{"id":"W4402639429","doi":"10.1016/j.watres.2024.122474","title":"Patterns of nitrate load variability under surface water-groundwater interactions in agriculturally intensive valley watersheds","year":2024,"lang":"en","type":"article","venue":"Water Research","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Education and Child Care","funders":"","keywords":"Groundwater; Nitrate; Environmental science; Surface water; Hydrology (agriculture); Watershed; Environmental engineering; Geology; Ecology; Biology; Geotechnical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002697473,0.0001003183,0.0003035679,0.0006387332,0.0004910043,0.0008125207,0.0003033518,0.0003145645,0.0006966033],"category_scores_gemma":[0.0007029441,0.0001608118,0.0001745538,0.0008591932,0.0005267504,0.000372719,0.0005223572,0.0001598215,0.0001102788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007163744,"about_ca_system_score_gemma":0.0004878369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03660576,"about_ca_topic_score_gemma":0.07052097,"domain_scores_codex":[0.9997671,0.00004963797,0.00001578997,0.00007667745,0.00003617685,0.00005462432],"domain_scores_gemma":[0.9994448,0.000180716,0.0001409056,0.00002339873,0.00009393848,0.0001162804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000438252,0.000108659,0.9809595,0.00001233661,0.00006417118,0.0001127375,0.0009657391,0.000624038,0.01390052,0.0001111355,0.0001116351,0.002591169],"study_design_scores_gemma":[0.000003971187,0.00002619932,0.9983599,8.868313e-7,0.000005495897,0.0000224783,0.0003678412,0.0009785503,0.0001465119,0.00003657663,0.00004860491,0.000003010332],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999797,0.000006155232,0.00003275246,0.000005049803,2.468554e-7,0.000001054468,0.00005262408,0.000001685776,0.0001034024],"genre_scores_gemma":[0.9997225,0.000005292718,0.00003584613,0.000002830412,0.000001062384,0.000001959474,0.0001192567,0.000001297462,0.0001099992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03660576,"threshold_uncertainty_score":0.07278544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04416082426625732,"score_gpt":0.3132939608004525,"score_spread":0.2691331365341952,"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."}}