{"id":"W4285585368","doi":"10.1016/j.lana.2022.100326","title":"It's high time Canada started collecting race-based performance data on medical training and careers","year":2022,"lang":"en","type":"review","venue":"The Lancet Regional Health - Americas","topic":"Medical Education and Admissions","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Training (meteorology); Race (biology); Medical education; Computer science; Operations research; Aeronautics; Medicine; Engineering; Geography; Sociology; Gender studies; Meteorology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001640058,0.0003192016,0.001941397,0.0001048197,0.0006725111,0.0000142409,0.0006387462,0.0001063741,0.004910686],"category_scores_gemma":[0.002825123,0.0001989526,0.00007612522,0.0006698907,0.0002567549,0.00002218594,0.0001458235,0.001727845,0.00001337286],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000718748,"about_ca_system_score_gemma":0.06080711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03395004,"about_ca_topic_score_gemma":0.004393184,"domain_scores_codex":[0.9961067,0.0005880362,0.0006579986,0.0005519307,0.001501421,0.0005939464],"domain_scores_gemma":[0.9943633,0.00249516,0.0005125319,0.0009591051,0.00003555023,0.001634331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003668399,0.00003756039,0.00000237849,0.002607932,0.0000490059,0.0000245359,0.0002071636,0.000001118398,3.726425e-9,0.000009606525,0.4529635,0.5440605],"study_design_scores_gemma":[0.0005884927,0.0002750133,0.00002481303,0.008165412,0.0001311083,0.0002553461,0.0003728617,0.001237304,7.33771e-9,0.000001174639,0.988774,0.0001744926],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000618995,0.6943857,0.000007469283,0.3029804,0.0004305799,0.0009319368,0.0002371629,0.00006097776,0.0009038291],"genre_scores_gemma":[0.00007034725,0.8794979,0.0001724186,0.1154172,0.0009324719,0.0000918197,0.002384212,0.00004424951,0.001389342],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5438861,"threshold_uncertainty_score":0.995999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3785310314505114,"score_gpt":0.4663689009539491,"score_spread":0.08783786950343775,"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."}}