{"id":"W1979463845","doi":"10.1080/07011784.2013.780792","title":"Modeling the effects of agricultural BMPs on sediments, nutrients, and water quality of the Beaurivage River watershed (Quebec, Canada)","year":2013,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut National de la Recherche Scientifique","funders":"","keywords":"Environmental science; Soil and Water Assessment Tool; Buffer strip; SWAT model; Watershed; Hydrology (agriculture); Surface runoff; Water quality; Nonpoint source pollution; Universal Soil Loss Equation; Riparian buffer; Riparian zone; Drainage basin; Streamflow; Ecology; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005387898,0.0003457112,0.0004411908,0.0001177184,0.001116394,0.00008946379,0.0008323247,0.0001159602,0.0001548272],"category_scores_gemma":[0.00009016981,0.0001521387,0.0001407785,0.0001342378,0.001097687,0.0002593064,0.0002796734,0.0004150803,0.000009068145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000692072,"about_ca_system_score_gemma":0.000005906888,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9773329,"about_ca_topic_score_gemma":0.9903538,"domain_scores_codex":[0.9972024,0.0004772039,0.0006073227,0.0003693659,0.0003075736,0.001036161],"domain_scores_gemma":[0.9987059,0.00009710285,0.0001796239,0.0004253923,0.00007223123,0.0005197421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001192648,0.00008903231,0.1341008,0.0007066306,0.0008722114,0.0001414333,0.7987825,0.03127123,0.03041486,0.0000155331,0.00168992,0.001796592],"study_design_scores_gemma":[0.002439311,0.0005948975,0.6399813,0.001034746,0.0004797337,0.0002161638,0.007674773,0.001723551,0.1397182,0.003410288,0.2009271,0.001799981],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946208,0.0002222184,0.000004133727,0.003863552,0.0002150055,0.0005526665,0.00001227821,0.00000952215,0.0004998163],"genre_scores_gemma":[0.9972891,0.0001124521,0.0000143659,0.0007497618,0.00007752942,0.00002968627,0.000008181823,0.00002381999,0.00169514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7911077,"threshold_uncertainty_score":0.8586512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007414807000591828,"score_gpt":0.1747759570716705,"score_spread":0.1673611500710787,"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."}}