{"id":"W2753638051","doi":"10.1002/hyp.11346","title":"A modelling framework to simulate field‐scale nitrate response and transport during snowmelt: The WINTRA model","year":2017,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Global Institute for Water Security; University of Saskatchewan","funders":"Environment and Climate Change Canada; Canadian Water Network; Agriculture and Agri-Food Canada; Canada Research Chairs","keywords":"Snowmelt; Snowpack; Surface runoff; Meltwater; Snow; Environmental science; Hydrology (agriculture); Biogeochemical cycle; Atmospheric sciences; Geology; Chemistry; Environmental chemistry; Geomorphology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004714617,0.0007058992,0.0005665538,0.0005290678,0.0008144578,0.001270136,0.001758904,0.001272558,0.002281029],"category_scores_gemma":[0.001041906,0.0004948777,0.0009314252,0.0005460224,0.0004310883,0.001232876,0.0007127961,0.0008110919,0.0002879295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001632552,"about_ca_system_score_gemma":0.002545012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1095516,"about_ca_topic_score_gemma":0.0766739,"domain_scores_codex":[0.9998834,0.00002924621,0.000008439825,0.00002896321,0.0000240637,0.00002582269],"domain_scores_gemma":[0.9996611,0.0001524071,0.00003636394,0.00002108563,0.00009465294,0.00003449922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002096656,0.0000346296,0.0008317013,0.000009646676,0.00002016937,0.00003794549,0.0000197614,0.9943983,0.0006196125,0.002023753,0.0001987146,0.00178485],"study_design_scores_gemma":[0.000006866799,0.000005908817,0.00006740206,9.896194e-7,0.000002803313,0.000001872463,0.00000415629,0.9993312,0.00008280575,0.0002694311,0.0002242233,0.00000239322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6067314,0.000443725,0.3594623,0.0007526168,0.000214596,0.0004331108,0.002782906,0.00253048,0.026649],"genre_scores_gemma":[0.9405316,0.0003304998,0.05059097,0.00007544536,0.0000410334,0.0003323783,0.0009858268,0.0002128051,0.006899448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1095516,"threshold_uncertainty_score":0.2178278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03819669686684152,"score_gpt":0.2510530984763534,"score_spread":0.2128564016095119,"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."}}