{"id":"W4391650700","doi":"10.1016/j.jhydrol.2024.130849","title":"How extreme are flood peak distributions? A quasi-global analysis of daily discharge records","year":2024,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Global Institute for Water Security; Concordia University; University of Saskatchewan; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Flood myth; Generalized Pareto distribution; Extreme value theory; Streamflow; Environmental science; Generalized extreme value distribution; Parametric statistics; Flow (mathematics); Distribution (mathematics); STREAMS; Statistics; Shape parameter; Hydrology (agriculture); Drainage basin; Mathematics; Geology; Geography; Computer science; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000516445,0.000110752,0.0002011756,0.0004939914,0.0001767563,0.0006668497,0.000165851,0.0001852021,0.0009806924],"category_scores_gemma":[0.001433414,0.0001085008,0.0003119584,0.0009030337,0.0003421902,0.000710687,0.0003096738,0.0002149752,0.0001082839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000278184,"about_ca_system_score_gemma":0.0002313001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01099621,"about_ca_topic_score_gemma":0.01726087,"domain_scores_codex":[0.9999245,0.00003260321,0.000003159166,0.00002163424,0.000006722608,0.00001129986],"domain_scores_gemma":[0.9994417,0.0003457988,0.00006676905,0.0000656507,0.00004533063,0.00003490838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003307629,0.0000471077,0.8740731,0.00006833694,0.0004009615,0.0001800499,0.0009451428,0.06374755,0.009844009,0.004465584,0.001848669,0.04404869],"study_design_scores_gemma":[0.00000831556,0.00004005261,0.8947902,0.00000753086,0.00005641067,0.00005744564,0.0006199859,0.101228,0.0003139911,0.002141712,0.0007221006,0.00001437461],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995459,0.00007262686,0.003079046,0.0001070124,0.000002508654,0.000004333946,0.0005982795,0.00002634988,0.0006509845],"genre_scores_gemma":[0.9981537,0.00006594278,0.00115685,0.00001113419,0.000004051638,0.000003131657,0.0004437617,0.00001873517,0.0001425051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01099621,"threshold_uncertainty_score":0.02186435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01433032434167183,"score_gpt":0.2491783619934318,"score_spread":0.2348480376517599,"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."}}