{"id":"W4406225346","doi":"10.1017/asb.2024.38","title":"Forecasting mortality rates with functional signatures","year":2025,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Robustness (evolution); Outlier; Bootstrapping (finance); Computer science; Econometrics; Regression; Data mining; Statistics; Artificial intelligence; Mathematics; 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":[0.002997964,0.0004571743,0.000512777,0.0015768,0.0001612629,0.0007680078,0.0009372512,0.0007117948,0.001157113],"category_scores_gemma":[0.0130055,0.0002220911,0.0005960112,0.001196996,0.0003885627,0.001039438,0.0007316634,0.0008637873,0.0002507666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006654587,"about_ca_system_score_gemma":0.000651687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006073632,"about_ca_topic_score_gemma":0.003088271,"domain_scores_codex":[0.9991938,0.0004791028,0.00003802035,0.0001003718,0.0001254281,0.00006322325],"domain_scores_gemma":[0.995922,0.002402544,0.0006865087,0.0003767426,0.0004665551,0.00014564],"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":[0.0001291637,0.00005626687,0.03096737,0.00003586428,0.00006373938,0.0000734172,0.000076664,0.9027562,0.0006887164,0.01180136,0.0009775745,0.05237364],"study_design_scores_gemma":[0.000002020773,0.00001269868,0.001710922,0.000003309019,0.000002510759,0.000006699552,0.000008911885,0.9951723,0.0001205136,0.002867435,0.00008828819,0.000004405153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5513948,0.0002554403,0.4439011,0.0006893134,0.00008373676,0.00005016285,0.0008511479,0.000350368,0.002424001],"genre_scores_gemma":[0.9826493,0.00008380671,0.01617923,0.00002660177,0.00003126325,0.00002375273,0.0004572038,0.00001096502,0.0005377517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006073632,"threshold_uncertainty_score":0.01585495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03122937804714777,"score_gpt":0.2961986112930384,"score_spread":0.2649692332458907,"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."}}