{"id":"W2275234227","doi":"10.1016/j.jglr.2016.02.008","title":"Hydrologic modeling and evaluation of Best Management Practice scenarios for the Grand River watershed in Southern Ontario","year":2016,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; University of Guelph","funders":"","keywords":"Soil and Water Assessment Tool; Environmental science; Watershed; Hydrology (agriculture); Water quality; SWAT model; Watershed management; Wetland; Nonpoint source pollution; Nutrient pollution; Water resource management; Drainage basin; Streamflow; Geography; Ecology; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0009559463,0.0003902369,0.0003357084,0.0006190428,0.0009399439,0.001572825,0.001130797,0.0008333046,0.001494941],"category_scores_gemma":[0.00376122,0.000285473,0.0004545577,0.0009574787,0.0006710146,0.0008535348,0.0003996327,0.0005140511,0.0001007721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02427481,"about_ca_system_score_gemma":0.008902788,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.879288,"about_ca_topic_score_gemma":0.9280938,"domain_scores_codex":[0.9994972,0.0002011375,0.000027982,0.0000741113,0.00007896544,0.0001205798],"domain_scores_gemma":[0.9983619,0.0007813366,0.0001839718,0.0000814599,0.0004286423,0.000162662],"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":[0.0004333673,0.0005616838,0.08458105,0.00005507009,0.000101191,0.0002563259,0.0004504322,0.8990046,0.0009285314,0.002273918,0.002023001,0.009330697],"study_design_scores_gemma":[0.0001646958,0.0001704965,0.05423815,0.00001355709,0.00007187059,0.00001834962,0.001141508,0.9415946,0.0006044493,0.0007760838,0.0011742,0.00003205105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969217,0.00002413915,0.0003490265,0.000225757,0.000003321896,0.00003428579,0.0004802619,0.00002319954,0.001938271],"genre_scores_gemma":[0.9984158,0.00002785444,0.0006162812,0.00001098397,0.000001499536,0.00001602749,0.000297442,0.000004632314,0.0006093593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.120712,"threshold_uncertainty_score":0.2428457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09195242126704913,"score_gpt":0.342136787718728,"score_spread":0.2501843664516789,"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."}}