{"id":"W3183525205","doi":"10.1016/j.annepidem.2021.07.007","title":"Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study","year":2021,"lang":"en","type":"article","venue":"Annals of Epidemiology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Health and Long Term Care; University of Manitoba; Toronto Public Health; Sunnybrook Health Science Centre; University of Toronto; University Health Network; University of Calgary; McGill University; Institute for Clinical Evaluative Sciences; Public Health Ontario; St. Michael's Hospital","funders":"","keywords":"Socioeconomic status; Gini coefficient; Demography; Lorenz curve; Confidence interval; Population; Observational study; Medicine; Health equity; Economic inequality; Geography; Inequality; Public health; Sociology","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":[0.001320552,0.0006704381,0.0007097516,0.001919059,0.003892067,0.001648401,0.001925215,0.0006628897,0.002675078],"category_scores_gemma":[0.004717946,0.0006872352,0.001084037,0.007579863,0.001396042,0.000674617,0.001854518,0.001134354,0.0003440708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05465838,"about_ca_system_score_gemma":0.054373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9963648,"about_ca_topic_score_gemma":0.9972813,"domain_scores_codex":[0.9979749,0.0002278882,0.0002367299,0.0004191359,0.0005482447,0.0005930879],"domain_scores_gemma":[0.993193,0.0003870041,0.001672508,0.0004682546,0.002817456,0.001461785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005226535,0.00001806888,0.9954687,0.00006988644,0.00009699494,0.00008136439,0.0008626046,0.0001095007,0.00007224293,0.0001244471,0.001738873,0.001305016],"study_design_scores_gemma":[0.00001040632,0.00002154412,0.9962662,0.00008618001,0.00007088853,0.0000905464,0.001648952,0.0004443115,0.00004645739,0.00004935252,0.001244705,0.00002054453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712493,0.002125604,0.0005979274,0.0007484531,0.00003047832,0.0001845279,0.02203356,0.00003362709,0.002996628],"genre_scores_gemma":[0.9935467,0.0007674088,0.0003779223,0.0001939934,0.00001135645,0.00006251124,0.004254009,0.00001102191,0.0007751064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05465838,"threshold_uncertainty_score":0.3965762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.543599516400753,"score_gpt":0.5207887466749413,"score_spread":0.02281076972581164,"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."}}