{"id":"W2943483591","doi":"10.1017/cem.2019.158","title":"MP23: Giving medical students what they deserve - a rigorous, equitable and defensible CaRMS selection process","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Hip and Femur Fractures","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"United States Medical Licensing Examination; Intraclass correlation; Medicine; Standardization; Raw data; Matching (statistics); Reliability (semiconductor); Curriculum; Medical education; Computer science; Statistics; Psychology; Medical school; Mathematics; Psychometrics; Clinical psychology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06761751,0.0006621548,0.000778787,0.002940044,0.008845707,0.008648939,0.003709816,0.006520293,0.08024916],"category_scores_gemma":[0.2285746,0.001030326,0.001015816,0.001250428,0.002902509,0.003820867,0.01461095,0.01041881,0.04234497],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004413559,"about_ca_system_score_gemma":0.03843402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003040525,"about_ca_topic_score_gemma":0.009882119,"domain_scores_codex":[0.937441,0.03131054,0.003236476,0.002259571,0.02126239,0.004490015],"domain_scores_gemma":[0.8156821,0.04899806,0.007272285,0.0162307,0.06161649,0.05020035],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007678758,0.0008378895,0.004923733,0.0002677886,0.00003366003,0.000574659,0.003515365,0.000502073,0.001776918,0.01134963,0.6856478,0.2898026],"study_design_scores_gemma":[0.0004594814,0.0009269064,0.01222108,0.0008695964,0.00004984297,0.001010297,0.006422039,0.002541618,0.003785606,0.02374003,0.9477325,0.000241005],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.06916986,0.0008762962,0.1370435,0.4940356,0.02349905,0.01719631,0.002216652,0.01378368,0.242179],"genre_scores_gemma":[0.277173,0.0009353817,0.2977856,0.1143541,0.009038298,0.01612708,0.001509003,0.004418367,0.2786593],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9969594,"threshold_uncertainty_score":0.3575999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04053128956002952,"score_gpt":0.3614836160341025,"score_spread":0.320952326474073,"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."}}