{"id":"W2609328783","doi":"10.1016/j.jmva.2017.05.008","title":"Extremal attractors of Liouville copulas","year":2017,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Dirichlet distribution; Inference; Applied mathematics; Copula (linguistics); Limiting; Extreme value theory; Tail dependence; Pure mathematics; Statistical physics; Multivariate statistics; Mathematical analysis; Econometrics; Statistics; Computer science; Physics; Boundary value problem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001815767,0.000810913,0.001003029,0.002556852,0.0009331924,0.002850416,0.001053254,0.001051905,0.004163685],"category_scores_gemma":[0.01047673,0.0006593419,0.0009756064,0.0008834873,0.002243007,0.001921332,0.001637954,0.002106497,0.0003452998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001552335,"about_ca_system_score_gemma":0.0006559748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002412684,"about_ca_topic_score_gemma":0.001923382,"domain_scores_codex":[0.9995503,0.0001734653,0.00001888127,0.0000790477,0.00008128749,0.00009703274],"domain_scores_gemma":[0.9950412,0.002907101,0.0007624956,0.000168426,0.0004962759,0.0006245759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001516921,0.000078833,0.003607498,0.000110799,0.0001319603,0.0004390103,0.0005530384,0.07206064,0.005678532,0.906106,0.002383108,0.008698924],"study_design_scores_gemma":[0.00002999589,0.00005332537,0.002669491,0.00004002327,0.00003862485,0.0001749644,0.0001652316,0.6332123,0.0007801107,0.3615156,0.001251883,0.00006848387],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6446687,0.001477953,0.3271732,0.001371037,0.0001360356,0.00005069108,0.0003211658,0.000426978,0.0243742],"genre_scores_gemma":[0.9873804,0.0003539244,0.006961483,0.00007475389,0.00008224732,0.0000449643,0.0001400582,0.00009184027,0.004870354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004163685,"threshold_uncertainty_score":0.01392889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846733779528799,"score_gpt":0.2887322747530727,"score_spread":0.2702649369577848,"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."}}