{"id":"W4392793879","doi":"10.1097/ee9.0000000000000303","title":"Estimating the impacts of nonoptimal temperatures on mortality: A study in British Columbia, Canada, 2001–2021","year":2024,"lang":"en","type":"article","venue":"Environmental Epidemiology","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Royal Roads University; Government of British Columbia; University of Victoria; Ministry of Health","funders":"","keywords":"Confidence interval; Distributed lag; Demography; Geography; Population; Apparent temperature; Extreme Cold; Environmental science; Climatology; Meteorology; Statistics; Mathematics","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":[0.002161047,0.0009004956,0.000664834,0.001400518,0.003446679,0.001563445,0.0024255,0.0008207385,0.001648533],"category_scores_gemma":[0.00542042,0.0006184808,0.0008723488,0.006034077,0.0009733671,0.0005738821,0.001122415,0.001583148,0.0002968721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04904138,"about_ca_system_score_gemma":0.06022338,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9987532,"about_ca_topic_score_gemma":0.99906,"domain_scores_codex":[0.9984792,0.0002814443,0.0001220014,0.0002683268,0.0004922848,0.0003567152],"domain_scores_gemma":[0.9950762,0.000498237,0.0005793242,0.0002374388,0.002831491,0.0007772691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001135685,0.00009977528,0.9842206,0.000114966,0.0001959274,0.0001981978,0.0009652386,0.001889919,0.0001605375,0.0001824171,0.003185789,0.008672936],"study_design_scores_gemma":[0.00002817973,0.00004089427,0.9899799,0.00009129597,0.0001107287,0.00007944393,0.003067267,0.004122369,0.0001003218,0.00008660115,0.002264927,0.00002810511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848303,0.001533459,0.0009917921,0.001035287,0.00002799718,0.000156203,0.008968323,0.00004399001,0.002412867],"genre_scores_gemma":[0.9911458,0.001022946,0.001169739,0.0003646636,0.000009913266,0.00009415945,0.00438753,0.00002065436,0.00178456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04904138,"threshold_uncertainty_score":0.3558217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05199417977501097,"score_gpt":0.3344697124576971,"score_spread":0.2824755326826862,"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."}}