{"id":"W2181531051","doi":"10.1289/ehp.1409276","title":"Ambient PM <sub>2.5</sub> , O <sub>3</sub> , and NO <sub>2</sub> Exposures and Associations with Mortality over 16 Years of Follow-Up in the Canadian Census Health and Environment Cohort (CanCHEC)","year":2015,"lang":"en","type":"article","venue":"Environmental Health Perspectives","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":559,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of British Columbia; Public Health Ontario; Dalhousie University; University of New Brunswick; University of Toronto; McGill University Health Centre; Carleton University; Environment and Climate Change Canada; Health Canada","funders":"","keywords":"Pollutant; Percentile; Nitrogen dioxide; Environmental health; Air pollution; Ozone; Environmental science; Particulates; Criteria air contaminants; Hazard ratio; Medicine; Air pollutants; Toxicology; Demography; Geography; Confidence interval; Meteorology; Chemistry; Statistics; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002311485,0.0004607229,0.0006874863,0.0001418397,0.0007649835,0.00006440417,0.0002050241,0.0002112137,0.0000220166],"category_scores_gemma":[0.00009379742,0.0004266468,0.00006800509,0.0002220225,0.001303215,0.0003919852,0.0001829801,0.0005953165,0.00003356548],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005498016,"about_ca_system_score_gemma":0.0004000686,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06115513,"about_ca_topic_score_gemma":0.1808169,"domain_scores_codex":[0.9951051,0.0008078043,0.0007772638,0.0009902058,0.001132663,0.001186909],"domain_scores_gemma":[0.9971037,0.0001841546,0.0005317876,0.0005061595,0.000008173368,0.001666012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002109534,0.0007594136,0.9222987,0.0001415424,0.0001003875,0.00001973532,0.05538182,0.0001273127,0.004496614,0.0002166372,0.003791995,0.01245488],"study_design_scores_gemma":[0.001841649,0.001295742,0.9783023,0.00006855783,0.00003147657,0.00002384215,0.01520606,0.00007752587,0.001566555,0.0002505175,0.0009323898,0.0004033981],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916144,0.002067269,0.00001746315,0.003573018,0.00009450434,0.001778364,0.0005432777,0.00002331833,0.0002883972],"genre_scores_gemma":[0.9906208,0.005686754,0.000145234,0.003218434,0.00007174194,0.0001014552,0.00009803518,0.00004937608,0.00000819647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1196618,"threshold_uncertainty_score":0.9998186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02891012358418923,"score_gpt":0.27806158127141,"score_spread":0.2491514576872207,"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."}}