{"id":"W1500874545","doi":"10.2166/wst.2002.0227","title":"Modeling diffuse pollution with a distributed approach","year":2002,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Surface runoff; Environmental science; Watershed; Water quality; Hydrology (agriculture); Distributed element model; Nonpoint source pollution; Pollution; Flood myth; Point source pollution; Geographic information system; Computer science; Remote sensing; Engineering; Geology","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":[0.0006423071,0.0006078024,0.0007385222,0.0004993991,0.0003926728,0.001224527,0.001196099,0.001008164,0.00220458],"category_scores_gemma":[0.001455089,0.0003610336,0.0008936257,0.0006657375,0.0008159943,0.001460505,0.001320797,0.000782259,0.0003226025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008750875,"about_ca_system_score_gemma":0.0007837602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008165064,"about_ca_topic_score_gemma":0.006726229,"domain_scores_codex":[0.9995573,0.0001312055,0.00001797501,0.0001350475,0.000117482,0.00004098522],"domain_scores_gemma":[0.9994712,0.0002205617,0.00007071917,0.000076071,0.0001243247,0.00003715162],"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":[0.00001593019,0.00003214781,0.0008392108,0.00001582847,0.00001842272,0.0000541745,0.00003131931,0.9832609,0.001073734,0.007217865,0.000186813,0.007253644],"study_design_scores_gemma":[0.000006703072,0.0000140459,0.0001230413,0.000001330555,0.00000619508,0.00000893677,0.000008983494,0.9946522,0.000181806,0.004644095,0.0003497891,0.000002798392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05018234,0.0001002245,0.944748,0.0001398972,0.00002272794,0.00004016496,0.0001101501,0.0003872679,0.00426921],"genre_scores_gemma":[0.8689916,0.0003285891,0.1207183,0.0000841041,0.00005243826,0.0002058344,0.0002145346,0.000116203,0.009288383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008165064,"threshold_uncertainty_score":0.01623505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01135496554617847,"score_gpt":0.1866870036715561,"score_spread":0.1753320381253777,"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."}}