{"id":"W4313480414","doi":"10.1002/hyp.14802","title":"Using stable water isotopes to evaluate water flow and nonpoint source pollutant contributions in three southern Ontario agricultural headwater streams","year":2023,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; Ministry of Environment; Ministry of the Environment, Conservation and Parks; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tile drainage; Hydrology (agriculture); Hydrograph; Soil water; STREAMS; Environmental science; Surface runoff; Antecedent moisture; Drainage; Drainage basin; Nonpoint source pollution; Soil science; Geology; Ecology; Runoff curve number; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000170981,0.0002417449,0.0001945367,0.0008822839,0.001268441,0.0008418093,0.0002922325,0.0002225655,0.0006866359],"category_scores_gemma":[0.0004333749,0.0001889721,0.0001768962,0.001351804,0.0006324295,0.0001734669,0.0004428481,0.0001541263,0.00009233163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006321717,"about_ca_system_score_gemma":0.004257159,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8567521,"about_ca_topic_score_gemma":0.9589084,"domain_scores_codex":[0.9998181,0.00000996081,0.000009455885,0.00003777621,0.00007657328,0.00004815523],"domain_scores_gemma":[0.999679,0.00003049406,0.00006640372,0.0000092333,0.0001374935,0.0000773732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001792317,0.00003350132,0.9699369,0.00003132384,0.0000435022,0.0002008755,0.00211476,0.0004935684,0.01748139,0.00007724873,0.0002117117,0.009196015],"study_design_scores_gemma":[0.000005620368,0.00001918691,0.9974589,0.000002096404,0.000009542642,0.00001370387,0.0007572626,0.000449064,0.0007453552,0.00002171818,0.0005129441,0.00000461021],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992782,0.00001661119,0.00006773335,0.00000685484,5.067635e-7,0.00001200743,0.0001769563,0.000003499568,0.0004376025],"genre_scores_gemma":[0.9981024,0.00004739689,0.0003431027,0.00001018471,0.00000108575,0.00001870777,0.000491336,0.000003306195,0.0009825048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1432479,"threshold_uncertainty_score":0.288183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02266114160285609,"score_gpt":0.2370557073959353,"score_spread":0.2143945657930792,"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."}}