{"id":"W2033569897","doi":"10.1016/s0043-1354(00)00336-5","title":"Nonpoint source pollution: a distributed water quality modeling approach","year":2001,"lang":"en","type":"article","venue":"Water Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":94,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Nonpoint source pollution; Environmental science; Water quality; Hydrology (agriculture); Surface runoff; Watershed; Distributed element model; Geographic information system; Computer science; Remote sensing; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002806318,0.0001428382,0.0001676833,0.00007476119,0.000776961,0.00005746576,0.0003698594,0.00008649209,0.001541132],"category_scores_gemma":[0.00002014295,0.00008045822,0.0000604645,0.0001749536,0.0004133657,0.0001939965,0.001350219,0.0003491275,0.003761086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000160338,"about_ca_system_score_gemma":0.000002131541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001413309,"about_ca_topic_score_gemma":0.00004208996,"domain_scores_codex":[0.997178,0.0003976796,0.0002425348,0.0004918338,0.0006254391,0.001064515],"domain_scores_gemma":[0.9994588,0.000007891806,0.000009730978,0.0003891748,0.00002062625,0.0001137733],"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":[0.001193593,0.001679068,0.1233564,0.0001663711,0.000360129,0.0002015769,0.02749233,0.6967914,0.1225414,0.0007342752,0.02076519,0.004718297],"study_design_scores_gemma":[0.004173939,0.0005401722,0.01967438,0.00003611165,0.00007184824,0.00008783776,0.004720396,0.4709803,0.05222216,0.02783844,0.4176657,0.001988668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9314745,0.00001205887,0.0385682,0.007339875,0.00004222032,0.0003181073,0.000003428729,0.0000830471,0.02215855],"genre_scores_gemma":[0.9905411,0.00001974729,0.0001842162,0.0001965674,0.0000621018,0.00007651532,0.0000727093,0.00001335323,0.008833708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3969006,"threshold_uncertainty_score":0.9993716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1005522781594402,"score_gpt":0.3372068608052094,"score_spread":0.2366545826457692,"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."}}