{"id":"W2766235828","doi":"10.1016/j.jmva.2017.10.006","title":"Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Hüsler–Reiß distribution","year":2017,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; King Abdullah University of Science and Technology","keywords":"Mathematics; Multivariate statistics; Copula (linguistics); Multivariate normal distribution; Convolution (computer science); Exponential function; Applied mathematics; Multivariate random variable; Limit (mathematics); Random variable; Statistics; Mathematical analysis; Econometrics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001144462,0.0001670902,0.0005124892,0.0001062515,0.000644007,0.00008243616,0.0005885297,0.0001015615,0.00007525097],"category_scores_gemma":[0.005499275,0.0001018446,0.0004411163,0.0005057359,0.0002937424,0.0002093456,0.000200613,0.0002440854,0.000003367456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008573927,"about_ca_system_score_gemma":0.00008134131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002856201,"about_ca_topic_score_gemma":0.00004998858,"domain_scores_codex":[0.9977143,0.000250049,0.00114357,0.0001731539,0.0005255485,0.0001933833],"domain_scores_gemma":[0.9954022,0.0006486767,0.002178484,0.0006915044,0.0009485291,0.0001306357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004036909,0.001018053,0.01031794,0.0001237007,0.003391827,0.000003635014,0.001038976,0.003980746,0.021728,0.9452678,0.00186086,0.01086479],"study_design_scores_gemma":[0.001406975,0.00008598232,0.885132,0.0001318375,0.003974654,0.00001159997,0.0001768273,0.08626993,0.006108171,0.01538661,0.001121529,0.0001939008],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1335436,0.00003732167,0.8597478,0.005035781,0.0001306546,0.0002636627,0.001171174,0.000007372123,0.00006263894],"genre_scores_gemma":[0.9931254,0.0000238153,0.006579232,0.00002187709,0.000105198,0.00001210099,0.00006564002,0.000008061387,0.00005861514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9298812,"threshold_uncertainty_score":0.6583543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07240964380968566,"score_gpt":0.3601203292356547,"score_spread":0.287710685425969,"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."}}