{"id":"W2019934488","doi":"10.2143/ast.39.1.2038063","title":"Analysis of the Compound Poisson Surplus Model with Liquid Reserves, Interest and Dividends","year":2009,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dividend; Economics; Poisson distribution; Interest rate; Constant (computer programming); Econometrics; Drawdown (hydrology); Mathematics; Monetary economics; Statistics; Computer science; Finance","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":[0.002339678,0.0001393713,0.0004106775,0.0002171345,0.0001650181,0.0001132378,0.0008358288,0.00006869207,0.0001314867],"category_scores_gemma":[0.001063197,0.00007180694,0.0001461816,0.001115163,0.0002923704,0.00007758229,0.0002447202,0.0001760026,0.00001208585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001885275,"about_ca_system_score_gemma":0.00004637965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002065523,"about_ca_topic_score_gemma":0.0006933472,"domain_scores_codex":[0.9977617,0.0002801638,0.0005219823,0.000451129,0.0007728785,0.0002121033],"domain_scores_gemma":[0.9977644,0.0008058231,0.0002495367,0.0008485587,0.0002424519,0.00008923611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.004080856,0.001071247,0.3623334,0.00003726261,0.0009972209,0.00003195515,0.006115266,0.5152517,0.002526499,0.02762053,0.04811003,0.03182407],"study_design_scores_gemma":[0.001094487,0.001066927,0.7040567,0.0001537694,0.0006667394,0.00001935136,0.0004038605,0.2499835,0.001015174,0.03095873,0.01005528,0.0005254685],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739339,0.0001979961,0.006682434,0.01756804,0.00003058035,0.0001181461,0.00002550382,0.00001669198,0.001426719],"genre_scores_gemma":[0.9968677,0.00001239607,0.001184298,0.0002792859,0.00001463342,0.000002322489,0.000002282979,0.000004767422,0.001632316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3417234,"threshold_uncertainty_score":0.2928202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1236134490543423,"score_gpt":0.3435376811393466,"score_spread":0.2199242320850043,"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."}}