{"id":"W2913267158","doi":"10.1097/acm.0000000000002636","title":"Tracking Indigenous Applicants Through the Admissions Process of a Socially Accountable Medical School","year":2019,"lang":"en","type":"article","venue":"Academic Medicine","topic":"Medical Education and Admissions","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"NOSM University; Laurentian University","funders":"","keywords":"Indigenous; Demographics; Medicine; Tracking (education); Population; Demography; Logistic regression; Medical school; Family medicine; Gerontology; Psychology; Medical education; Environmental health; Sociology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001165291,0.0002240486,0.0006644118,0.00009832082,0.0001785995,0.000004047889,0.0005795899,0.0004966499,0.05704059],"category_scores_gemma":[0.02196731,0.0001205385,0.00008102957,0.0006797207,0.0003504907,0.0001197341,0.00007301501,0.001921631,0.0001979509],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007589622,"about_ca_system_score_gemma":0.01007712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001379555,"about_ca_topic_score_gemma":0.000003248334,"domain_scores_codex":[0.9963793,0.00008160966,0.0008581153,0.0003724151,0.001823916,0.0004847121],"domain_scores_gemma":[0.9958422,0.0005264633,0.0003256899,0.0004833213,0.0002415637,0.002580775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001005349,0.001029159,0.1333714,0.00384642,0.0008796967,0.000109469,0.2077717,0.00001448347,0.04392679,0.01545089,0.531193,0.06140159],"study_design_scores_gemma":[0.01658185,0.001597341,0.03162093,0.01563796,0.001179761,0.001187272,0.1250853,0.0006312357,0.007140048,0.01821922,0.7800788,0.001040201],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7932295,0.003416742,0.0004139657,0.1688751,0.0009542959,0.002205129,0.000007563366,0.0001479722,0.03074976],"genre_scores_gemma":[0.9455183,0.001142474,0.00006855164,0.04325821,0.001272063,0.00006998163,0.00003331716,0.00003577213,0.00860133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2488859,"threshold_uncertainty_score":0.9955348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04146911625220073,"score_gpt":0.4188138805084863,"score_spread":0.3773447642562855,"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."}}