{"id":"W7072252175","doi":"","title":"(In)Visible Minorities in Canadian Health Data and Research","year":2015,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health equity; Health care; Public health; Neglect; Health data; Social determinants of health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00176486,0.0001274076,0.0001877115,0.001672936,0.0001644813,0.0003633371,0.002796389,0.0001222365,0.00000126566],"category_scores_gemma":[0.00007396829,0.0001490189,0.00001174659,0.001592215,0.0001442901,0.002878143,0.001779347,0.000541228,0.00005008544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005547601,"about_ca_system_score_gemma":0.000970846,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0271278,"about_ca_topic_score_gemma":0.8016198,"domain_scores_codex":[0.9979727,0.0002224664,0.0001743674,0.0006454086,0.0002995006,0.0006855723],"domain_scores_gemma":[0.9979768,0.00007923025,0.00004512859,0.001388084,0.0001074617,0.0004032492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000382226,0.00002879552,0.9896899,0.00001265573,0.000002885219,0.0001652948,0.0005960303,0.000003059101,0.000006118548,0.007127197,0.0000171082,0.002347158],"study_design_scores_gemma":[0.0007041137,0.0001111303,0.9606789,0.0000893967,0.000001595848,0.00003245729,0.001174332,0.00003702637,0.00007723464,0.004548245,0.03229192,0.0002536852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991027,0.0006097257,0.0007354058,0.006867914,0.00006852617,0.0002484377,0.00002503341,0.00008788132,0.0003300949],"genre_scores_gemma":[0.9978613,0.0001688035,0.000780815,0.0002384297,0.00001578078,0.000001790013,0.00001116143,0.000008514902,0.0009133525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.774492,"threshold_uncertainty_score":0.9793506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2970229435281995,"score_gpt":0.3971895285798386,"score_spread":0.1001665850516392,"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."}}