{"id":"W2100927586","doi":"10.1007/bf03403966","title":"Health inequalities, deprivation, immigration and aboriginality in Canada: a geographic perspective.","year":2011,"lang":"en","type":"article","venue":"PubMed","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Census; Inequality; Metropolitan area; Geography; Demography; Ethnic group; Demographic economics; Sociology; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005329771,0.000215379,0.0003881945,0.002511188,0.003732078,0.001665213,0.0005691146,0.0005161274,0.003087632],"category_scores_gemma":[0.001953215,0.0001466813,0.000430719,0.007629015,0.0008581647,0.0005774895,0.001239975,0.0009576789,0.0001031684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02147122,"about_ca_system_score_gemma":0.06175232,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957712,"about_ca_topic_score_gemma":0.998413,"domain_scores_codex":[0.9993698,0.00007247301,0.0000308995,0.00003816307,0.0001668405,0.0003218948],"domain_scores_gemma":[0.9989626,0.0001095262,0.0001483909,0.00001734738,0.0003878362,0.0003742083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002006687,0.0001056079,0.8769209,0.0008709329,0.0003410958,0.0006160659,0.01123314,0.0007578416,0.0001868321,0.009385892,0.02275666,0.0766243],"study_design_scores_gemma":[0.000009911684,0.00002827205,0.9735929,0.0006246222,0.0001851108,0.0001487507,0.0133608,0.0002927271,0.00005067008,0.001008093,0.01067042,0.00002777265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8426864,0.08571486,0.0003444768,0.03207375,0.0003109368,0.00008143452,0.01214812,0.00002307078,0.02661701],"genre_scores_gemma":[0.966344,0.02998996,0.0002498324,0.0006600122,0.0001000957,0.00002217232,0.001065593,0.00000468104,0.001563728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02147122,"threshold_uncertainty_score":0.1557854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05093791069277438,"score_gpt":0.2911640778414899,"score_spread":0.2402261671487155,"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."}}