{"id":"W2068066018","doi":"10.2134/jeq2014.06.0246","title":"Using AnnAGNPS to Predict the Effects of Tile Drainage Control on Nutrient and Sediment Loads for a River Basin","year":2015,"lang":"en","type":"article","venue":"Journal of Environmental Quality","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Ottawa","funders":"","keywords":"Tile drainage; Environmental science; Hydrology (agriculture); Drainage basin; Watershed; Water quality; Nonpoint source pollution; Drainage; Sediment; Nutrient; Surface runoff; Total suspended solids; Environmental engineering; Soil water; Ecology; Geology; Chemical oxygen demand; Sewage treatment; Soil science; Biology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0001897474,0.0005725812,0.0002325402,0.0002622578,0.000229121,0.0005342097,0.0004794215,0.0003418035,0.0007531996],"category_scores_gemma":[0.0005778827,0.0003646678,0.0003942024,0.0002180212,0.000227004,0.0002270847,0.000294994,0.0002654861,0.0001229129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002089816,"about_ca_system_score_gemma":0.00235852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3512387,"about_ca_topic_score_gemma":0.3645684,"domain_scores_codex":[0.9999275,0.00001002179,0.00000555024,0.00002561324,0.0000160394,0.00001517366],"domain_scores_gemma":[0.9998319,0.00005983372,0.00002406095,0.00001023376,0.00005119123,0.0000227455],"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":[0.0001046662,0.00006922292,0.05368753,0.00002772398,0.00004285035,0.00004522391,0.00003247654,0.9363665,0.003103232,0.0001227438,0.0003589933,0.006038819],"study_design_scores_gemma":[0.00002362949,0.0000420684,0.01206505,0.000002794312,0.00001541931,0.000005693224,0.00001679875,0.9864618,0.0009442904,0.00006285521,0.0003526174,0.000006993363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934545,0.00003147164,0.003754811,0.0000278596,0.000005776534,0.00004431737,0.0009302028,0.0003285186,0.001422551],"genre_scores_gemma":[0.9940888,0.00002872158,0.003804595,0.00001019067,0.000001542154,0.00004603645,0.001295356,0.00002095073,0.0007038362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3512387,"threshold_uncertainty_score":0.6983885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100448385463223,"score_gpt":0.2680419898671739,"score_spread":0.2470375060125417,"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."}}