{"id":"W2908732043","doi":"10.1016/j.ejrh.2018.12.008","title":"Hydrological variability affects particulate nitrogen and phosphorus in streams of the Northern Great Plains","year":2019,"lang":"en","type":"article","venue":"Journal of Hydrology Regional Studies","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Western University; Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Snowmelt; Environmental science; Nutrient; STREAMS; Hydrology (agriculture); Particulates; Phosphorus; Water year; Discharge; Precipitation; Streamflow; Surface runoff; Drainage basin; Ecology; Geography; Geology; Biology; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005145633,0.0001113184,0.0003355003,0.00002217947,0.00005425745,0.000002769684,0.000172607,0.00007305386,0.00001114896],"category_scores_gemma":[0.00007660616,0.0000595734,0.00009603255,0.000113795,0.0005796053,0.00006788505,0.0002327154,0.0001886267,0.000005853176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008208661,"about_ca_system_score_gemma":0.000008778743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004608416,"about_ca_topic_score_gemma":0.00009331545,"domain_scores_codex":[0.9989869,0.0001721648,0.0002845978,0.0001538505,0.0002173033,0.0001851839],"domain_scores_gemma":[0.9993066,0.0002644437,0.0002455771,0.0001238911,0.00001802687,0.00004143443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000175196,0.000091137,0.994224,0.000005699423,0.00007358666,0.0000168934,0.0004154942,0.004476444,0.00008188697,0.0000513281,0.00004657563,0.0003417837],"study_design_scores_gemma":[0.001009962,0.000468627,0.9464034,0.00002305156,0.00004862381,0.000202053,0.00009676482,0.001606215,0.000140697,0.04952965,0.0003813965,0.0000895839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974167,0.0005191709,0.000001408308,0.001679936,0.0001179529,0.0001125258,0.000001290361,0.000002545812,0.0001484141],"genre_scores_gemma":[0.9995033,0.00025072,0.00003071756,0.0001750693,0.00001774662,0.000002328473,2.379721e-7,0.000003939307,0.00001596702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04947833,"threshold_uncertainty_score":0.2429333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184382188730393,"score_gpt":0.2233955819792204,"score_spread":0.2115517600919165,"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."}}