{"id":"W4396525721","doi":"10.2196/51757","title":"Understanding Health Care Students’ Perceptions, Beliefs, and Attitudes Toward AI-Powered Language Models: Cross-Sectional Study","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Health care; Perception; Medical education; Psychology; Peer review; Medicine; Computer science; Political science; World Wide Web","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":[0.005328949,0.0002602829,0.0004835519,0.0008408705,0.000920443,0.001517204,0.0004489594,0.0008330183,0.003508475],"category_scores_gemma":[0.01026105,0.0006149391,0.0006335878,0.0007108221,0.0006229986,0.001313213,0.001181732,0.001796922,0.0006343951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006640514,"about_ca_system_score_gemma":0.00100007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003938072,"about_ca_topic_score_gemma":0.005715175,"domain_scores_codex":[0.9983236,0.0006523587,0.0001744117,0.0001439542,0.0004183256,0.0002872416],"domain_scores_gemma":[0.9926063,0.002559232,0.002262332,0.0003449499,0.001091505,0.001135789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006725528,0.001516517,0.9847854,0.00005346087,0.00004570867,0.00007670773,0.008868559,0.00003262333,0.0002002155,0.00003725072,0.0001864004,0.004129888],"study_design_scores_gemma":[0.00002544422,0.001758957,0.9654669,0.0001023835,0.00006391279,0.0002385562,0.03065464,0.0005120033,0.0002133283,0.00007986143,0.0008628292,0.00002112975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995097,0.00004143956,0.00005148853,0.00006517667,0.00000266618,0.00002909476,0.00003709605,8.305172e-7,0.00026255],"genre_scores_gemma":[0.9991779,0.0001230907,0.0001676146,0.0001571482,0.000006048704,0.00006660034,0.00006493816,0.000001203607,0.0002354839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005328949,"threshold_uncertainty_score":0.02818251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2376865746454844,"score_gpt":0.549405276044209,"score_spread":0.3117187013987246,"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."}}