{"id":"W3023820845","doi":"10.2166/nh.2020.109","title":"Improved modelling of a Prairie catchment using a progressive two-stage calibration strategy with in situ soil moisture and streamflow data","year":2020,"lang":"en","type":"article","venue":"Hydrology research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"","keywords":"Streamflow; Environmental science; Water content; Calibration; Hydrology (agriculture); Moisture; Stage (stratigraphy); Hydrological modelling; Drainage basin; Soil science; Climatology; Meteorology; Geology; Geography; Cartography; Mathematics","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":[0.0006213194,0.0001221496,0.0002072974,0.0000611927,0.0001644962,0.00001754875,0.0002953235,0.00008195633,0.00003799325],"category_scores_gemma":[0.00002631302,0.00009664101,0.000009360633,0.0002848147,0.0007529826,0.0002802188,0.0009523231,0.0003454104,0.000003281511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000371357,"about_ca_system_score_gemma":0.00003195255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002744386,"about_ca_topic_score_gemma":0.004439827,"domain_scores_codex":[0.998362,0.0002523604,0.0001894788,0.0005488883,0.0002438502,0.0004033976],"domain_scores_gemma":[0.9994816,0.0000653707,0.0000672337,0.0002916693,0.00001299824,0.00008108096],"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":[0.0009371698,0.0002068724,0.2555119,0.0001206353,0.0001119676,0.0002275841,0.004175059,0.7187254,0.01906838,0.0001153474,0.0002081663,0.0005915261],"study_design_scores_gemma":[0.000921665,0.0005613602,0.001570211,0.00001208026,0.00001794747,0.000003307972,0.0004828184,0.9942945,0.001719279,0.0002377262,0.00007345561,0.0001056904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924693,0.0001661624,0.002862735,0.003415071,0.000005935041,0.0005385166,0.00001267082,0.00001355387,0.0005160465],"genre_scores_gemma":[0.9988313,0.00002066525,0.000876672,0.0001192487,0.00001859139,0.00003141015,0.00003216713,0.000009928158,0.0000599865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.275569,"threshold_uncertainty_score":0.414871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1246098509773684,"score_gpt":0.3422768182628646,"score_spread":0.2176669672854962,"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."}}