{"id":"W3097355529","doi":"10.1016/s2542-5196(20)30222-9","title":"Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study","year":2020,"lang":"en","type":"article","venue":"The Lancet Planetary Health","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Public Health; Health Canada; University of Ottawa","funders":"Natural Environment Research Council; Fundação para a Ciência e a Tecnologia; Medical Research Council; National Institute of Environmental Health Sciences; Horizon 2020; Ministry of Environment; Sight Research UK","keywords":"Representative Concentration Pathways; Climate change; Geography; Diurnal temperature variation; Environmental science; Excess mortality; Climatology; Demography; Range (aeronautics); Climate model; Mortality rate; Meteorology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009584472,0.0002033986,0.0004972732,0.00003275801,0.0004146756,0.00002609309,0.0003265567,0.00007587102,0.0002944491],"category_scores_gemma":[0.00001536568,0.0001425416,0.0000344702,0.0005050038,0.0000587023,0.0001820526,0.0001403084,0.0004991676,0.0001332773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001145609,"about_ca_system_score_gemma":0.00003359281,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009287811,"about_ca_topic_score_gemma":0.005649306,"domain_scores_codex":[0.9978425,0.0002516633,0.0004364714,0.0003669931,0.0003965806,0.0007058123],"domain_scores_gemma":[0.9989451,0.00005686537,0.0002127809,0.0003718227,0.0000103609,0.0004030733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005206891,0.0006045233,0.8455508,0.0006589364,0.00005801733,0.00003233846,0.05544912,0.09103118,0.0001032967,0.0000324397,0.005311077,0.0006476076],"study_design_scores_gemma":[0.001974915,0.0009691046,0.9344288,0.0001889936,0.00005247603,0.00001914851,0.003862217,0.05747472,0.000004722671,0.00006543896,0.0006549562,0.0003044879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9696361,0.0004249074,0.00005611874,0.02691383,0.0001644572,0.002073482,0.0004456926,0.00009122818,0.0001941217],"genre_scores_gemma":[0.9806204,0.001110259,0.0002916729,0.01749962,0.0002870141,0.00004879008,0.000110818,0.00002075939,0.00001062089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08887804,"threshold_uncertainty_score":0.9973094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.223795658178338,"score_gpt":0.3707513441893756,"score_spread":0.1469556860110376,"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."}}