{"id":"W4389559236","doi":"10.2196/50373","title":"AI-Enabled Medical Education: Threads of Change, Promising Futures, and Risky Realities Across Four Potential Future Worlds","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Engineering ethics; Health care; Autonomy; Public relations; Sociology; Knowledge management; Political science; Psychology; Engineering; Computer science; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00124307,0.0002142183,0.0003917709,0.0002728416,0.0003083082,0.00004662327,0.0001882678,0.0005781956,0.001142772],"category_scores_gemma":[0.001495138,0.0001846011,0.00009158174,0.0009070692,0.000297935,0.000243259,0.00007453831,0.0006575935,0.00004978128],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001377818,"about_ca_system_score_gemma":0.007743082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001904115,"about_ca_topic_score_gemma":0.000564519,"domain_scores_codex":[0.9968448,0.0001412612,0.0007522887,0.0004331713,0.001342815,0.0004857089],"domain_scores_gemma":[0.9977843,0.0001170504,0.0002143132,0.0003902162,0.0005970083,0.0008971512],"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":[0.0001914342,0.0008340503,0.01469195,0.001015815,0.00003638537,0.00001115398,0.0227399,2.33637e-7,0.00004665933,0.001986408,0.1032652,0.8551808],"study_design_scores_gemma":[0.00107187,0.001028126,0.4723281,0.006778337,0.0002994751,0.001239042,0.2288997,0.003113465,0.00171241,0.02123147,0.2611785,0.00111948],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8035028,0.001732099,0.00003856608,0.1877597,0.005432967,0.0009705375,0.000006716983,0.0001362067,0.0004204407],"genre_scores_gemma":[0.9700909,0.002456209,0.0001882489,0.009809796,0.01419633,0.0007192687,0.0004220699,0.00003979836,0.002077344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8540613,"threshold_uncertainty_score":0.9997703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09443296181870102,"score_gpt":0.4631091434658297,"score_spread":0.3686761816471286,"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."}}