{"id":"W4390631601","doi":"10.2196/51247","title":"Artificial Intelligence in Medicine: Cross-Sectional Study Among Medical Students on Application, Education, and Ethical Aspects","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Curriculum; Medical education; Medical ethics; Cross-sectional study; Psychology; Family medicine; Medicine; Pedagogy; Pathology","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":[0.003675296,0.0002811957,0.000382713,0.0006883531,0.0002009865,0.000168812,0.0004046681,0.0008673851,0.00200619],"category_scores_gemma":[0.005583566,0.0002387444,0.00006352478,0.001179831,0.0006387833,0.0001460608,0.00008297003,0.002140884,0.0003006434],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005061111,"about_ca_system_score_gemma":0.007083385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001954798,"about_ca_topic_score_gemma":0.0008842003,"domain_scores_codex":[0.9937178,0.0002523542,0.001498988,0.0009502146,0.003196158,0.000384445],"domain_scores_gemma":[0.9971729,0.0007749128,0.000122805,0.0004408471,0.0004531761,0.001035369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001082311,0.003890282,0.6181026,0.0002277665,0.00002593899,0.00001810676,0.004858591,0.000001488232,0.000007875134,0.02026749,0.003044471,0.3494471],"study_design_scores_gemma":[0.0000783513,0.0007573455,0.9600672,0.001325736,0.00003565475,0.0001432911,0.006266775,0.002344603,0.0000743544,0.02610619,0.002544629,0.0002558626],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530004,0.0006430663,0.0006093691,0.03831058,0.003826166,0.001924789,0.000001167944,0.0001509894,0.001533414],"genre_scores_gemma":[0.9878099,0.0001711679,0.00005121746,0.006374416,0.003671165,0.001459083,0.0001015526,0.00003854282,0.0003229873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3491913,"threshold_uncertainty_score":0.9989061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07736878108075156,"score_gpt":0.5312998261579426,"score_spread":0.453931045077191,"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."}}