{"id":"W4220840485","doi":"10.5194/egusphere-egu22-5238","title":"Celebrating Eric Wood's advances in large domain hydrologic modeling","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Hydrological modelling; Streamflow; Domain (mathematical analysis); Environmental science; Representation (politics); Hydrology (agriculture); Environmental resource management; Drainage basin; Geography; Climatology; Political science; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003996972,0.0008666241,0.0005614659,0.0009724147,0.0009464429,0.003471974,0.001323215,0.001640084,0.009713929],"category_scores_gemma":[0.009892696,0.0004938977,0.0007158308,0.001725407,0.001239188,0.005518436,0.00238009,0.005004746,0.003945371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001346459,"about_ca_system_score_gemma":0.002142288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00862793,"about_ca_topic_score_gemma":0.007053202,"domain_scores_codex":[0.9981511,0.0003342681,0.00006614775,0.0003927912,0.0009234672,0.0001321992],"domain_scores_gemma":[0.9951223,0.002353492,0.000180261,0.0004782586,0.001260101,0.0006055869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003494551,0.0000596334,0.001012236,0.0001142786,0.00002717446,0.0001934512,0.0003764844,0.01512556,0.0009250134,0.1509368,0.6156183,0.2155763],"study_design_scores_gemma":[0.000008233743,0.00001592416,0.0002583042,0.00007398492,0.000009494966,0.0001333537,0.00006042396,0.03254988,0.001106564,0.03937269,0.926383,0.00002813155],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.009446115,0.03210854,0.588911,0.2050611,0.01371255,0.00008135197,0.001273475,0.005417867,0.1439881],"genre_scores_gemma":[0.1420982,0.06778862,0.4761615,0.01933856,0.01264308,0.0001992663,0.002129306,0.005701401,0.2739401],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.009713929,"threshold_uncertainty_score":0.03249627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01348712943949232,"score_gpt":0.2425741806299718,"score_spread":0.2290870511904795,"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."}}