{"id":"W4392511180","doi":"10.5194/hess-28-1127-2024","title":"On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow","year":2024,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Hydro-Québec","keywords":"Snow; Hydrological modelling; Environmental science; Distributed element model; Hydrology (agriculture); Geology; Climatology; Geomorphology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002537178,0.001123357,0.0007461705,0.0006914457,0.0003706505,0.0007638086,0.0006022792,0.001149746,0.0007937442],"category_scores_gemma":[0.00474149,0.0005125434,0.0007892709,0.0005197424,0.0005731496,0.0007140478,0.0008837062,0.001019602,0.0001016541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009606238,"about_ca_system_score_gemma":0.0009312149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008682649,"about_ca_topic_score_gemma":0.005059811,"domain_scores_codex":[0.9995587,0.0002316272,0.00002123696,0.00008218562,0.00006184504,0.0000443219],"domain_scores_gemma":[0.9981907,0.001266672,0.0001859117,0.00009297745,0.0002184601,0.00004525404],"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":[0.00001089288,0.00001114432,0.0003945577,0.000006319757,0.000008096408,0.000006962402,0.000005448564,0.9977145,0.0001582753,0.0001289452,0.00002238908,0.001532428],"study_design_scores_gemma":[0.000003073088,0.00001179638,0.000134556,0.000001686562,0.000001836648,0.00000121645,0.000004161418,0.9995897,0.0001368478,0.00009288941,0.00002074719,0.000001387867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6649535,0.0003337366,0.3296154,0.0003190011,0.00004164613,0.0001423868,0.0001896984,0.0003564444,0.004048306],"genre_scores_gemma":[0.9797543,0.00004298063,0.01968897,0.00002889639,0.000003445857,0.00006064356,0.00008886899,0.00001965677,0.0003122195],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008682649,"threshold_uncertainty_score":0.01726419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009903728168844904,"score_gpt":0.2038314305826318,"score_spread":0.1939277024137869,"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."}}