{"id":"W2981099987","doi":"10.3390/su11205700","title":"Effect of Income Inequality on Health in Quebec: New Insights from Panel Data","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture; Université du Québec à Montréal; Université Laval","keywords":"Economic inequality; Inequality; Socioeconomic status; Demographic economics; Depression (economics); Mortality rate; Economics; Demography; Population; Mathematics; Sociology; Macroeconomics","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":[0.002079213,0.0002983243,0.000584414,0.001071484,0.001210961,0.001152774,0.0008326212,0.0005046935,0.003590025],"category_scores_gemma":[0.00371858,0.0001717842,0.000631112,0.002698159,0.0004355909,0.0005200395,0.0007162801,0.0006792532,0.0002012115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009183032,"about_ca_system_score_gemma":0.004739685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9846725,"about_ca_topic_score_gemma":0.9845071,"domain_scores_codex":[0.9990441,0.0004886489,0.00003551468,0.0001272055,0.00009781047,0.0002067938],"domain_scores_gemma":[0.9961441,0.001790278,0.0006685239,0.0003568339,0.0006789195,0.0003614082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001020349,0.00005819858,0.9866642,0.00003264206,0.0002691393,0.0001653388,0.0007123047,0.00371534,0.0001647596,0.0007837886,0.001587678,0.005744534],"study_design_scores_gemma":[0.00000816486,0.00002330482,0.9860513,0.00003857773,0.00008291948,0.00002194057,0.0007417371,0.01095772,0.00005242809,0.0002038255,0.00180112,0.000016867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850659,0.001321292,0.001137405,0.00105889,0.00001948336,0.00004072711,0.008819776,0.00002321072,0.002513255],"genre_scores_gemma":[0.9949163,0.0003522524,0.0005287557,0.0001448716,0.0000133757,0.00002229025,0.003223327,0.000005175563,0.0007936283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01532751,"threshold_uncertainty_score":0.06662786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03721884937222775,"score_gpt":0.3940459172138866,"score_spread":0.3568270678416589,"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."}}