{"id":"W3178583316","doi":"10.3390/math9141629","title":"Mortality/Longevity Risk-Minimization with or without Securitization","year":2021,"lang":"en","type":"article","venue":"MDPI (MDPI AG)","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":3,"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; Bond; Mathematics; Economics; Statistics; Finance; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001044061,0.0002658728,0.0003653105,0.0001433904,0.0009744622,0.0003291581,0.0003229422,0.0001694915,0.0007853534],"category_scores_gemma":[0.0003527496,0.0002344932,0.0001221977,0.001396688,0.0003966154,0.0005759749,0.00009183439,0.0002449764,0.0000749731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001428858,"about_ca_system_score_gemma":0.000341113,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003823798,"about_ca_topic_score_gemma":0.06559824,"domain_scores_codex":[0.9965057,0.0007466776,0.0004170811,0.0006575545,0.001111973,0.0005610042],"domain_scores_gemma":[0.998293,0.00009522228,0.0003335649,0.0005972988,0.0004910307,0.0001899281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006473721,0.0003143968,0.9679879,0.00009121474,0.0001976188,0.0001046516,0.008493596,0.0003938603,0.00001146701,0.01501685,0.002037682,0.005286056],"study_design_scores_gemma":[0.001759756,0.000159324,0.846179,0.0001749587,0.0005689755,0.000007369412,0.00986967,0.001576383,0.0004286572,0.004289976,0.1338792,0.001106729],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9210525,0.0002939508,0.005952809,0.000738934,0.0008511964,0.001007017,0.00007183178,0.0004472698,0.0695845],"genre_scores_gemma":[0.9926122,0.001027765,0.001677229,0.0004067669,0.0004541427,0.00008301947,0.0001163728,0.00004270635,0.003579792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1318415,"threshold_uncertainty_score":0.9562354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0258648201438433,"score_gpt":0.3175541860442148,"score_spread":0.2916893659003715,"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."}}