{"id":"W2010396941","doi":"10.1016/j.puhe.2009.04.012","title":"Community-level income inequality and mortality in Québec, Canada","year":2009,"lang":"en","type":"article","venue":"Public Health","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal; Institut National de Santé Publique du Québec","funders":"Canada Research Chairs; University of South Australia","keywords":"Decile; Demography; Economic inequality; Poisson regression; American Community Survey; Inequality; Mortality rate; Confidence interval; Medicine; Census; Population; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001115505,0.0004595332,0.0007798508,0.002315717,0.006145066,0.002363375,0.002179155,0.0009438664,0.00588771],"category_scores_gemma":[0.00354725,0.0003710271,0.001125533,0.005868156,0.0009956326,0.0007885097,0.001356679,0.001684022,0.0004295951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06337611,"about_ca_system_score_gemma":0.05619144,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.999196,"about_ca_topic_score_gemma":0.9995399,"domain_scores_codex":[0.9988235,0.0001494644,0.00009107807,0.0001415953,0.000257343,0.0005370919],"domain_scores_gemma":[0.9959984,0.0003021022,0.0005762194,0.00009217787,0.001633678,0.001397496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002158357,0.0002024974,0.9698435,0.00009931038,0.0002603999,0.0001973033,0.001346974,0.0007156918,0.00009553046,0.001208766,0.0122693,0.0135448],"study_design_scores_gemma":[0.00004050753,0.00002297703,0.9939516,0.0001631538,0.00007715496,0.0000408271,0.001702692,0.0007243159,0.00003861475,0.0001331287,0.00307828,0.00002666468],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9585869,0.005855048,0.0003105288,0.005451868,0.0001749323,0.0001035512,0.01777541,0.00004881128,0.011693],"genre_scores_gemma":[0.9909876,0.001444386,0.000225436,0.0004170132,0.00003279562,0.00004862398,0.002546529,0.00001334925,0.0042843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06337611,"threshold_uncertainty_score":0.459828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1675473086352133,"score_gpt":0.4071492854193759,"score_spread":0.2396019767841626,"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."}}