{"id":"W2068589359","doi":"10.1111/j.1752-1688.2002.tb04350.x","title":"MODELING THE HYDROCHEMISTRY OF THE CANNONSVILLE WATERSHED WITH GENERALIZED WATERSHED LOADING FUNCTIONS (GWLF)<sup>1</sup>","year":2002,"lang":"en","type":"article","venue":"JAWRA Journal of the American Water Resources Association","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"Smiths Detection (Canada)","funders":"U.S. Geological Survey","keywords":"Watershed; Sediment; Environmental science; Hydrology (agriculture); Streamflow; Nutrient; Particulates; Geology; Drainage basin; Geotechnical engineering; Ecology; Geomorphology","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":[0.0003138824,0.0004402784,0.000190924,0.00028143,0.0004532047,0.0008680194,0.0007959271,0.0008501837,0.0009787118],"category_scores_gemma":[0.0007999566,0.000246916,0.0003274613,0.0004835427,0.0005047599,0.0006878702,0.0003651879,0.0003516926,0.0001415394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00339727,"about_ca_system_score_gemma":0.001861462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1527184,"about_ca_topic_score_gemma":0.1291608,"domain_scores_codex":[0.9998866,0.00003262443,0.000005053132,0.00002782538,0.00001838286,0.00002957971],"domain_scores_gemma":[0.9997436,0.00009276516,0.00004023546,0.00002055887,0.00007017925,0.00003254742],"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":[0.00002180454,0.00002794605,0.01440899,0.000009105059,0.0000131365,0.00005814212,0.00004227513,0.9795447,0.001223647,0.0009539578,0.0004107276,0.003285552],"study_design_scores_gemma":[0.000005964474,0.000007565257,0.002750172,0.000001628596,0.00000434519,0.000006686013,0.00001861824,0.9959763,0.00058006,0.0003708765,0.0002727815,0.00000502285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744453,0.00002774093,0.02160945,0.0001979019,0.000007932037,0.00002360632,0.0004671764,0.000324916,0.002895918],"genre_scores_gemma":[0.9942006,0.00002557746,0.004612451,0.00001930023,0.000002523468,0.00001868044,0.0002340645,0.00002645482,0.0008604477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1527184,"threshold_uncertainty_score":0.3036589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007789436302949303,"score_gpt":0.1858215491069052,"score_spread":0.1780321128039558,"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."}}