{"id":"W2126817991","doi":"10.1002/hyp.6874","title":"Development of a SWAT extension module to simulate riparian wetland hydrologic processes at a watershed scale","year":2008,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ministry of Environment; Canadian Water Network","keywords":"Wetland; Riparian zone; Environmental science; Hydrology (agriculture); Watershed; Surface runoff; Soil and Water Assessment Tool; SWAT model; Channel (broadcasting); Streamflow; Geology; Drainage basin; Ecology; Geography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000332455,0.0003706574,0.0005309696,0.00008878207,0.0007674602,0.00001140473,0.0004676822,0.0001914423,0.0007483778],"category_scores_gemma":[0.000300932,0.0002519433,0.00005702148,0.0006299278,0.0006367197,0.0002146187,0.001123498,0.0001449708,0.001008988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008867423,"about_ca_system_score_gemma":0.00002853703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000276093,"about_ca_topic_score_gemma":0.0002771041,"domain_scores_codex":[0.997383,0.00006664429,0.0005462652,0.0008838521,0.0004417559,0.0006784579],"domain_scores_gemma":[0.9991618,0.0001061999,0.0001640273,0.0003105583,0.00005150381,0.0002059563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003230021,0.002948013,0.7021434,0.001302537,0.0002981189,0.0004999295,0.01922928,0.161366,0.09969477,0.00001731377,0.007788194,0.00148245],"study_design_scores_gemma":[0.006648838,0.004211981,0.2811921,0.0002478986,0.0003536534,0.0003365619,0.0004109493,0.009790871,0.5105503,0.007563232,0.1745086,0.004184959],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931229,0.0001136095,0.0006359782,0.001054783,0.000049667,0.00053284,0.0000034751,0.0001699225,0.004316767],"genre_scores_gemma":[0.9937497,0.00009960827,0.003664468,0.001172387,0.00002580723,0.0001330667,0.0000193179,0.00001889055,0.001116776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4209513,"threshold_uncertainty_score":0.9999933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02841577067943587,"score_gpt":0.231559928048774,"score_spread":0.2031441573693381,"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."}}