{"id":"W4400482813","doi":"10.55016/ojs/cpai.v6i1.76772","title":"Exploring Official Academic Integrity Data","year":2023,"lang":"en","type":"article","venue":"Canadian Perspectives on Academic Integrity","topic":"Academic integrity and plagiarism","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Research integrity; Data integrity; Academic integrity; Data science; Political science; Computer science; Computer security; Library science; Public relations","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.122998,0.0007589712,0.00150818,0.02804379,0.01979188,0.02486463,0.007253835,0.00276701,0.007235291],"category_scores_gemma":[0.4113631,0.001151426,0.0007165038,0.05038089,0.01074798,0.0080108,0.014152,0.006837558,0.002212897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1282292,"about_ca_system_score_gemma":0.3140534,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9347682,"about_ca_topic_score_gemma":0.9327211,"domain_scores_codex":[0.7486575,0.03745344,0.01782996,0.01139691,0.1641963,0.02046595],"domain_scores_gemma":[0.2975082,0.116968,0.06049988,0.06181426,0.4452365,0.01797314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003938118,0.0002867453,0.2171272,0.002552267,0.0002081496,0.001002682,0.1937861,0.001592983,0.00123156,0.2126731,0.1650085,0.2041368],"study_design_scores_gemma":[0.00003321896,0.00008298442,0.1313704,0.002523132,0.0000987893,0.0002084947,0.09981211,0.002190142,0.00205683,0.01669733,0.7446442,0.0002824038],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3047235,0.005357548,0.05732482,0.1112271,0.001692516,0.004917978,0.1797127,0.001827858,0.333216],"genre_scores_gemma":[0.839969,0.0048301,0.03908009,0.01018871,0.0004097382,0.003170285,0.05422402,0.0006445927,0.04748346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9347682,"threshold_uncertainty_score":0.9303724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2860422586479901,"score_gpt":0.3891125448216935,"score_spread":0.1030702861737034,"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."}}