{"id":"W3199079561","doi":"10.1503/cmaj.1095960","title":"Minority of doctors block CMA diversity overhaul","year":2021,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Pharmaceutical industry and healthcare","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversity (politics); Boosting (machine learning); Democracy; Inclusion (mineral); Shadow (psychology); Racial diversity; Political science; Medicine; Computer science; Psychology; Sociology; Law; Artificial intelligence; Gender studies; Ethnic group","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":[],"consensus_categories":[],"category_scores_codex":[0.02454584,0.0003816789,0.0006586243,0.001593741,0.02969664,0.009008285,0.002226857,0.008211732,0.02310757],"category_scores_gemma":[0.06524357,0.0006063123,0.0007749401,0.001319671,0.009413697,0.003133155,0.01493981,0.01406265,0.003900695],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02118274,"about_ca_system_score_gemma":0.0759253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.190459,"about_ca_topic_score_gemma":0.2788923,"domain_scores_codex":[0.9658988,0.004803639,0.0006732668,0.002435276,0.01195826,0.01423076],"domain_scores_gemma":[0.9120845,0.01099549,0.003723619,0.00262514,0.01818416,0.05238707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005427587,0.0002117094,0.02599723,0.0002557037,0.00008117752,0.0007319619,0.02627206,0.0002149488,0.00370454,0.2226442,0.6131777,0.1061661],"study_design_scores_gemma":[0.0002006643,0.0001677217,0.02064523,0.0002878127,0.00002854623,0.00028062,0.01143184,0.0003690112,0.0007524269,0.0145956,0.9511746,0.00006597798],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.05145884,0.002147089,0.001790125,0.7964595,0.007191761,0.0002503749,0.0002409681,0.000103605,0.1403577],"genre_scores_gemma":[0.5462516,0.001174112,0.001396336,0.3143505,0.003993088,0.0001769262,0.0001536325,0.00009962035,0.1324042],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9788173,"threshold_uncertainty_score":0.3787007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2171659372731029,"score_gpt":0.4729969941975394,"score_spread":0.2558310569244365,"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."}}