{"id":"W4394962853","doi":"10.3390/risks12040070","title":"Determining Safe Withdrawal Rates for Post-Retirement via a Ruin-Theory Approach","year":2024,"lang":"en","type":"article","venue":"Risks","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Economics; Ruin theory; Actuarial science; Econometrics; Risk model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00234548,0.0002172849,0.0002376422,0.0002031643,0.0006670764,0.0003334635,0.0003841799,0.0001179145,0.0001266916],"category_scores_gemma":[0.0001043984,0.0002018844,0.0002399558,0.0004214689,0.0003323346,0.0002512784,0.00007986225,0.0001784328,0.00008424515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294818,"about_ca_system_score_gemma":0.0001234505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009135723,"about_ca_topic_score_gemma":0.000586827,"domain_scores_codex":[0.9977471,0.000273212,0.0003276181,0.0005233174,0.0005258869,0.0006028456],"domain_scores_gemma":[0.999148,0.0002380326,0.00008532537,0.0002862703,0.0001146123,0.0001277756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002373566,0.0004621198,0.05347292,0.0009375761,0.0008636917,0.00008535405,0.04914995,0.000200698,0.0004612225,0.4141344,0.008871348,0.4711234],"study_design_scores_gemma":[0.002778245,0.001122302,0.1396897,0.0006894051,0.001311215,0.00001211017,0.04639613,0.02390173,0.001295993,0.1349025,0.6444911,0.0034095],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6880495,0.003911835,0.09500686,0.001670351,0.004408183,0.004931852,0.0001469454,0.001218715,0.2006557],"genre_scores_gemma":[0.9927028,0.0001150028,0.004003651,0.0002928153,0.0005468847,0.000318818,0.00002635552,0.00004060764,0.001953037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6356198,"threshold_uncertainty_score":0.8232605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04918025630331083,"score_gpt":0.3912611217786733,"score_spread":0.3420808654753625,"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."}}