{"id":"W1947527549","doi":"10.1017/asb.2017.9","title":"THE FULL TAILS GAMMA DISTRIBUTION APPLIED TO MODEL EXTREME VALUES","year":2017,"lang":"en","type":"preprint","venue":"Astin Bulletin","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Generalized Pareto distribution; Pareto distribution; Extreme value theory; Gamma distribution; Pareto principle; Heavy-tailed distribution; Distribution (mathematics); Statistical physics; Econometrics; Aggregate (composite); Mathematics; Statistics; Physics; Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003022343,0.001034458,0.0008443113,0.00205486,0.0005199864,0.002200237,0.001431594,0.001820825,0.003194807],"category_scores_gemma":[0.01351262,0.0004304391,0.001039314,0.001527379,0.002111288,0.002265661,0.001999622,0.002472712,0.0007184408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001272813,"about_ca_system_score_gemma":0.0009239726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003276626,"about_ca_topic_score_gemma":0.001326131,"domain_scores_codex":[0.9989035,0.0005799606,0.00004048718,0.0001306965,0.0002208732,0.0001244966],"domain_scores_gemma":[0.9951815,0.003097782,0.0004756745,0.0004558582,0.0005459078,0.0002431863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004125627,0.00003436059,0.001537378,0.0000445534,0.00003928162,0.0003934699,0.0001627683,0.5928408,0.0007589598,0.3940569,0.001478815,0.008611488],"study_design_scores_gemma":[0.000009176922,0.00001403386,0.00019276,0.0000174576,0.000007501273,0.0000809359,0.00002375645,0.7837542,0.0001452476,0.2147305,0.001010311,0.00001416291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04080705,0.0006367133,0.9491342,0.0007544019,0.0001449973,0.00003453716,0.0001310241,0.0002619251,0.00809518],"genre_scores_gemma":[0.9292204,0.001229247,0.05890438,0.0003254281,0.0003131074,0.0001843012,0.0002416921,0.0002057861,0.009375636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003276626,"threshold_uncertainty_score":0.01598388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04999764873180144,"score_gpt":0.2304865213492025,"score_spread":0.1804888726174011,"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."}}