{"id":"W7023889461","doi":"","title":"Plagiarism detection software and academic integrity :\\nthe canadian perspective","year":2005,"lang":"en","type":"article","venue":"E-LIS Repository (University of Naples Federico II)","topic":"Academic integrity and plagiarism","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Academic integrity; Plagiarism detection; Academic dishonesty; Academic institution; Work (physics); Software; Perspective (graphical); Institution; Service (business)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["research_integrity"],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":["research_integrity"],"domain":null,"study_design":"not_applicable","genre":"commentary","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01523443,0.0007441286,0.0009087637,0.01164618,0.04752715,0.02877949,0.004870739,0.007885047,0.01335769],"category_scores_gemma":[0.03719983,0.0008587287,0.0007364882,0.0195693,0.02953994,0.01175782,0.0068647,0.008558342,0.0009642082],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2620083,"about_ca_system_score_gemma":0.4217394,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944996,"about_ca_topic_score_gemma":0.996116,"domain_scores_codex":[0.9727525,0.005128507,0.0009386212,0.002046898,0.01212022,0.007013205],"domain_scores_gemma":[0.9066855,0.02056541,0.00588464,0.001670345,0.04709669,0.01809745],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001821138,0.0002045809,0.0481208,0.001919777,0.00008351538,0.001786189,0.09421698,0.0008592884,0.0009864538,0.4761737,0.2113395,0.164127],"study_design_scores_gemma":[0.00003372879,0.0001085618,0.05611128,0.002616934,0.0001221057,0.0006676406,0.1499252,0.001069674,0.0008656341,0.02598212,0.762124,0.0003732417],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04915347,0.05184072,0.0020499,0.6271443,0.001355864,0.0001354081,0.001063443,0.0001478038,0.2671091],"genre_scores_gemma":[0.7398593,0.1185772,0.005001979,0.07531787,0.0009603712,0.00009273375,0.0006795056,0.0001915425,0.0593195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.992115,"threshold_uncertainty_score":0.8559658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581698572582044,"score_gpt":0.2432584707279217,"score_spread":0.2274414850021013,"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."}}