{"id":"W4292833122","doi":"10.1002/hyp.14682","title":"Pulling the rabbit out of the hat: Unravelling hidden nitrogen legacies in <scp>catchment‐scale</scp> water quality models","year":2022,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Helmholtz-Gemeinschaft","keywords":"Environmental science; Reactive nitrogen; Eutrophication; Water quality; Surface water; Greenhouse gas; Environmental protection; Manure; Nutrient pollution; Hydrology (agriculture); Environmental engineering; Ecology; Nitrogen; Nutrient; Oceanography; Chemistry; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008473188,0.000183752,0.0002365837,0.0000235286,0.0004531832,0.00004000366,0.0009476515,0.00007050298,0.00007991682],"category_scores_gemma":[0.00009514979,0.0000869514,0.00009600039,0.0003345631,0.000416177,0.0001928848,0.001068718,0.000376943,0.00002870055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008696322,"about_ca_system_score_gemma":0.00001571899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002395942,"about_ca_topic_score_gemma":0.00005835319,"domain_scores_codex":[0.9978551,0.0002603273,0.0004189278,0.0003973061,0.0006102427,0.0004581582],"domain_scores_gemma":[0.9992001,0.000287142,0.0001330305,0.0003164227,0.00001467846,0.00004863746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003787405,0.0003909372,0.660865,0.00007071585,0.00001923203,0.000007175541,0.01240221,0.3235244,0.002018776,0.0002483712,0.0001200937,0.0002951539],"study_design_scores_gemma":[0.001061602,0.000298639,0.008145582,0.00003286757,0.00007368773,0.00002642174,0.007227619,0.08001152,0.06141248,0.8329581,0.008379512,0.0003719406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947529,0.0001971713,0.000309147,0.001132108,0.0001419194,0.0002991097,0.0000169032,0.00003924015,0.003111479],"genre_scores_gemma":[0.9987448,0.00005373774,0.00007081538,0.0005694639,0.00002582596,0.0001097709,0.00001160369,0.00001168968,0.0004023098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8327097,"threshold_uncertainty_score":0.3545775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03047651380287256,"score_gpt":0.2364374516337328,"score_spread":0.2059609378308602,"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."}}