{"id":"W4402622770","doi":"10.1057/s10713-024-00105-9","title":"The Riccati tontine: how to satisfy regulators on average","year":2024,"lang":"en","type":"article","venue":"The Geneva Risk and Insurance Review","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Riccati equation; Mathematical economics; Linear-quadratic regulator; Mathematics; Mathematical optimization; Applied mathematics; Control theory (sociology); Computer science; Control (management); Optimal control; Mathematical analysis; Artificial intelligence; Differential equation","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007196311,0.0001362268,0.000266812,0.00003387361,0.0004072808,0.0001485704,0.0002739796,0.00003310015,0.00001344087],"category_scores_gemma":[0.0002273397,0.00008171728,0.0000888882,0.0005032208,0.0000580754,0.00005997651,0.00005074808,0.0001523825,0.0004579715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002453299,"about_ca_system_score_gemma":0.00001639661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004538663,"about_ca_topic_score_gemma":0.00001189635,"domain_scores_codex":[0.9991137,0.00001091716,0.0003146932,0.0003164124,0.00004337941,0.0002009134],"domain_scores_gemma":[0.9991663,0.0001617112,0.0001303857,0.0004597239,0.000024374,0.00005748683],"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":[0.000003627907,0.000007498221,0.0005541319,0.0002860294,0.00001988661,4.082563e-7,0.0001114628,0.000008632541,0.000001899449,0.657635,0.005335417,0.3360359],"study_design_scores_gemma":[0.0000494885,0.00003847582,0.02356653,0.0005093779,0.00001334081,0.000005472376,0.00000579642,0.0002371509,0.000007891835,0.08517712,0.8902407,0.0001486507],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00915374,0.9089947,0.05473967,0.02314627,0.0004141502,0.0008040683,0.0002144701,0.00005052896,0.002482347],"genre_scores_gemma":[0.4735021,0.5242024,0.0001852039,0.00108687,0.0001909098,0.0002292702,0.00000242732,0.00001775204,0.0005831278],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8849053,"threshold_uncertainty_score":0.588645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679896312488162,"score_gpt":0.2339985870550645,"score_spread":0.2171996239301829,"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."}}