{"id":"W2808916139","doi":"10.2134/jeq2017.09.0369","title":"A Field‐Scale Approach to Estimate Nitrate Loading to Groundwater","year":2018,"lang":"en","type":"article","venue":"Journal of Environmental Quality","topic":"Groundwater and Isotope Geochemistry","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Agriculture and Agri-Food Canada; University of Calgary","funders":"Agriculture and Agri-Food Canada; Canadian Water Network","keywords":"Groundwater recharge; Groundwater; Hydraulic conductivity; Environmental science; Flux (metallurgy); Hydrology (agriculture); Soil science; Precipitation; Groundwater model; Aquifer; Geology; Soil water; Chemistry; Meteorology; Geography; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000301672,0.0003426547,0.000457179,0.0006338451,0.0002832264,0.0003151051,0.0004986528,0.0003640103,0.0009631463],"category_scores_gemma":[0.0002746086,0.000206088,0.0001770069,0.0004951769,0.0001969054,0.0002648366,0.0002578921,0.000285941,0.0003242819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005124684,"about_ca_system_score_gemma":0.0004552326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01002279,"about_ca_topic_score_gemma":0.01996608,"domain_scores_codex":[0.9998536,0.0000206862,0.000005001098,0.00006647045,0.00004379891,0.00001049005],"domain_scores_gemma":[0.9998472,0.00003026791,0.00003387541,0.00001801803,0.00005800007,0.00001265924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000184002,0.000197484,0.03143652,0.0001706647,0.00003999223,0.00005209378,0.00007677091,0.00403294,0.8891402,0.0002891973,0.001004347,0.07337578],"study_design_scores_gemma":[0.0001482199,0.001567346,0.4594895,0.00006002864,0.0001510145,0.0004103826,0.0002877517,0.1429484,0.3752875,0.001770811,0.01775534,0.00012363],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6900957,0.0005822634,0.2934644,0.0001229175,0.00003929163,0.0009825106,0.004008559,0.001783688,0.008920753],"genre_scores_gemma":[0.727259,0.0005325979,0.2648182,0.0002272447,0.00002216509,0.001309194,0.001846499,0.00006553977,0.003919563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01002279,"threshold_uncertainty_score":0.01992887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01901247808632016,"score_gpt":0.2652246053121475,"score_spread":0.2462121272258273,"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."}}