{"id":"W4414718331","doi":"10.1016/j.insmatheco.2025.103162","title":"Modelling seasonal mortality: An age–period–cohort approach","year":2025,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec; Simon Fraser University; Society of Actuaries","keywords":"Seasonality; Context (archaeology); Parametric statistics; Seasonal adjustment; Mortality rate; Parametric model","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004145222,0.0004778718,0.0004997784,0.001238063,0.0004286471,0.0008178795,0.001536007,0.001173269,0.004412817],"category_scores_gemma":[0.007529678,0.0003710488,0.001525136,0.001245707,0.0004066527,0.0006078494,0.0009475409,0.0009769561,0.0004827236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009785901,"about_ca_system_score_gemma":0.00147982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1017391,"about_ca_topic_score_gemma":0.07501266,"domain_scores_codex":[0.9992112,0.0003724708,0.00003579519,0.000192815,0.00006910403,0.0001185573],"domain_scores_gemma":[0.9978321,0.001181578,0.0002826138,0.000285829,0.0002656955,0.0001521143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002483848,0.0001564036,0.1818119,0.0001605291,0.0008715643,0.000443014,0.0005756308,0.7177075,0.0008831854,0.04878158,0.008106491,0.04025377],"study_design_scores_gemma":[0.00002986067,0.00008288487,0.01782769,0.00003592519,0.0001369092,0.0001218973,0.0001499152,0.9619823,0.00009651911,0.01436111,0.005150681,0.000024332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4603863,0.001305231,0.5121094,0.002927167,0.0003625947,0.0004241988,0.01415769,0.0005443663,0.007783048],"genre_scores_gemma":[0.9438597,0.0008947522,0.04085767,0.000321621,0.0001425552,0.0003314483,0.003895553,0.00008133257,0.009615398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1017391,"threshold_uncertainty_score":0.2022938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07653198677612695,"score_gpt":0.2908956228444554,"score_spread":0.2143636360683284,"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."}}