{"id":"W98088619","doi":"","title":"Efficient Hedging Methodology Applied to Equity-Linked Life Insurance","year":2005,"lang":"en","type":"article","venue":"Spectrum Research Repository (Concordia University)","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Life insurance; Actuarial science; Equity (law); Insurance policy; Imperfect; Black–Scholes model; Profit (economics); Economics; Business; Auto insurance risk selection; Key person insurance; Microeconomics; Financial economics; Volatility (finance)","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","sts"],"consensus_categories":[],"category_scores_codex":[0.005835116,0.0002749417,0.000475982,0.001689589,0.002674351,0.0002568436,0.001717123,0.0002302983,0.0001121373],"category_scores_gemma":[0.0004770244,0.0003303138,0.0002331341,0.003451324,0.001231021,0.0002048062,0.001029654,0.0008614701,0.0003008062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001409265,"about_ca_system_score_gemma":0.0008638909,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02055767,"about_ca_topic_score_gemma":0.01826724,"domain_scores_codex":[0.9927908,0.002345017,0.0003926646,0.001005365,0.001703637,0.001762531],"domain_scores_gemma":[0.9970052,0.0007342136,0.0001606503,0.0008316956,0.0003240335,0.0009442171],"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":[0.001484071,0.0009551214,0.2769188,0.0001688437,0.0005987749,0.000977745,0.02504956,0.01448737,0.01161994,0.6368843,0.00511032,0.0257452],"study_design_scores_gemma":[0.001349928,0.000235607,0.4436123,0.00005075697,0.00005385167,0.000004059031,0.01198993,0.0003601346,0.002410552,0.001056905,0.5380456,0.0008303648],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6386715,0.00008002312,0.001462912,0.003832977,0.0005860067,0.000931498,0.000005193602,0.0002370097,0.3541929],"genre_scores_gemma":[0.9907205,0.00008949417,0.000978499,0.0002676176,0.001082344,0.00001483242,0.000002085555,0.00003345115,0.006811146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6358274,"threshold_uncertainty_score":0.9999149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09532174268850789,"score_gpt":0.368580496253746,"score_spread":0.2732587535652381,"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."}}