{"id":"W2805334223","doi":"10.3390/math9141629","title":"Mortality/Longevity Risk-Minimization with or without Securitization","year":2021,"lang":"en","type":"preprint","venue":"Mathematics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Agentschap voor Innovatie door Wetenschap en Technologie","keywords":"Securitization; Longevity risk; Martingale (probability theory); Longevity; Actuarial science; Econometrics; Economics; Mathematics; Finance; Statistics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001657172,0.000429628,0.0007344637,0.0001936666,0.0006141942,0.000688861,0.0005880918,0.0004206098,0.0003821392],"category_scores_gemma":[0.0005253052,0.0003696459,0.0001932059,0.0006794094,0.0003913458,0.0002547413,0.0003945123,0.000569774,0.00002263775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001969937,"about_ca_system_score_gemma":0.0004825148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00229367,"about_ca_topic_score_gemma":0.02721714,"domain_scores_codex":[0.9960907,0.0005635554,0.0007038275,0.0006953027,0.001469183,0.0004774332],"domain_scores_gemma":[0.9970469,0.0001449103,0.001049827,0.001058371,0.0005468801,0.0001531534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007248761,0.002458954,0.723567,0.007513456,0.001953841,0.0001850047,0.1988955,0.007391335,0.000003252558,0.05109628,0.002128619,0.004734332],"study_design_scores_gemma":[0.006482924,0.0006919942,0.3239376,0.01322429,0.01387486,0.00003775579,0.2432078,0.1479927,0.0004511248,0.1999067,0.03751255,0.01267969],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8580972,0.000243187,0.09640797,0.000238637,0.001091987,0.00293251,0.0001190479,0.0005931004,0.04027638],"genre_scores_gemma":[0.9560163,0.002087575,0.03947972,0.0001025535,0.000422341,0.000245884,0.0002342034,0.00008938839,0.001322027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3996294,"threshold_uncertainty_score":0.9998755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04363289064928536,"score_gpt":0.3378856037304201,"score_spread":0.2942527130811348,"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."}}