{"id":"W1771613708","doi":"10.3233/rda-2011-0027","title":"Excess-of-loss reinsurance under taxes and fixed costs","year":2010,"lang":"en","type":"article","venue":"Risk and Decision Analysis","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reinsurance; Fixed cost; Economics; Actuarial science; Microeconomics","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":[0.003908271,0.0001723118,0.0006602724,0.0006570421,0.0003039153,0.0002407419,0.0004632082,0.0001772206,0.0002844178],"category_scores_gemma":[0.002952739,0.0001076585,0.0002701759,0.002130584,0.0004434223,0.0003386318,0.0002204448,0.0002786615,0.00003263083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008372672,"about_ca_system_score_gemma":0.00003458802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003985987,"about_ca_topic_score_gemma":0.002888578,"domain_scores_codex":[0.9969456,0.0001844423,0.0008178065,0.0007253647,0.001120386,0.0002064444],"domain_scores_gemma":[0.9944861,0.003504755,0.0003975808,0.0009717676,0.0004073421,0.0002324801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001930756,0.0000926825,0.4188053,0.0000030623,0.0001805904,0.000004770483,0.0003224516,0.001611346,0.0004818259,0.004813266,0.0004541974,0.5730374],"study_design_scores_gemma":[0.0005789397,0.00004712444,0.470264,0.00001073084,0.0003230858,0.000006966749,0.0002909373,0.04793506,0.0005161754,0.4770299,0.002767653,0.0002294995],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8504544,0.0007467792,0.1480072,0.0001692806,0.0001188086,0.0000776591,0.00007955114,0.00001496389,0.000331366],"genre_scores_gemma":[0.9886131,0.001562616,0.009445352,0.0000566723,0.00003587225,0.000003284313,0.000002290987,0.000005821425,0.0002749755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5728079,"threshold_uncertainty_score":0.4390188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0389890206133421,"score_gpt":0.3625656847635659,"score_spread":0.3235766641502238,"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."}}