{"id":"W4406968543","doi":"10.36834/cmej.80775","title":"Bridging gaps in orthopedic residency admissions: embracing diversity beyond research metrics","year":2025,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bridging (networking); Diversity (politics); Data science; Medical education; Computer science; Medicine; Sociology; Computer security; Anthropology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1566013,0.0007643976,0.001562558,0.01033043,0.008912664,0.02193113,0.004540311,0.005744944,0.009676576],"category_scores_gemma":[0.4086354,0.0007078029,0.001126913,0.01072458,0.01125917,0.02666594,0.03911992,0.009067707,0.001346979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02058613,"about_ca_system_score_gemma":0.1167658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03580036,"about_ca_topic_score_gemma":0.07922086,"domain_scores_codex":[0.8613873,0.08692541,0.009702225,0.004534711,0.02951086,0.007939565],"domain_scores_gemma":[0.515101,0.3013591,0.03437471,0.02109819,0.07339577,0.05467112],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002253221,0.0002828531,0.05288358,0.003659626,0.0002709814,0.0002558099,0.02346935,0.001089181,0.0005445448,0.08230672,0.121648,0.713364],"study_design_scores_gemma":[0.0001806594,0.0008427853,0.09456962,0.02739621,0.0003497945,0.0006942189,0.06740304,0.00352797,0.001642857,0.3439211,0.4589753,0.0004965775],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0263893,0.02925559,0.01626505,0.8928373,0.004448215,0.0003278063,0.0006195112,0.0002775362,0.02957971],"genre_scores_gemma":[0.7536198,0.03894817,0.0717402,0.1134809,0.01098528,0.001471563,0.001282093,0.0004145493,0.008057433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8433987,"threshold_uncertainty_score":0.8281966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04571026184497338,"score_gpt":0.3967749292406724,"score_spread":0.351064667395699,"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."}}