{"id":"W3152245405","doi":"10.3390/risks9040068","title":"Matrix-Tilted Archimedean Copulas","year":2021,"lang":"en","type":"article","venue":"Risks","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Copula (linguistics); Cholesky decomposition; Mathematics; Pure mathematics; Matrix (chemical analysis); Extension (predicate logic); Econometrics; Computer science; Physics; Eigenvalues and eigenvectors","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":[0.001483966,0.000988474,0.0009394067,0.001299485,0.0005418959,0.002822213,0.001155655,0.0007987611,0.004996502],"category_scores_gemma":[0.006549309,0.0004105793,0.001068293,0.001628031,0.001114254,0.002663884,0.001228008,0.001786502,0.00107601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009205614,"about_ca_system_score_gemma":0.001120475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002013562,"about_ca_topic_score_gemma":0.001564684,"domain_scores_codex":[0.9987308,0.0003100071,0.00007686565,0.0003050053,0.0003991925,0.0001780058],"domain_scores_gemma":[0.9977142,0.0007484518,0.0003779555,0.0003295323,0.0006785134,0.0001513658],"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":[0.00004368571,0.00002654614,0.00136388,0.00007053163,0.00006331754,0.000234027,0.0001421602,0.07186361,0.004586349,0.8864317,0.002902439,0.03227175],"study_design_scores_gemma":[0.00001201324,0.0000381709,0.001487415,0.00003148414,0.00002929398,0.0002852345,0.00006283656,0.4970437,0.001624013,0.489208,0.01012062,0.00005715505],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01485737,0.0004004313,0.9774913,0.0001940831,0.0001046369,0.00004427624,0.0003012252,0.0001784275,0.006428273],"genre_scores_gemma":[0.7353156,0.002759045,0.2384315,0.0005142092,0.0005051824,0.0002474128,0.001163719,0.000316712,0.02074668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004996502,"threshold_uncertainty_score":0.01671499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1228776448594994,"score_gpt":0.3085838189170331,"score_spread":0.1857061740575337,"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."}}