{"id":"W4309829711","doi":"10.1093/cjres/rsac043","title":"COVID-19 vaccines: a geographic, social and policy view of vaccination efforts in Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"Cambridge Journal of Regions Economy and Society","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network","funders":"","keywords":"Vaccination; Disadvantaged; Pandemic; Equity (law); Coronavirus disease 2019 (COVID-19); Political science; Economic growth; Public health; Medicine; Infectious disease (medical specialty); Virology; Disease; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001239177,0.0001269358,0.0005686579,0.000093399,0.000401981,0.00001063459,0.0001186028,0.00005498796,0.00004477986],"category_scores_gemma":[0.0006827989,0.0001131197,0.0002006609,0.0001978932,0.00006079052,0.00009410252,0.0001596938,0.0003727079,1.828478e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012817,"about_ca_system_score_gemma":0.00186482,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4893325,"about_ca_topic_score_gemma":0.5763906,"domain_scores_codex":[0.9987816,0.0001444397,0.0006334621,0.0001480902,0.0001090755,0.0001833604],"domain_scores_gemma":[0.998036,0.001030487,0.0006258069,0.0000829213,0.00007406852,0.0001507226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009661703,0.000235108,0.6259106,0.0008098367,0.0005554958,0.00005275787,0.008843052,0.0001338351,0.000005867088,0.1371459,0.2241922,0.002018713],"study_design_scores_gemma":[0.00251057,0.0002408219,0.5850894,0.00003766803,0.000133914,0.0002489582,0.006319945,0.0001188278,0.000003014969,0.04675568,0.3582449,0.0002962559],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980312,0.001434038,0.0004764714,0.01717062,0.00006006885,0.0002120748,0.00001789293,0.000005955192,0.0003108555],"genre_scores_gemma":[0.9944984,0.001008284,0.0002744681,0.004018112,0.0000706024,0.0000166266,0.00000212181,0.000006728344,0.0001046116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1340527,"threshold_uncertainty_score":0.5140681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08704690374637661,"score_gpt":0.3432075278395063,"score_spread":0.2561606240931297,"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."}}