{"id":"W3084077498","doi":"10.5194/egusphere-egu2020-12547","title":"A Methodological Framework to Combine Multiple Precipitation Datasets for Improving Streamflow Simulations: A test study in the Saskatchewan River basin, Canada","year":2020,"lang":"en","type":"article","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Global Institute for Water Security","funders":"","keywords":"Streamflow; Precipitation; Environmental science; Structural basin; Weighting; Benchmarking; Robustness (evolution); Computer science; Climatology; Drainage basin; Meteorology; Geology; Cartography; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01407829,0.0007883793,0.0004178313,0.002420763,0.001263597,0.002635648,0.002054803,0.0006846931,0.0004728019],"category_scores_gemma":[0.01853269,0.0004105735,0.0008468485,0.003561319,0.0009199744,0.001391524,0.002512219,0.0008441464,0.00007622362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009062455,"about_ca_system_score_gemma":0.01550126,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6363701,"about_ca_topic_score_gemma":0.7077999,"domain_scores_codex":[0.9960465,0.00189086,0.0003352848,0.0005724913,0.0009554478,0.000199323],"domain_scores_gemma":[0.9928967,0.001946508,0.0005859224,0.0007863996,0.003526572,0.000257888],"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":[0.0002172305,0.0004236695,0.1634834,0.0002808473,0.0009455746,0.0003474215,0.0007766929,0.5927222,0.006620019,0.02528081,0.00408649,0.2048157],"study_design_scores_gemma":[0.0001200832,0.0001179474,0.03566405,0.0001041157,0.0001086764,0.00004974951,0.000781337,0.9494071,0.003946421,0.00387491,0.005756775,0.00006881224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4796224,0.0008632247,0.5020182,0.003151962,0.00007753142,0.001747808,0.005311186,0.001201872,0.006005963],"genre_scores_gemma":[0.4623894,0.0002816073,0.5325087,0.0001842246,0.00002258095,0.0006248578,0.002982531,0.000104158,0.0009019783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3636299,"threshold_uncertainty_score":0.7315427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06470531766920429,"score_gpt":0.3047808906149556,"score_spread":0.2400755729457513,"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."}}