{"id":"W4312941747","doi":"10.2139/ssrn.4282024","title":"Modeling Longevity and Disability with Generalized Autoregressive Score Models","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Concordia University","funders":"","keywords":"Autoregressive model; Longevity; Econometrics; Nonlinear autoregressive exogenous model; Mathematics; STAR model; Statistics; Medicine; Computer science; Autoregressive integrated moving average; Gerontology; Time series","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":[0.004307637,0.001155635,0.001535391,0.001550491,0.000536442,0.002346761,0.001866612,0.002005576,0.003343155],"category_scores_gemma":[0.0107061,0.0007941694,0.002006007,0.002090096,0.0009499354,0.001558411,0.001732645,0.002137826,0.0008017397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295268,"about_ca_system_score_gemma":0.001687536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05284994,"about_ca_topic_score_gemma":0.05300839,"domain_scores_codex":[0.9983884,0.0008120296,0.00006893462,0.0002712436,0.0001330214,0.0003263383],"domain_scores_gemma":[0.9943189,0.003937762,0.0007400895,0.0002794946,0.0004501935,0.0002736227],"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":[0.0001532588,0.0002843859,0.0543846,0.00006828685,0.000575296,0.0002398623,0.0003376333,0.8773711,0.0002136111,0.03639811,0.002251355,0.02772256],"study_design_scores_gemma":[0.00002577049,0.00009033735,0.007958624,0.00002243365,0.00008791902,0.00003504472,0.0001100514,0.9676907,0.00005218651,0.02308252,0.0008163698,0.00002802642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7049496,0.001278037,0.2825032,0.00260195,0.0002934884,0.0001280925,0.002897234,0.0007285355,0.004619909],"genre_scores_gemma":[0.972411,0.0005319812,0.0142709,0.0001177693,0.0001112559,0.0001005384,0.001342645,0.00005606829,0.01105778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05284994,"threshold_uncertainty_score":0.1050847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04916690784921359,"score_gpt":0.3779719317564922,"score_spread":0.3288050239072786,"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."}}