{"id":"W4387829826","doi":"10.2196/49877","title":"ChatGPT Interactive Medical Simulations for Early Clinical Education: Case Study","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Curriculum; Test (biology); Creativity; Medical education; Medical physics; Medicine; Psychology","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":[0.004724784,0.0008562376,0.0003584187,0.000746439,0.001139633,0.00156778,0.002208838,0.00274685,0.006337913],"category_scores_gemma":[0.02084835,0.000460629,0.0008136771,0.0005755902,0.001423002,0.001049541,0.002919468,0.001519082,0.001655987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00146007,"about_ca_system_score_gemma":0.001383671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00207399,"about_ca_topic_score_gemma":0.003666515,"domain_scores_codex":[0.9963511,0.002730938,0.0001645618,0.0001355951,0.0003393118,0.0002783332],"domain_scores_gemma":[0.9775878,0.01796151,0.0005386479,0.001105225,0.0008387167,0.00196811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"case_report","study_design_scores_codex":[0.004646424,0.01243294,0.08462724,0.004818246,0.0002624803,0.1115566,0.07091998,0.2446932,0.0188873,0.01906039,0.046062,0.3820332],"study_design_scores_gemma":[0.001941795,0.01182953,0.05282306,0.00337756,0.0004500613,0.1001048,0.02787675,0.4787885,0.05458097,0.02051787,0.2467102,0.000998991],"study_design_candidate":"case_report","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8810923,0.001228263,0.08852735,0.002933093,0.0002214763,0.00192847,0.000652704,0.00214584,0.02127048],"genre_scores_gemma":[0.9292761,0.0006931119,0.06412637,0.0004840699,0.00006494497,0.0009039788,0.0003452964,0.0001964012,0.003909695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006337913,"threshold_uncertainty_score":0.02498734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2328928300421382,"score_gpt":0.6145299154526388,"score_spread":0.3816370854105006,"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."}}