{"id":"W2135415712","doi":"10.3109/0142159x.2011.577123","title":"Admission selection criteria as predictors of outcomes in an undergraduate medical course: A prospective study","year":2011,"lang":"en","type":"article","venue":"Medical Teacher","topic":"Medical Education and Admissions","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Aptitude; Test (biology); Selection (genetic algorithm); Predictive validity; Predictive power; Educational measurement; Academic achievement; Psychology; Medicine; Medical education; Clinical psychology; Mathematics education; Curriculum; Developmental psychology; Computer science; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002639677,0.000347009,0.0003340241,0.001067049,0.0008379826,0.00133338,0.0005334732,0.0006794983,0.001782615],"category_scores_gemma":[0.0111891,0.0004036008,0.0003967662,0.001220118,0.0005550021,0.000924471,0.001165855,0.001746216,0.0005259685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006175055,"about_ca_system_score_gemma":0.001048621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004962815,"about_ca_topic_score_gemma":0.005848188,"domain_scores_codex":[0.9983942,0.0004822171,0.00013021,0.0001572382,0.0004620729,0.000374132],"domain_scores_gemma":[0.990239,0.001837409,0.003931771,0.0003119958,0.0007613869,0.002918442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006373517,0.0001555312,0.9989384,0.000002385925,0.000006037245,0.00003160612,0.0001270721,0.00001295093,0.0000314144,0.000007914903,0.0000394282,0.0005835305],"study_design_scores_gemma":[0.000006751844,0.0004535542,0.9985687,0.000007578071,0.00000717422,0.0001070584,0.0005025616,0.0001777513,0.00005403801,0.00001585819,0.00009317334,0.000005742929],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997025,0.00004417715,0.0000347432,0.00002290965,0.000004272555,0.00001333853,0.00004111948,0.000001209461,0.0001356159],"genre_scores_gemma":[0.9996306,0.00003311894,0.00004448928,0.0000132256,0.000007144645,0.00001382448,0.0001071847,0.000001498936,0.0001490064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004962815,"threshold_uncertainty_score":0.01396012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0503530725367782,"score_gpt":0.4099198168979873,"score_spread":0.3595667443612091,"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."}}