{"id":"W3081852946","doi":"10.1111/medu.14318","title":"Introductory machine learning for medical students: A pilot","year":2020,"lang":"en","type":"article","venue":"Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Columbia university; Medical school; Library science; Medicine; Sociology; Medical education; Media studies; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009783922,0.0001133054,0.0002214082,0.0000652215,0.0001270895,0.00002489749,0.0002372673,0.0001508362,0.00334762],"category_scores_gemma":[0.02325124,0.0000987625,0.00005831104,0.0002356892,0.00009022708,0.000064752,0.0000437139,0.0005302229,0.0001884522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001099908,"about_ca_system_score_gemma":0.00362762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002458685,"about_ca_topic_score_gemma":0.00003016308,"domain_scores_codex":[0.9975815,0.00008320945,0.0004774587,0.0003190719,0.00129494,0.0002437627],"domain_scores_gemma":[0.998472,0.0002355639,0.00008196762,0.0001423158,0.0002693592,0.0007987381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006790057,0.002378603,0.1376289,0.000646038,0.00005916321,0.000006513003,0.004665939,0.000002521062,0.0002258686,0.0008495716,0.1725934,0.6802644],"study_design_scores_gemma":[0.0006458093,0.003574134,0.01328552,0.0005193175,0.00013861,0.00008400423,0.003301204,0.0170965,0.001580809,0.000601963,0.9588314,0.0003407237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4284451,0.001567703,0.007357151,0.5574526,0.002990176,0.001116922,0.000001614204,0.0002025472,0.0008661596],"genre_scores_gemma":[0.9247611,0.0002796946,0.0004567951,0.06825864,0.005329866,0.0001809542,0.0002062003,0.00002503026,0.000501717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.786238,"threshold_uncertainty_score":0.9975635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1019210713808119,"score_gpt":0.4678451054234911,"score_spread":0.3659240340426791,"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."}}