{"id":"W4391579907","doi":"10.1016/s2542-5196(23)00269-3","title":"Seasonality of mortality under climate change: a multicountry projection study","year":2024,"lang":"en","type":"article","venue":"The Lancet Planetary Health","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Health Canada","funders":"Strategic International Collaborative Research Program; Medical Research Council; Ministry of the Environment, Government of Japan; Università degli Studi di Firenze; Academy of Finland; Japan Science and Technology Agency; Ministero dell’Istruzione, dell’Università e della Ricerca; Grantová Agentura České Republiky; Environmental Restoration and Conservation Agency","keywords":"Seasonality; Climate change; Projection (relational algebra); Geography; Climatology; Computer science; Statistics; Mathematics; Biology; Ecology; Geology","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":[0.001883887,0.0001346852,0.0003062237,0.00001100292,0.0001833794,0.0000245951,0.0001744408,0.00003992312,0.0005425664],"category_scores_gemma":[0.00001031136,0.0000880006,0.00003026023,0.0002424879,0.00008161993,0.000159278,0.00009453898,0.0002476363,0.0002015227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628797,"about_ca_system_score_gemma":0.00003650268,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01600736,"about_ca_topic_score_gemma":0.01064199,"domain_scores_codex":[0.9982585,0.0002528488,0.0003011814,0.0002790423,0.000370597,0.0005378163],"domain_scores_gemma":[0.9992772,0.0001113987,0.0001024517,0.0003715205,0.000004251976,0.0001331996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001041093,0.0002382003,0.9743178,0.0009391836,0.00002669371,0.00001414353,0.006259587,0.00008942602,0.0000209391,0.0001254777,0.008578953,0.009285446],"study_design_scores_gemma":[0.0002525913,0.0002674522,0.9929959,0.0001113034,0.00002371276,0.00001396981,0.0006872306,0.003391351,0.000002833274,0.0003597976,0.001805385,0.0000885312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847059,0.001070449,0.000007149915,0.01130363,0.0003498253,0.001246201,0.0003693839,0.0001127428,0.000834689],"genre_scores_gemma":[0.9936748,0.001502863,0.00004038504,0.004145771,0.0004694754,0.00004144734,0.00009689682,0.0000118936,0.00001643152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.018678,"threshold_uncertainty_score":0.9905452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2097267156963788,"score_gpt":0.4084885552813282,"score_spread":0.1987618395849494,"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."}}