{"id":"W2084117721","doi":"10.1007/s00477-014-0978-0","title":"Maximum entropy-Gumbel-Hougaard copula method for simulation of monthly streamflow in Xiangxi river, China","year":2014,"lang":"en","type":"article","venue":"Stochastic Environmental Research and Risk Assessment","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Kurtosis; Streamflow; Copula (linguistics); Gumbel distribution; Mathematics; Skewness; Quantile; Statistics; Principle of maximum entropy; Econometrics; Extreme value theory; Drainage basin","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":[0.001324266,0.0006639254,0.0007035345,0.0006219439,0.0006469896,0.0006853532,0.001071125,0.001445432,0.00124585],"category_scores_gemma":[0.002879323,0.000484343,0.0007781865,0.0004810823,0.000425026,0.0007972945,0.0007458368,0.0007677214,0.0001048971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008910109,"about_ca_system_score_gemma":0.002204688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05221292,"about_ca_topic_score_gemma":0.02413267,"domain_scores_codex":[0.9997106,0.0001407468,0.0000161189,0.00004613121,0.00004129512,0.00004503921],"domain_scores_gemma":[0.9991448,0.000544444,0.00005851818,0.00003405006,0.0001567988,0.00006144583],"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":[0.00001715902,0.00001477777,0.0009112977,0.00001289082,0.00001385628,0.00002289164,0.00001374073,0.9962007,0.0001899433,0.0007071156,0.00008796932,0.001807522],"study_design_scores_gemma":[0.000001262786,0.000001554354,0.00009029805,5.278945e-7,0.000001138862,6.782465e-7,0.000001404819,0.9997973,0.00002701491,0.00006793495,0.000009986873,9.49366e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5873404,0.0005653238,0.4047385,0.0004496172,0.00008348552,0.0001100417,0.0004536915,0.0005288952,0.005730196],"genre_scores_gemma":[0.9847229,0.00009336121,0.01369554,0.0000292787,0.00001350442,0.00008340607,0.0001741931,0.00004295023,0.001144907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05221292,"threshold_uncertainty_score":0.103818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133485429300542,"score_gpt":0.3403939632044117,"score_spread":0.3270454202743575,"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."}}