{"id":"W4383909653","doi":"10.1017/asb.2023.24","title":"Reinsurance games with variance-premium reinsurers: from tree to chain","year":2023,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reinsurance; Ambiguity; Stackelberg competition; Variance (accounting); Economics; Competition (biology); Nash equilibrium; Actuarial science; Econometrics; Microeconomics; Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006504747,0.0002797118,0.0005160422,0.0002843415,0.000151578,0.00009986967,0.0004511221,0.0001123348,0.0008260191],"category_scores_gemma":[0.0002827799,0.0003008219,0.00009904543,0.0009055898,0.0000575853,0.0000817845,0.0001356705,0.000210469,0.0203789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008447855,"about_ca_system_score_gemma":0.00001810089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001362745,"about_ca_topic_score_gemma":0.0001826071,"domain_scores_codex":[0.9978339,0.00002301073,0.0005760943,0.0008272053,0.0001119704,0.0006277874],"domain_scores_gemma":[0.9987956,0.0001185042,0.0002431147,0.000664998,0.00004691758,0.0001309166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008130663,0.0002386321,0.2399326,0.0001208944,0.000293095,0.0003979971,0.00305777,0.004691669,0.0001801062,0.1673971,0.5128295,0.07004754],"study_design_scores_gemma":[0.0007005808,0.0001396524,0.3533804,0.00008702585,0.000005841084,9.694297e-7,0.00009631826,0.0002372622,0.00008359669,0.004200593,0.6406468,0.0004209557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6904731,0.001797181,0.03001684,0.03121978,0.002178016,0.001511421,0.0008559874,0.0009049563,0.2410427],"genre_scores_gemma":[0.9774468,0.0002877406,0.005083948,0.001792142,0.0005251928,0.0001704298,0.00006411417,0.00007962938,0.01455001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2869737,"threshold_uncertainty_score":0.9999444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01818879061361756,"score_gpt":0.195491688352573,"score_spread":0.1773028977389555,"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."}}