{"id":"W3137404772","doi":"10.2166/wcc.2021.302","title":"Application of the HBV model for the future projections of water levels using dynamically downscaled global climate model data","year":2021,"lang":"en","type":"article","venue":"Journal of Water and Climate Change","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Transport Canada","keywords":"Weather Research and Forecasting Model; Streamflow; Environmental science; Climatology; Climate change; Climate model; Arctic; Meteorology; Hydrology (agriculture); Geography; Drainage basin; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004728833,0.00009943854,0.0001991265,0.00001952662,0.0002377699,0.00002799626,0.0003034493,0.0000608363,0.00002265766],"category_scores_gemma":[0.000005981224,0.00004080589,0.00009526777,0.00006513293,0.00008916275,0.0002723679,0.0001097553,0.0001101625,5.627599e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008134998,"about_ca_system_score_gemma":0.00003741882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006926263,"about_ca_topic_score_gemma":0.0004687083,"domain_scores_codex":[0.9990336,0.00003423827,0.0003636795,0.0001316103,0.0001955115,0.0002413326],"domain_scores_gemma":[0.9993176,0.0000305764,0.0001769192,0.000254775,0.0001782898,0.00004185104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001990937,0.0006282154,0.5251732,0.002941942,0.0008335235,0.00001648166,0.02644678,0.3350223,0.03275358,0.002772078,0.0001669225,0.07125406],"study_design_scores_gemma":[0.0002894868,0.0000323336,0.009120055,0.0000385715,0.0001789746,0.00008561143,0.0009399151,0.9875089,0.0002555193,0.001446208,0.00003871969,0.00006569585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9407278,0.000264991,0.05305828,0.002930083,0.0002984485,0.0003340906,0.002302705,0.00000429795,0.00007926826],"genre_scores_gemma":[0.9957413,0.0006060976,0.003192792,0.0001676497,0.0001693373,0.000001279986,0.0001078236,0.000003723977,0.000009997862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6524866,"threshold_uncertainty_score":0.1828758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0681616726764185,"score_gpt":0.2828153740073595,"score_spread":0.214653701330941,"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."}}