{"id":"W2773810921","doi":"10.18865/ed.27.4.371","title":"Inequalities in Hypertension and Diabetes in Canada: Intersections between Racial Identity, Gender, and Income","year":2017,"lang":"en","type":"article","venue":"Ethnicity & Disease","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Université de Montréal","funders":"","keywords":"Decile; Demography; Diabetes mellitus; Intersectionality; Medicine; Health equity; Odds; Odds ratio; Gerontology; Public health; Internal medicine; Endocrinology; Logistic regression; Sociology; Gender studies","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001361753,0.0003966039,0.0006757099,0.002415481,0.004216257,0.001899294,0.001342592,0.0005298803,0.002977863],"category_scores_gemma":[0.003887548,0.000345847,0.001375705,0.007053973,0.0009705168,0.0006534045,0.002351672,0.001245854,0.0001855777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04312764,"about_ca_system_score_gemma":0.08498607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9987018,"about_ca_topic_score_gemma":0.9991891,"domain_scores_codex":[0.9984108,0.0001737939,0.0000856413,0.0002111955,0.0004204821,0.0006979292],"domain_scores_gemma":[0.9969207,0.0002696061,0.0005279899,0.0001391329,0.001432965,0.0007095286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009782415,0.00003146819,0.9873369,0.00005800711,0.0001279916,0.0000692932,0.0009530465,0.0001865541,0.00006716486,0.0005761592,0.002014199,0.008481483],"study_design_scores_gemma":[0.000009423759,0.00001132641,0.9955893,0.00009816141,0.0001006375,0.00003351078,0.001595429,0.0005931283,0.00005090056,0.0002359263,0.001660596,0.0000217208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704391,0.006226774,0.0005256434,0.004409536,0.0000669353,0.00007018063,0.01093599,0.00003865632,0.00728703],"genre_scores_gemma":[0.9937973,0.001782814,0.0004923696,0.0003990661,0.00001708049,0.00002718782,0.002236889,0.00001102907,0.001236282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04312764,"threshold_uncertainty_score":0.3129144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09066264621603011,"score_gpt":0.3610845575907966,"score_spread":0.2704219113747665,"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."}}