{"id":"W4387337629","doi":"10.1016/j.cjca.2023.06.292","title":"DIFFERENTIAL IMPACT OF NEIGHBOURHOOD-LEVEL INCOME ON THE RISK OF CARDIOVASCULAR EVENT BETWEEN IMMIGRANTS AND LONG-TERM RESIDENTS IN ONTARIO","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Medicine; Socioeconomic status; Immigration; Neighbourhood (mathematics); Ethnic group; Demography; Cohort; Population; Incidence (geometry); Disease; Cohort study; Gerontology; Environmental health; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003884775,0.0002137406,0.0003931042,0.0006556857,0.003044697,0.001221063,0.0008333097,0.0004513704,0.002805847],"category_scores_gemma":[0.001865895,0.000291342,0.0007408519,0.00156608,0.0009595471,0.0004198412,0.001451344,0.0007040831,0.0002140136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01078175,"about_ca_system_score_gemma":0.01195362,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9680734,"about_ca_topic_score_gemma":0.9899431,"domain_scores_codex":[0.9993163,0.00008357119,0.00004758061,0.00009479109,0.0001279023,0.0003297978],"domain_scores_gemma":[0.9982882,0.0001049102,0.0003681669,0.00005110702,0.0004048943,0.0007826575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001403496,0.00002583352,0.9957266,0.00001660896,0.00004480188,0.0001257061,0.002021775,0.00003405277,0.0001141789,0.00009690624,0.0003183973,0.001334744],"study_design_scores_gemma":[0.000004156223,0.00001371812,0.9966515,0.00001453635,0.00001365736,0.00002916683,0.002977623,0.00004993468,0.000008780678,0.00002092225,0.0002110808,0.000004925514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980189,0.0001672312,0.00002487857,0.0002249851,0.000008474958,0.000005301446,0.0004192547,0.000001787581,0.001129309],"genre_scores_gemma":[0.9990393,0.00009728745,0.00002308361,0.00003473555,0.000004651347,0.000003767408,0.0001904122,0.00000170444,0.0006051475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03192657,"threshold_uncertainty_score":0.07822746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06581562447670404,"score_gpt":0.3475458377171912,"score_spread":0.2817302132404871,"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."}}