{"id":"W4386186558","doi":"10.2139/ssrn.4544565","title":"A Bayesian Generalized Additive Model Approach for Forecasting Mortality Improvement with External Information","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bayesian probability; Econometrics; Bayesian inference; Statistics; Computer science; Mathematics","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":[0.004567965,0.00117377,0.002524637,0.002035504,0.0006807739,0.0019024,0.002262983,0.002479859,0.002798576],"category_scores_gemma":[0.01399339,0.0009274535,0.001460008,0.002226862,0.0005984086,0.002074395,0.001227551,0.002193741,0.0005416222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001249173,"about_ca_system_score_gemma":0.00149943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02964919,"about_ca_topic_score_gemma":0.02584914,"domain_scores_codex":[0.9985254,0.000764652,0.00009209589,0.0002902043,0.0002100222,0.0001175965],"domain_scores_gemma":[0.9944181,0.004394926,0.0003464788,0.000174868,0.0005500875,0.0001155549],"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":[0.00009529421,0.00009191007,0.002662089,0.00004585943,0.0001482333,0.00004853904,0.00004744006,0.9564021,0.0002415949,0.009341382,0.0008790623,0.02999653],"study_design_scores_gemma":[0.000007525714,0.00002001681,0.0003275848,0.000004363652,0.00001687914,0.00000614892,0.000003945917,0.9953437,0.0000360036,0.004118011,0.0001069526,0.000008711127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08000854,0.0007999203,0.9146698,0.0007846433,0.0001657626,0.00007587377,0.0006482955,0.00052671,0.002320372],"genre_scores_gemma":[0.8233832,0.0008894627,0.1683518,0.0002184999,0.0002687815,0.0002314224,0.001213215,0.00008387447,0.005359706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02964919,"threshold_uncertainty_score":0.05895323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02588836351000383,"score_gpt":0.2853758138325987,"score_spread":0.2594874503225948,"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."}}