{"id":"W4310102422","doi":"10.1073/pnas.2209490119","title":"Impact of lowering fine particulate matter from major emission sources on mortality in Canada: A nationwide causal analysis","year":2022,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Environment and Climate Change Canada; McGill University; Statistics Canada; Public Health Ontario; University of Toronto; Health Canada","funders":"","keywords":"Particulates; Environmental health; Demography; Psychological intervention; Public health; Cohort; Population; Medicine; Environmental science; Geography; Ecology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005721741,0.001179559,0.001389212,0.001669238,0.003302664,0.001465479,0.002393489,0.001170429,0.005555457],"category_scores_gemma":[0.01434722,0.0007267832,0.006589251,0.003073715,0.0009892517,0.0005924205,0.002246154,0.002096935,0.0002889131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04706947,"about_ca_system_score_gemma":0.133836,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953661,"about_ca_topic_score_gemma":0.9944495,"domain_scores_codex":[0.9954823,0.0009802108,0.0003654141,0.0007471836,0.001026597,0.001398299],"domain_scores_gemma":[0.9887733,0.00205435,0.001283588,0.0008671402,0.005743849,0.001277775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001883548,0.0002976952,0.9497513,0.0009257796,0.006248772,0.0003274244,0.0004286123,0.004382329,0.0001948541,0.002418414,0.01086533,0.02227594],"study_design_scores_gemma":[0.001250719,0.0005760249,0.938441,0.001176477,0.01948921,0.0002581994,0.001300372,0.0203329,0.0004801713,0.002221618,0.01431365,0.0001596363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8867956,0.01520044,0.005154346,0.008626865,0.0004888286,0.00139919,0.0723984,0.0002941929,0.009642075],"genre_scores_gemma":[0.978135,0.00381073,0.003248561,0.001112497,0.00007848583,0.0003066187,0.01048625,0.00003351364,0.002788437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04706947,"threshold_uncertainty_score":0.3415145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04747474795406267,"score_gpt":0.3319395807230332,"score_spread":0.2844648327689705,"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."}}