{"id":"W3000115556","doi":"10.1017/cem.2019.460","title":"A transparent and defensible process for applicant selection within a Canadian emergency medicine residency program","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Matching (statistics); Scrutiny; Attendance; Selection (genetic algorithm); Medicine; Process (computing); Variance (accounting); Personnel selection; Medical education; Family medicine; Computer science; Statistics; Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1812534,0.000971664,0.001012044,0.005315706,0.02531998,0.01807406,0.007954127,0.008566103,0.01038904],"category_scores_gemma":[0.2850322,0.002402708,0.001483617,0.002672878,0.006256019,0.006093116,0.01653242,0.01013045,0.005862676],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03037674,"about_ca_system_score_gemma":0.2647934,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2480769,"about_ca_topic_score_gemma":0.4418045,"domain_scores_codex":[0.7959982,0.07832946,0.0113067,0.01159107,0.08237214,0.02040241],"domain_scores_gemma":[0.6651039,0.1275273,0.02185105,0.05225316,0.09215754,0.04110714],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001198786,0.002334322,0.03618689,0.0004877906,0.0001573347,0.003026969,0.03273383,0.008334884,0.01297731,0.07769605,0.2871007,0.5377651],"study_design_scores_gemma":[0.0009045938,0.002238874,0.165252,0.002491514,0.0002107296,0.001696725,0.02877333,0.04987259,0.01253986,0.04841287,0.6856682,0.001938689],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1409633,0.0008316803,0.4740063,0.1520786,0.004371636,0.03478109,0.001524922,0.01467309,0.1767694],"genre_scores_gemma":[0.4698718,0.0004108328,0.4417972,0.01842328,0.0008283762,0.008836937,0.0008015253,0.0008765853,0.05815346],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9696233,"threshold_uncertainty_score":0.9585711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2045351857422056,"score_gpt":0.3965776377631395,"score_spread":0.1920424520209339,"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."}}