{"id":"W1487883497","doi":"","title":"Multiperiod Statistical Risk Management Methods and Equity-Linked Life Insurance","year":2004,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Equity (law); Actuarial science; Life insurance; Quantile; Investment management; Econometrics; Economics; Stock (firearms); Risk management; Business; Financial economics; Finance; Engineering; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01397334,0.0005007485,0.0009047114,0.0008378768,0.0009818323,0.0006608304,0.001425441,0.0006071331,0.000125155],"category_scores_gemma":[0.001750678,0.0005803307,0.0002258165,0.0003733876,0.002339743,0.0001929539,0.003560512,0.002492333,0.00002066407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604714,"about_ca_system_score_gemma":0.000768849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004501718,"about_ca_topic_score_gemma":0.004803323,"domain_scores_codex":[0.9918135,0.002758525,0.001104231,0.001755861,0.0009416359,0.001626189],"domain_scores_gemma":[0.9964139,0.001098879,0.000403725,0.001288415,0.0001792397,0.0006158194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000141941,0.0003553694,0.07880272,0.0006989728,0.0004845122,0.0001190792,0.005635388,0.005898585,0.000002076337,0.04738488,0.0000571699,0.8604193],"study_design_scores_gemma":[0.002602104,0.0001360175,0.7600771,0.0005125874,0.0001088259,0.000001757896,0.009680231,0.003950466,0.000006178175,0.08389989,0.1374103,0.001614536],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4280339,0.001858557,0.002171147,0.001260344,0.002558533,0.006607959,0.0007286468,0.0003199498,0.556461],"genre_scores_gemma":[0.8177364,0.1172944,0.06278413,0.000198637,0.0003557267,0.000690077,0.00004867839,0.00008687874,0.0008050764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8588048,"threshold_uncertainty_score":0.999809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05574827697127892,"score_gpt":0.4342932980715196,"score_spread":0.3785450211002407,"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."}}