{"id":"W3127912923","doi":"10.1016/j.envint.2021.106422","title":"Re: Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis (Environment International 146 (2021) 106316)","year":2021,"lang":"en","type":"letter","venue":"Environment International","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; McGill University Health Centre; Carleton University; Montreal General Hospital","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Term (time); Air pollution; Environmental science; 2019-20 coronavirus outbreak; Pollution; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Geography; Environmental health; Medicine; Outbreak; Virology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002269859,0.001172984,0.001595057,0.001908924,0.0003567386,0.0002448633,0.001023945,0.001134867,0.01486488],"category_scores_gemma":[0.0006518783,0.001246566,0.0005589743,0.00100036,0.0006028303,0.0004531726,0.001876693,0.002072889,0.0001238362],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006583587,"about_ca_system_score_gemma":0.0002048191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01149664,"about_ca_topic_score_gemma":0.07434037,"domain_scores_codex":[0.988992,0.001327202,0.002056123,0.003046745,0.003224979,0.001352997],"domain_scores_gemma":[0.9957385,0.0004967575,0.0007191821,0.001213698,0.00002117228,0.001810697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005556482,0.000732101,0.9287747,0.0001344973,0.001423212,0.001648731,0.004135061,0.05553254,0.0001371001,0.000008336027,0.002843563,0.004074539],"study_design_scores_gemma":[0.003378143,0.0004192796,0.9583468,0.00008744551,0.001046818,0.00004276518,0.00006854295,0.002902206,0.00001912135,0.0001456904,0.03242351,0.001119614],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7823304,0.0001744676,0.02676831,0.1855455,0.0005090692,0.001453863,0.003081428,0.00004761907,0.00008930926],"genre_scores_gemma":[0.8757973,0.001335367,0.0004929694,0.1071878,0.001798774,0.0005104355,0.01231276,0.00007755455,0.0004870326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09346689,"threshold_uncertainty_score":0.9989984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0395741338826803,"score_gpt":0.3206047862639045,"score_spread":0.2810306523812242,"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."}}