{"id":"W2155967382","doi":"10.1175/jcli-d-14-00237.1","title":"Probabilistic Multisite Statistical Downscaling for Daily Precipitation Using a Bernoulli–Generalized Pareto Multivariate Autoregressive Model","year":2015,"lang":"en","type":"article","venue":"Journal of Climate","topic":"Climate variability and models","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Autoregressive model; Multivariate statistics; Downscaling; Mathematics; Statistics; Probabilistic logic; Generalized Pareto distribution; Pareto principle; Precipitation; Econometrics; Extreme value theory; Meteorology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001268992,0.0004932687,0.0007047346,0.000452048,0.0002933605,0.0006043884,0.001438803,0.0005643885,0.001129894],"category_scores_gemma":[0.001774485,0.0004153581,0.001012273,0.0006356703,0.0004800537,0.0007397228,0.0005156858,0.0009429951,0.0002480363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006697394,"about_ca_system_score_gemma":0.001273509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01497169,"about_ca_topic_score_gemma":0.0141019,"domain_scores_codex":[0.9994729,0.0001891144,0.00002562197,0.0001141379,0.0001507391,0.00004755418],"domain_scores_gemma":[0.9994696,0.0002177332,0.00009974041,0.00005318925,0.0001358952,0.00002388568],"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":[0.00001451996,0.00001604021,0.0005136341,0.00001187155,0.000024209,0.00002392358,0.00001442886,0.9798076,0.001053185,0.006754829,0.0002693056,0.01149641],"study_design_scores_gemma":[0.000001638303,0.000003069207,0.0001184028,9.467684e-7,0.000002323747,0.000003415732,9.660192e-7,0.9988795,0.00009791538,0.0007982537,0.00009070169,0.000002879428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01488312,0.00005323458,0.9840523,0.00009976421,0.000017078,0.00002289776,0.00006123769,0.0001889184,0.0006214201],"genre_scores_gemma":[0.7861197,0.0002359653,0.2096302,0.0001159775,0.00006094902,0.0001745072,0.0003306324,0.0001134621,0.003218633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01497169,"threshold_uncertainty_score":0.02976912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06963737259607652,"score_gpt":0.33822529807823,"score_spread":0.2685879254821535,"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."}}