{"id":"W2470723556","doi":"10.4172/plastic-surgery.1000943","title":"Selecting the best and brightest: A comparison of residency match processes in the United States and Canada","year":2015,"lang":"en","type":"article","venue":"Plastic Surgery","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Likert scale; Medical education; Grading (engineering); Psychology; Scale (ratio); United States Medical Licensing Examination; Personnel selection; Family medicine; Medicine; Medical school; Management; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001295282,0.00004193029,0.0001118046,0.00004411401,0.0001809083,0.00004053133,0.0001094252,0.00001917411,0.000004274797],"category_scores_gemma":[0.007804504,0.00002512349,0.000004432273,0.0004124515,0.0002206525,0.00005065893,0.00002270307,0.00008142214,2.672166e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002336807,"about_ca_system_score_gemma":0.0008113993,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8687707,"about_ca_topic_score_gemma":0.9265493,"domain_scores_codex":[0.9991192,0.0001539652,0.0001116496,0.00006809244,0.0004177614,0.0001293561],"domain_scores_gemma":[0.9843315,0.01540133,0.00005707481,0.00003990546,0.0001222766,0.000047854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001121954,0.00001524982,0.9500927,0.0000415583,0.000005051453,0.000008530578,0.03789305,0.00002749096,5.419257e-7,0.00009137807,0.01160697,0.0002062908],"study_design_scores_gemma":[0.0001867577,0.00004148131,0.0989209,0.0002755522,0.00005144158,0.000005737309,0.884608,0.0002753457,0.00003416692,0.0005690604,0.01491284,0.0001187623],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972391,0.0005282129,0.00000404872,0.001625676,0.0002183232,0.00004498714,0.000003469426,0.000004470459,0.0003316722],"genre_scores_gemma":[0.9996848,0.0001557037,0.000003843385,0.00009208489,0.00003751648,0.000001691539,0.000003762524,0.000001535228,0.00001907087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8511718,"threshold_uncertainty_score":0.9343284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06639071557292564,"score_gpt":0.2914616210007344,"score_spread":0.2250709054278087,"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."}}