{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005393892,0.00008149743,0.0002049526,0.00007186775,0.0006628504,0.0001240519,0.0001559155,0.00004722728,0.00002466564],"category_scores_gemma":[0.00111741,0.00008340404,0.00002086104,0.00006180873,0.0002344099,0.0005239255,0.0001804657,0.0001568983,8.908289e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002716744,"about_ca_system_score_gemma":0.0007980781,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9833656,"about_ca_topic_score_gemma":0.9979077,"domain_scores_codex":[0.9988614,0.0001981266,0.0002087739,0.0001760764,0.0002218792,0.0003337996],"domain_scores_gemma":[0.9991922,0.0002307366,0.00006619964,0.0001470965,0.00002665597,0.0003371453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006347273,0.000009918146,0.9949975,0.00008285212,0.000003089247,0.00001433504,0.002387228,5.839567e-7,5.302853e-7,0.001681887,0.00005276276,0.0007629644],"study_design_scores_gemma":[0.0002664971,0.000003565354,0.9906045,0.00006767589,0.000009565801,4.015861e-8,0.005296633,0.00003773573,7.891235e-7,0.003351904,0.0002634382,0.00009769784],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948459,0.0006598654,0.000001585139,0.003655532,0.0002506246,0.000152402,0.00004899759,0.00001029934,0.0003747786],"genre_scores_gemma":[0.9987491,0.0003513348,0.000005014168,0.0006971582,0.0001318848,0.00001074233,0.000002947351,0.000005094452,0.00004666356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0145421,"threshold_uncertainty_score":0.5098176,"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."}}