{"id":"W4318262517","doi":"10.1016/b978-0-323-95908-7.00003-7","title":"Multivariate hydrological frequency analysis, overview","year":2023,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Multivariate statistics; Univariate; Quantile; Copula (linguistics); Multivariate analysis; Computer science; Storm; Econometrics; Machine learning; Meteorology; Mathematics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009611606,0.001116892,0.0007441739,0.002102676,0.0001933954,0.001429206,0.0007758056,0.0008243929,0.02172902],"category_scores_gemma":[0.002013754,0.0008300276,0.0006924034,0.003817555,0.0004598509,0.001906463,0.0009122712,0.001322243,0.01184059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003306041,"about_ca_system_score_gemma":0.0006104416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002111658,"about_ca_topic_score_gemma":0.002927229,"domain_scores_codex":[0.9996326,0.00006394414,0.00003030144,0.00007946928,0.0001747588,0.0000189003],"domain_scores_gemma":[0.9993829,0.0003069965,0.00003014855,0.0000792009,0.0001739217,0.00002687725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002084901,0.00004997287,0.0003509159,0.0004037954,0.00004144106,0.00003622062,0.00003649753,0.008152268,0.001928501,0.02125873,0.08729894,0.880422],"study_design_scores_gemma":[0.00001713239,0.00006932592,0.00496487,0.0004114346,0.00006930919,0.0007174528,0.00006378532,0.0860213,0.003166429,0.1067663,0.7976444,0.00008823056],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001147058,0.06366445,0.8956897,0.00114201,0.0009775264,0.00007861971,0.001381514,0.003735198,0.03218392],"genre_scores_gemma":[0.027077,0.1963923,0.642094,0.001300945,0.006983097,0.0004389792,0.005960973,0.002435157,0.1173175],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02172902,"threshold_uncertainty_score":0.07269084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02657577384491348,"score_gpt":0.2602031471320678,"score_spread":0.2336273732871544,"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."}}