{"id":"W4399542284","doi":"10.2196/56117","title":"A Use Case for Generative AI in Medical Education","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Generative grammar; Computer science; Artificial intelligence; Natural language processing","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":[0.003972138,0.0007181265,0.0004508492,0.001560781,0.001655755,0.007619516,0.002592725,0.005076929,0.0176166],"category_scores_gemma":[0.01242677,0.0006199276,0.001130531,0.001006173,0.003560988,0.003966119,0.00398011,0.003058913,0.004059511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00137858,"about_ca_system_score_gemma":0.001144182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005400257,"about_ca_topic_score_gemma":0.005664386,"domain_scores_codex":[0.9961675,0.002150383,0.0001758126,0.0002479795,0.001029541,0.0002288148],"domain_scores_gemma":[0.9869425,0.01022797,0.0001812257,0.001615717,0.0006420371,0.0003905077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004628089,0.0006153121,0.006637747,0.0006965052,0.0001004495,0.006553309,0.007659888,0.0176318,0.0156688,0.6456231,0.0260407,0.2723096],"study_design_scores_gemma":[0.0002362737,0.0002553508,0.001605032,0.0006521631,0.0001348304,0.005433453,0.002441504,0.235855,0.02612912,0.3644262,0.3627309,0.000100225],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04199967,0.00192341,0.7216439,0.01892575,0.00055883,0.0006336626,0.0004861866,0.009141112,0.2046874],"genre_scores_gemma":[0.4719187,0.001102384,0.4895949,0.002386263,0.0002006249,0.0003453621,0.0004532548,0.001362286,0.03263631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0176166,"threshold_uncertainty_score":0.05893338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139294354644328,"score_gpt":0.5354344051062581,"score_spread":0.3961400504619301,"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."}}