0002682077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008190907,0.0001026059,0.895871,0.001428351,0.00003296343,0.003891265,0.00662553,0.0008282973,0.0279146,0.001302419,0.03756167,0.02443314],"study_design_scores_gemma":[0.0006461116,0.0001624105,0.8396387,0.002849645,0.000006722184,0.02334962,0.00143731,0.005308183,0.0001397151,0.01139304,0.1148049,0.0002637104],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760076,0.004971027,0.0003417442,0.01773107,0.0005270627,0.0002387914,8.070538e-7,0.00002987941,0.0001520413],"genre_scores_gemma":[0.9902608,0.004214,0.00018166,0.0001691134,0.0003226385,0.000007840267,0.000001815868,0.000006029858,0.004836042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07724324,"threshold_uncertainty_score":0.856407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1492370218645163,"score_gpt":0.4616240283417291,"score_spread":0.3123870064772128,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}