{"id":"W2217283112","doi":"10.1007/s10687-015-0234-0","title":"A limiting distribution for maxima of discrete stationary triangular arrays with an application to risk due to avalanches","year":2015,"lang":"en","type":"article","venue":"Extremes","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"Agence Nationale de la Recherche","keywords":"Gumbel distribution; Maxima; Mathematics; Extreme value theory; Generalized extreme value distribution; Limiting; Integer (computer science); Random variable; Distribution (mathematics); Applied mathematics; Statistical physics; Combinatorics; Statistics; Mathematical analysis; Computer science; Physics","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":[0.0005983589,0.0000984591,0.000251961,0.00008450817,0.00007752841,0.00002491573,0.0001054236,0.00004446158,0.000003998507],"category_scores_gemma":[0.0004097742,0.0001032189,0.0000445307,0.000190332,0.00001513663,0.0001896915,0.00001946196,0.00004548794,0.00001893964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006895665,"about_ca_system_score_gemma":0.00002922432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003592284,"about_ca_topic_score_gemma":0.0001274339,"domain_scores_codex":[0.9990886,0.00001255532,0.0003777478,0.0003059751,0.00004621716,0.0001688503],"domain_scores_gemma":[0.9992667,0.00004772471,0.0002234617,0.0002324317,0.0001124905,0.0001171836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003914471,0.0006413349,0.4241436,0.0002471133,0.0001460089,0.000003489975,0.01944748,0.05557914,0.0009741492,0.2631553,0.002482646,0.2292654],"study_design_scores_gemma":[0.002968306,0.002310989,0.2046319,0.00009936607,0.00004840925,0.000003430291,0.00233852,0.5264041,0.002268732,0.2126827,0.04527437,0.0009691057],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4057593,0.0001361027,0.5926675,0.0001998022,0.00003217776,0.0003654142,0.0006879607,0.00001687383,0.0001349386],"genre_scores_gemma":[0.9549019,0.00000721466,0.04447452,0.00003339632,0.0001088611,0.0001414988,0.0002717229,0.00001592587,0.0000449676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5491426,"threshold_uncertainty_score":0.4209145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05261780967975654,"score_gpt":0.2566966306965285,"score_spread":0.204078821016772,"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."}}