{"id":"W1899825239","doi":"10.1002/9781118445112.stat04357","title":"Options and Guarantees in Life Insurance","year":2014,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Life insurance; Actuarial science; Context (archaeology); Payment; Cover (algebra); Insurance policy; Business; Variable (mathematics); Finance; Mathematics; Geography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007971481,0.0005265882,0.000810724,0.0007350174,0.0002755453,0.0001681198,0.0006233584,0.0004268549,0.001175161],"category_scores_gemma":[0.0005188667,0.0005459908,0.00005960944,0.000601969,0.001087182,0.0001090699,0.0001451578,0.0006475377,0.0001403344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001048395,"about_ca_system_score_gemma":0.0003350075,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01342868,"about_ca_topic_score_gemma":0.1635648,"domain_scores_codex":[0.9961622,0.0005664934,0.0007223855,0.0008302875,0.0009195912,0.0007990139],"domain_scores_gemma":[0.9981226,0.0002577726,0.0005361126,0.0006044406,0.0001716494,0.000307425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004737609,0.0006376859,0.04546289,0.0006313757,0.0002105951,0.00008467068,0.001712319,0.00003643653,0.000002621165,0.4900133,0.421486,0.03967478],"study_design_scores_gemma":[0.000760193,0.00008826002,0.05687414,0.0007713473,0.00006806992,7.426942e-7,0.0007884672,0.0001793007,1.315712e-7,0.01298539,0.9266502,0.0008338119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006399457,0.02085378,0.04527424,0.001508209,0.003654595,0.004892764,0.08155377,0.001487163,0.834376],"genre_scores_gemma":[0.1198607,0.2863398,0.1791315,0.001791216,0.002386379,0.0003865156,0.006309619,0.001385659,0.4024086],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5051641,"threshold_uncertainty_score":0.9997379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03273783712912254,"score_gpt":0.3320167743752495,"score_spread":0.2992789372461269,"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."}}