{"id":"W4416247114","doi":"10.36834/cmej.82560","title":"The impact of artificial intelligence on case-based learning during pre-clerkship education","year":2025,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Michael's Hospital; Western University; University of Toronto","funders":"","keywords":"Applications of artificial intelligence; Artificial Intelligence System; Artificial psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.006448771,0.000195258,0.0002577261,0.001192012,0.000725464,0.00257024,0.0009955439,0.0006605627,0.004684541],"category_scores_gemma":[0.08834582,0.0001725785,0.0002493927,0.0006737065,0.000662399,0.001368908,0.001457414,0.000845326,0.0003679415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001655827,"about_ca_system_score_gemma":0.002410601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004576144,"about_ca_topic_score_gemma":0.006825791,"domain_scores_codex":[0.9921218,0.005404285,0.0003121776,0.0002704511,0.001596591,0.0002945466],"domain_scores_gemma":[0.8956035,0.09445223,0.002179191,0.001001937,0.00313863,0.003624509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002441154,0.008801817,0.1250868,0.000417941,0.0001049422,0.0009524397,0.01357079,0.004643208,0.001950832,0.003383448,0.003408426,0.8352382],"study_design_scores_gemma":[0.0006385735,0.008888578,0.8626468,0.001427687,0.000450542,0.002805592,0.02829327,0.04315923,0.006867202,0.01659928,0.02797101,0.0002522003],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583293,0.001503689,0.003030031,0.002511911,0.0001438493,0.0002062245,0.00007975847,0.00007854626,0.03411666],"genre_scores_gemma":[0.9963853,0.0004054872,0.00220814,0.00006889868,0.00002664293,0.00003158846,0.00002779339,0.00000817315,0.0008380356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006448771,"threshold_uncertainty_score":0.03410476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01652138906389119,"score_gpt":0.321794059517067,"score_spread":0.3052726704531758,"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."}}