{"id":"W2032970891","doi":"10.1002/hyp.8037","title":"Internal catchment process simulation in a snow‐dominated basin: performance evaluation with spatiotemporally variable runoff generation and groundwater dynamics","year":2011,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Forests; Government of British Columbia; University of British Columbia","funders":"","keywords":"Environmental science; Watershed; Hydrology (agriculture); Hydrological modelling; Surface runoff; Snowpack; Baseflow; Catchment hydrology; Equifinality; Range (aeronautics); Snow; Spatial variability; Drainage basin; Continuous simulation; Streamflow; Meteorology; Geology; Climatology; Computer science; Ecology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00104786,0.0007198066,0.0006288155,0.0004203728,0.0003536872,0.0007086036,0.0008358131,0.0007514399,0.0006806053],"category_scores_gemma":[0.001692023,0.0003179862,0.0005564369,0.0004122433,0.0005420199,0.0005761187,0.0006316488,0.0005760948,0.00007740513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001179503,"about_ca_system_score_gemma":0.0009524662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02916336,"about_ca_topic_score_gemma":0.01153588,"domain_scores_codex":[0.9997509,0.0001140969,0.00001438383,0.00005128373,0.00002970371,0.00003958401],"domain_scores_gemma":[0.9987722,0.0007284132,0.0001114111,0.0001001821,0.0001677337,0.0001199224],"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":[0.0001386217,0.0001614543,0.005006087,0.00001001581,0.00002137024,0.00002802382,0.00003566287,0.9904958,0.001156564,0.0001887505,0.00005100949,0.002706717],"study_design_scores_gemma":[0.00001454557,0.00007762099,0.0005430313,8.740647e-7,0.000004657081,0.00000174803,0.000008613292,0.9987229,0.0005747345,0.00003347318,0.00001498168,0.000002762484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940097,0.0000136836,0.005090897,0.00002684833,0.000004351475,0.00001945173,0.00004877906,0.000137425,0.0006487851],"genre_scores_gemma":[0.9979214,0.00001068693,0.001840599,0.000006113306,0.000001135959,0.00001138004,0.00005761007,0.000008152127,0.0001429629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02916336,"threshold_uncertainty_score":0.05798721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02768757661343302,"score_gpt":0.2430369058430347,"score_spread":0.2153493292296016,"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."}}