{"id":"W1511690701","doi":"10.1029/2008wr007490","title":"Index flood–based multivariate regional frequency analysis","year":2009,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Univariate; Quantile; Bivariate analysis; Multivariate statistics; Multivariate analysis; Flood myth; Statistics; Copula (linguistics); Homogeneity (statistics); Index (typography); Bivariate data; Econometrics; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001632363,0.0001630411,0.0002673628,0.000535332,0.0005156447,0.00008020081,0.000655764,0.000177766,0.007488881],"category_scores_gemma":[0.00004936164,0.000110541,0.0002346385,0.001843545,0.0004584555,0.0001581014,0.000166973,0.0005057446,0.002748989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001262917,"about_ca_system_score_gemma":0.000008303286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003448936,"about_ca_topic_score_gemma":0.0006762294,"domain_scores_codex":[0.9965612,0.0006030719,0.0002718217,0.0006074249,0.001108737,0.0008477521],"domain_scores_gemma":[0.9990085,0.00009618624,0.00003287875,0.0006028386,0.00003289893,0.0002267338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003249899,0.0006426035,0.8719524,0.000006876864,0.0006398209,0.0002577417,0.005659543,0.06780318,0.04447117,0.00009117372,0.003225167,0.004925304],"study_design_scores_gemma":[0.001217303,0.0003911672,0.7625751,0.000009847518,0.0003178585,0.000005820477,0.0001366329,0.1417526,0.008838969,0.01040277,0.07372791,0.0006239978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783952,0.00003767412,0.0008423651,0.003969138,0.00001065527,0.0001297097,0.000002890678,0.00007953855,0.01653284],"genre_scores_gemma":[0.9959174,0.00000392734,0.000507782,0.0005797175,0.0000656721,0.00001629587,0.00003457626,0.000012724,0.002861878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1093773,"threshold_uncertainty_score":0.9980275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03600302257378379,"score_gpt":0.3194211930821281,"score_spread":0.2834181705083443,"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."}}