{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005216331,0.0009415299,0.0007980239,0.0006426093,0.001421335,0.001312112,0.001765405,0.001906252,0.01920654],"category_scores_gemma":[0.009317334,0.0006714509,0.0008064209,0.0005384583,0.000656457,0.001357907,0.002808616,0.003487205,0.006573559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009755503,"about_ca_system_score_gemma":0.004665453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005443758,"about_ca_topic_score_gemma":0.006094431,"domain_scores_codex":[0.9984596,0.0005618592,0.00005150148,0.0002149164,0.0001990867,0.0005130391],"domain_scores_gemma":[0.9861193,0.002957945,0.0002090579,0.00114993,0.001787392,0.007776411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.02665956,0.4002743,0.03095396,0.0008945346,0.0001796143,0.00193841,0.008258423,0.006304229,0.01834255,0.001504654,0.05490103,0.4497887],"study_design_scores_gemma":[0.04721419,0.4021955,0.2587903,0.0006467232,0.0005535764,0.001357713,0.01057235,0.03610621,0.04970824,0.006917195,0.1855283,0.0004097566],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699069,0.0001173936,0.008462315,0.001663261,0.0004357514,0.008126628,0.001780228,0.001824771,0.007682753],"genre_scores_gemma":[0.9146838,0.0003653762,0.04184586,0.002112725,0.0002508711,0.009894843,0.004779477,0.0002849161,0.02578215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01920654,"threshold_uncertainty_score":0.0642522,"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."}}