{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001604493,0.000189288,0.0003660122,0.0003672783,0.0003074725,0.00004363001,0.000182758,0.0004261619,0.001927617],"category_scores_gemma":[0.0106381,0.0001716506,0.0001602607,0.0008975902,0.000159748,0.0002121112,0.00005147693,0.0006683354,0.0004480116],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002011147,"about_ca_system_score_gemma":0.0131615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001432919,"about_ca_topic_score_gemma":0.0005476386,"domain_scores_codex":[0.9967023,0.000234549,0.0011603,0.0005485398,0.0009805728,0.0003737439],"domain_scores_gemma":[0.995575,0.001605279,0.0002033852,0.0004874517,0.0009191541,0.001209699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001859124,0.008160138,0.1296498,0.0001316059,0.00007261184,0.0001023102,0.01710037,0.000001181437,0.000002005559,0.0002913249,0.07336737,0.7709354],"study_design_scores_gemma":[0.002487107,0.007662321,0.3183671,0.002373995,0.0007131036,0.005126332,0.3998957,0.03214252,0.0001520854,0.008333376,0.221349,0.001397428],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952306,0.00006058925,0.0002442688,0.03707378,0.006655413,0.003003233,0.000005225175,0.0002026804,0.0004488285],"genre_scores_gemma":[0.984116,0.00004263264,0.0001866035,0.00582024,0.005612948,0.001855963,0.0002816544,0.00003910213,0.002044877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.769538,"threshold_uncertainty_score":0.9989848,"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."}}