{"id":"W4321996504","doi":"10.5194/egusphere-egu23-10284","title":"A reproducible data-driven workflow for probabilistic seasonal streamflow forecasting over North America","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Calgary; University of Saskatchewan","funders":"","keywords":"Streamflow; Snowmelt; Environmental science; Snow; Climatology; Flood forecasting; Surface runoff; Hydrology (agriculture); Drainage basin; Meteorology; Geology; 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":[0.00221994,0.001140179,0.0006078189,0.001094006,0.001067947,0.001693578,0.002066571,0.0005155804,0.007902587],"category_scores_gemma":[0.005525553,0.0007955942,0.001625354,0.001337366,0.0004665202,0.001243309,0.001855968,0.001282201,0.003643956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001687029,"about_ca_system_score_gemma":0.005821507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06912153,"about_ca_topic_score_gemma":0.07737952,"domain_scores_codex":[0.9990644,0.00009056825,0.0001329448,0.0003847264,0.000223612,0.0001037709],"domain_scores_gemma":[0.9975707,0.0005555419,0.0001248902,0.0005654409,0.000886031,0.000297425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001055405,0.0005536396,0.02653398,0.0007081287,0.0004244401,0.001383536,0.002255161,0.2435864,0.04030221,0.01691468,0.2705996,0.3956828],"study_design_scores_gemma":[0.0004083999,0.00005937589,0.008966272,0.00007772503,0.00004426637,0.0001094726,0.0003633526,0.8515368,0.01631256,0.01629853,0.105673,0.0001503032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02200562,0.0001221849,0.7109939,0.0004009191,0.0001498352,0.0008542089,0.03076779,0.2275459,0.007159738],"genre_scores_gemma":[0.1424021,0.0002121901,0.7649649,0.0002729365,0.0000491848,0.001739789,0.07433485,0.01146977,0.004554225],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06912153,"threshold_uncertainty_score":0.1374384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1578699873285662,"score_gpt":0.284403636312506,"score_spread":0.1265336489839399,"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."}}