{"id":"W3124504710","doi":"10.2139/ssrn.3180333","title":"Management of Withdrawal Risk Through Optimal Life Cycle Asset Allocation","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Asset allocation; IT asset management; Economics; Business; Actuarial science; Asset management; Financial economics; 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":[],"consensus_categories":[],"category_scores_codex":[0.00434153,0.0001754263,0.0002241676,0.0001299669,0.0009468462,0.00009746479,0.0006121064,0.00009128685,0.000118462],"category_scores_gemma":[0.00005253507,0.0001706181,0.0001743338,0.0005821798,0.000502825,0.0004985499,0.00007794222,0.0007755788,0.00007101197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005555901,"about_ca_system_score_gemma":0.0008564509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002285299,"about_ca_topic_score_gemma":0.007002632,"domain_scores_codex":[0.9960632,0.0003636994,0.0004638952,0.000287344,0.0009126205,0.00190925],"domain_scores_gemma":[0.9988075,0.00002904933,0.0004985154,0.0002921476,0.0002611712,0.0001115687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001213453,0.0002809222,0.02941107,0.00002295602,0.001108405,0.000006735497,0.004486816,0.0004007354,0.00001017409,0.9332906,0.0007479581,0.03011229],"study_design_scores_gemma":[0.003366945,0.001690829,0.1603677,0.0001653912,0.0008994085,0.00002903545,0.08606332,0.000755977,0.0001582478,0.6847088,0.06066868,0.001125635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9056038,0.001286458,0.03628503,0.001040643,0.0007528276,0.0004967679,0.000006889608,0.00008308672,0.05444453],"genre_scores_gemma":[0.9835859,0.01304383,0.001730773,0.00008770932,0.0007088587,0.00001203401,0.000003571291,0.00002201581,0.0008052918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2485817,"threshold_uncertainty_score":0.728247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008722092026762761,"score_gpt":0.2891649995024045,"score_spread":0.2804429074756417,"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."}}