{"id":"W4416321751","doi":"10.2196/75911","title":"How AI Is Transforming Medical Education: Bibliometric Analysis","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Focus (optics); Work (physics); Generative grammar; MEDLINE","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01575162,0.000571114,0.001582628,0.1737169,0.001261841,0.006971906,0.000987481,0.0009124472,0.002395337],"category_scores_gemma":[0.1020529,0.0003326772,0.002143596,0.2411501,0.001223896,0.00552596,0.002638785,0.0006227472,0.000623432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003238661,"about_ca_system_score_gemma":0.005405979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00680003,"about_ca_topic_score_gemma":0.007316168,"domain_scores_codex":[0.9804614,0.004948911,0.004101667,0.001403543,0.008407061,0.0006774414],"domain_scores_gemma":[0.8866994,0.07279386,0.02212778,0.003341094,0.01372828,0.001309559],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002066086,0.0001145523,0.7291983,0.01376243,0.002323873,0.0004659439,0.004835792,0.002860844,0.0006704264,0.005978119,0.01153754,0.2280456],"study_design_scores_gemma":[0.00003923992,0.0001638547,0.9132794,0.004733586,0.002047523,0.001514181,0.009170417,0.01049314,0.0009759992,0.00761319,0.04981851,0.0001510076],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8063785,0.09166194,0.008051604,0.007335279,0.0002553831,0.001095294,0.04679074,0.0004535301,0.03797773],"genre_scores_gemma":[0.9572859,0.02627466,0.005892449,0.0001726738,0.0002778406,0.0004268867,0.008963166,0.00005240727,0.0006540425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9842484,"threshold_uncertainty_score":0.08330351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06028025079004887,"score_gpt":0.4852943621309886,"score_spread":0.4250141113409397,"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."}}