{"id":"W3123151084","doi":"","title":"Ethnic Inequality in Canada: Economic and Health Dimensions","year":2007,"lang":"en","type":"article","venue":"Social and Economic Dimensions of an Aging Population Research Papers","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Ethnic group; Disadvantaged; Immigration; Inequality; Census; Demographic economics; Context (archaeology); Population; Social inequality; Socioeconomic status; Geography; Political science; Gender studies; Demography; Sociology; Economic growth; Economics","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":[0.0008872253,0.0002060385,0.0003948537,0.003896329,0.005159752,0.002041147,0.0006369562,0.0002993297,0.003849285],"category_scores_gemma":[0.003236792,0.00011605,0.0003537071,0.007961238,0.001027419,0.0005567025,0.001614918,0.0006207121,0.0001321609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0236277,"about_ca_system_score_gemma":0.03484772,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9879509,"about_ca_topic_score_gemma":0.9938073,"domain_scores_codex":[0.998794,0.00009308637,0.00004804969,0.00008198102,0.0005081454,0.0004746592],"domain_scores_gemma":[0.9979621,0.0002061581,0.0003387223,0.00005849636,0.0007853596,0.0006491469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008667812,0.00005868595,0.9588322,0.00007082901,0.00007199292,0.0002147343,0.004217785,0.0002795862,0.0001054773,0.005493673,0.003917943,0.02665045],"study_design_scores_gemma":[0.000002660013,0.000007413778,0.9903949,0.00006765083,0.00001949678,0.00005626923,0.004091153,0.0002299993,0.00003417644,0.0004469765,0.004638746,0.00001060566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454294,0.003788043,0.0002879024,0.005217734,0.00005690762,0.00005096834,0.0042854,0.00001064066,0.04087298],"genre_scores_gemma":[0.9957005,0.001210092,0.0001534208,0.0002373873,0.00001818932,0.00001254795,0.000738798,0.000004871061,0.001924028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0236277,"threshold_uncertainty_score":0.1714318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2204325303163736,"score_gpt":0.5001981081757177,"score_spread":0.2797655778593442,"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."}}