{"id":"W2914235725","doi":"10.1080/07011784.2019.1575774","title":"Implications of stubble management on snow hydrology and meltwater partitioning","year":2019,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Snowmelt; Environmental science; Meltwater; Hydrology (agriculture); Surface runoff; Snow; Infiltration (HVAC); Evapotranspiration; Advection; Water balance; Arid; Geology; Geography; Ecology; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001728364,0.0003662855,0.000223534,0.0003652366,0.0004944526,0.0007733805,0.0005320056,0.0003914721,0.001065207],"category_scores_gemma":[0.0004400585,0.0001602717,0.0005177747,0.0004137527,0.0004263875,0.0006054542,0.0003674676,0.0002751458,0.00008662933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003114185,"about_ca_system_score_gemma":0.002112696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4351781,"about_ca_topic_score_gemma":0.5433719,"domain_scores_codex":[0.9999042,0.00000870589,0.00000488033,0.00002555784,0.00001724968,0.00003941426],"domain_scores_gemma":[0.9998662,0.00003828259,0.00002141666,0.00001178744,0.00002655179,0.00003557134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002651362,0.0001372784,0.3440917,0.0000868709,0.0001513857,0.000528212,0.0002676213,0.5794919,0.05732559,0.001410302,0.0005250089,0.01571902],"study_design_scores_gemma":[0.00002825206,0.00007501534,0.5018294,0.00001262901,0.00004468431,0.00007341905,0.0003796046,0.4915298,0.004494242,0.0005690649,0.0009322113,0.0000316355],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975617,0.00007374142,0.0007307109,0.00004687879,0.000005031527,0.00001259204,0.0003597544,0.00003187522,0.001177815],"genre_scores_gemma":[0.9991308,0.00006590354,0.000250952,0.000007272112,8.755473e-7,0.000002785242,0.0002212564,0.000006978193,0.0003132837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4351781,"threshold_uncertainty_score":0.8652902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142412877977569,"score_gpt":0.1882977561330667,"score_spread":0.1740564683353098,"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."}}