{"id":"W4239901034","doi":"10.5194/hess-2020-54","title":"Future streamflow regime changes in the United States: assessment using functional classification","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"U.S. Army Corps of Engineers; U.S. Geological Survey; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Center for Atmospheric Research; National Science Foundation","keywords":"Streamflow; Hydrograph; Climate change; Classification scheme; Environmental science; Flood myth; Climatology; Drainage basin; Representation (politics); Hydrology (agriculture); Geography; Computer science; Geology; Cartography","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":[0.001549201,0.0002448721,0.0001925623,0.002437255,0.0002854858,0.0006412948,0.0002305355,0.0002722525,0.0004289007],"category_scores_gemma":[0.00237091,0.00007302266,0.0002395877,0.001988478,0.0001939422,0.0004511749,0.0003888977,0.0001921419,0.00006590642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001038274,"about_ca_system_score_gemma":0.0004363355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05756347,"about_ca_topic_score_gemma":0.06107185,"domain_scores_codex":[0.9997215,0.000115792,0.00002270863,0.00004264366,0.00006615939,0.00003113828],"domain_scores_gemma":[0.998455,0.000572503,0.0002704233,0.000123213,0.0004675682,0.0001113101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001059953,0.0000924163,0.9479324,0.00002044888,0.00006040117,0.00005205298,0.0001547757,0.01895142,0.0005003414,0.0002875874,0.0009565073,0.03088577],"study_design_scores_gemma":[0.000005400744,0.00006862635,0.7872158,0.00001499175,0.00002081724,0.00002478379,0.0003274945,0.2110953,0.0003377769,0.0003245322,0.0005526629,0.0000118305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971747,0.00005004429,0.001250693,0.00005054533,0.000002932338,0.00002386006,0.0008689651,0.0000297228,0.0005485096],"genre_scores_gemma":[0.9972417,0.00002707496,0.001477429,0.000008876499,0.000002440989,0.00001892034,0.001130753,0.000001919377,0.00009068711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05756347,"threshold_uncertainty_score":0.1144568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06514910880095248,"score_gpt":0.2851909588645455,"score_spread":0.220041850063593,"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."}}