{"id":"W2964139753","doi":"10.1139/facets-2018-0028","title":"Quantifying the fate of wastewater nitrogen discharged to a Canadian river","year":2019,"lang":"en","type":"article","venue":"FACETS","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Wilfrid Laurier University","funders":"","keywords":"Biogeochemical cycle; Environmental science; Nutrient; Nitrification; Denitrification; Nitrogen cycle; Nutrient pollution; Wastewater; Nitrogen; Volatilisation; Estuary; Sewage treatment; Eutrophication; Nutrient cycle; Environmental chemistry; Hydrology (agriculture); Environmental engineering; Ecology; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009446376,0.00007194278,0.00007901886,0.00002422138,0.00005881807,0.00001276533,0.0002248388,0.00002670759,0.0003649729],"category_scores_gemma":[0.000005602658,0.00004393354,0.00003369623,0.0001094115,0.00004371352,0.00006816785,0.000104456,0.00005129525,0.003267104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006961952,"about_ca_system_score_gemma":0.000007930733,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06066729,"about_ca_topic_score_gemma":0.01465016,"domain_scores_codex":[0.999351,0.00002145938,0.00009246905,0.0001460134,0.0001440151,0.0002450857],"domain_scores_gemma":[0.9996262,0.000008915114,0.00002209358,0.0002255148,0.00000402818,0.0001132872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005595084,0.000006880732,0.9923514,0.000002855534,0.000005812198,0.000001038867,0.001864388,0.0006032363,0.00404957,0.00003628827,0.0008414211,0.0002314945],"study_design_scores_gemma":[0.0009063867,0.0001616792,0.8451484,0.00005254845,0.00003067829,0.000009540091,0.0008417505,0.005750517,0.04257419,0.004055008,0.09986486,0.0006044728],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964122,0.000005092458,0.000007659061,0.0009856408,0.000142845,0.0002122488,0.00002202881,0.000008480671,0.002203843],"genre_scores_gemma":[0.9987955,0.000001275087,0.0001260677,0.0003409818,0.000007590151,0.00000584036,0.000005847675,0.000007967528,0.0007088953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1472031,"threshold_uncertainty_score":0.9975089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388104060234134,"score_gpt":0.2148197000220669,"score_spread":0.2009386594197256,"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."}}