{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003577341,0.0007205695,0.0009780411,0.0009971671,0.0003430832,0.001242529,0.001086292,0.0009622506,0.001769403],"category_scores_gemma":[0.007643417,0.0004947329,0.00086184,0.000881922,0.001176833,0.001887242,0.001352542,0.001366545,0.0001940682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007191645,"about_ca_system_score_gemma":0.0006681672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006735839,"about_ca_topic_score_gemma":0.0004589645,"domain_scores_codex":[0.9989846,0.0005113735,0.00005891041,0.0001060179,0.0002803405,0.00005872335],"domain_scores_gemma":[0.9980471,0.001244212,0.0001883463,0.0002300552,0.0002102173,0.00008002434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004101171,0.00008048831,0.001106543,0.000107531,0.00009575584,0.000180435,0.0001876255,0.4428338,0.003635089,0.4885743,0.0003807881,0.06277663],"study_design_scores_gemma":[0.000008524389,0.00003771254,0.0001861867,0.000007848026,0.0000116758,0.00003825598,0.000008974659,0.9332647,0.0005208132,0.06518196,0.0007245702,0.000008750265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01048226,0.0002930294,0.9883189,0.0000613006,0.0000175014,0.00001941514,0.000008406102,0.00002473855,0.0007744548],"genre_scores_gemma":[0.6624745,0.001152806,0.3292474,0.00009862379,0.0001902302,0.0001641874,0.0001237722,0.00009290657,0.006455539],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003577341,"threshold_uncertainty_score":0.01891899,"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."}}