{"id":"W4366975252","doi":"10.2166/wcc.2023.014","title":"Analysis of parameter uncertainty in SWAT model using a Bayesian Box–Cox transformation three-level factorial analysis method: a case of Naryn River Basin","year":2023,"lang":"en","type":"article","venue":"Journal of Water and Climate Change","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Xiamen University of Technology; Xiamen University; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Environmental science; Surface runoff; Glacier; Hydrology (agriculture); Climate change; Streamflow; Flood myth; Drainage basin; Statistics; Mathematics; Physical geography; Geography; Geology; Ecology","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":[0.002144368,0.0004456337,0.0004724581,0.0007279228,0.0006400088,0.0007005993,0.0006027291,0.0005232103,0.000997906],"category_scores_gemma":[0.004298735,0.0002274314,0.0009237587,0.0005406605,0.000456969,0.0006021876,0.0005379951,0.0005860441,0.00005644026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007338214,"about_ca_system_score_gemma":0.001090357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02856267,"about_ca_topic_score_gemma":0.02018864,"domain_scores_codex":[0.9992043,0.0003585187,0.00003628636,0.0001609695,0.0001493063,0.00009060012],"domain_scores_gemma":[0.9971918,0.002105232,0.0002233834,0.0001216901,0.00030636,0.0000515225],"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":[0.0001301691,0.00009706421,0.04236517,0.00005483857,0.00009965975,0.000724577,0.000196801,0.9211276,0.002944159,0.009234371,0.0005588362,0.0224668],"study_design_scores_gemma":[0.000002349725,0.00001060361,0.002131082,0.000001593945,0.000005734606,0.00001353971,0.00001989093,0.9968695,0.0002285786,0.0006331283,0.000079302,0.000004691725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7922316,0.00007520321,0.2055858,0.0001371736,0.00001385802,0.00004672022,0.0002443545,0.0001814088,0.001483825],"genre_scores_gemma":[0.9834549,0.00002471329,0.01593647,0.000007025844,0.000005025523,0.00003436294,0.0001222347,0.00002100184,0.0003942311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02856267,"threshold_uncertainty_score":0.0567928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07736729401714394,"score_gpt":0.3103784774820922,"score_spread":0.2330111834649483,"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."}}