{"id":"W4320065609","doi":"10.1289/isee.2022.p-0558","title":"Future mortality burden attributable to non-optimal temperatures under the dual threats from climate change and population aging","year":2022,"lang":"en","type":"article","venue":"ISEE Conference Abstracts","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Climate change; Poisson regression; Population; Global warming; Demography; Distributed lag; Environmental science; Multivariate statistics; Mean radiant temperature; Climatology; Geography; Statistics; Mathematics; Ecology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004480919,0.00050254,0.0005979283,0.0006841065,0.0002308932,0.0008592366,0.0005690288,0.0005744206,0.001565365],"category_scores_gemma":[0.006330919,0.0002534442,0.002799043,0.001251716,0.0004671888,0.0009914038,0.001172771,0.00102425,0.000172865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006928599,"about_ca_system_score_gemma":0.0007536626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006847607,"about_ca_topic_score_gemma":0.00690737,"domain_scores_codex":[0.9984695,0.0008630264,0.0001230077,0.0003335377,0.0001211727,0.0000897453],"domain_scores_gemma":[0.9971973,0.0009627664,0.0009285893,0.000448531,0.0003738179,0.00008904341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008077631,0.00005015513,0.9032326,0.002087291,0.01256859,0.000172202,0.0004701443,0.02864029,0.001642632,0.005498576,0.00374952,0.04108019],"study_design_scores_gemma":[0.00007839914,0.0003650504,0.9321218,0.0009689411,0.009838019,0.0004824905,0.0005594567,0.02995432,0.00163289,0.01189944,0.01202612,0.00007297589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.886911,0.04729421,0.04087772,0.005057345,0.0005293553,0.00007607014,0.01596615,0.000174228,0.003113965],"genre_scores_gemma":[0.9859694,0.005784921,0.004108105,0.0004718726,0.0002068598,0.00008168307,0.003051655,0.00002152708,0.0003039132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006847607,"threshold_uncertainty_score":0.02369761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1013097439765572,"score_gpt":0.3305789877324415,"score_spread":0.2292692437558844,"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."}}