{"id":"W4401219689","doi":"10.2196/55933","title":"Impact of Large Language Models on Medical Education and Teaching Adaptations","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transformative learning; Health care; Engineering ethics; Quality (philosophy); Medical education; Psychology; Medicine; Pedagogy; Political science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008806683,0.0004913086,0.0002850561,0.000591394,0.0005243943,0.00272146,0.001406299,0.000665052,0.01000692],"category_scores_gemma":[0.07919209,0.0002502674,0.0005204069,0.0006036417,0.0007679723,0.00276012,0.00370147,0.001290987,0.001771554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002126777,"about_ca_system_score_gemma":0.002525091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002159385,"about_ca_topic_score_gemma":0.002398961,"domain_scores_codex":[0.9885526,0.008511515,0.0004346272,0.0009726682,0.001224166,0.0003045162],"domain_scores_gemma":[0.9314281,0.05473711,0.003226089,0.005820651,0.003483882,0.001304212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001526948,0.002668058,0.04215568,0.0009657061,0.0001050549,0.0005077914,0.01320773,0.02302975,0.007289623,0.011618,0.007994001,0.8889316],"study_design_scores_gemma":[0.001596702,0.007073417,0.1244737,0.004006108,0.00111,0.003928542,0.04063915,0.3561068,0.05819976,0.1089124,0.2934134,0.0005399526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.844246,0.0009633074,0.0879737,0.006556234,0.0004661601,0.0007302734,0.0006263771,0.003111024,0.05532693],"genre_scores_gemma":[0.9642172,0.0002149528,0.02978004,0.0006554147,0.00004583624,0.0003262685,0.0003234132,0.0002557726,0.004181088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01000692,"threshold_uncertainty_score":0.04657477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0760441078056383,"score_gpt":0.4898796924798277,"score_spread":0.4138355846741893,"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."}}