{"id":"W3123307269","doi":"10.2139/ssrn.3192132","title":"A Data Driven Neural Network Approach to Optimal Asset Allocation for Target Based Defined Contribution Pension Plans","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pension; Asset allocation; Artificial neural network; Asset (computer security); Computer science; Pension plan; Actuarial science; Business; Economics; Finance; Artificial intelligence; Portfolio; Computer security","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.006427878,0.0001842032,0.0002358777,0.000138337,0.001412434,0.0001960631,0.0008955103,0.0001180775,0.00001375847],"category_scores_gemma":[0.0003106789,0.0001785363,0.0001137868,0.0005167479,0.0001512911,0.0004374456,0.00009681072,0.0005777676,0.00001640243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006378837,"about_ca_system_score_gemma":0.00124187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003013603,"about_ca_topic_score_gemma":0.01132653,"domain_scores_codex":[0.9957861,0.0003895529,0.0003725559,0.000447227,0.0005943119,0.002410247],"domain_scores_gemma":[0.9986608,0.00009460352,0.0002537021,0.0004178338,0.0004091071,0.0001639639],"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":[0.00173443,0.0008276801,0.04700349,0.00003416097,0.0007081506,0.000004497367,0.002119345,0.06086811,0.0002201363,0.8273737,0.04796862,0.01113773],"study_design_scores_gemma":[0.006368229,0.002973506,0.0413737,0.00009835128,0.0006026161,0.00004899671,0.007345563,0.6046964,0.00005378404,0.09822151,0.2365843,0.001633058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1887747,0.0003618619,0.802,0.00420944,0.001082618,0.001847112,0.0001685715,0.0001282098,0.001427421],"genre_scores_gemma":[0.9863503,0.0001487743,0.01030676,0.0004491749,0.001980314,0.0000453766,0.0005857099,0.00002349829,0.0001100868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7975756,"threshold_uncertainty_score":0.9998876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02956486934431266,"score_gpt":0.3085503154779632,"score_spread":0.2789854461336506,"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."}}