{"id":"W4317538359","doi":"10.5194/hess-27-453-2023","title":"A snow and glacier hydrological model for large catchments – case study for the Naryn River, central Asia","year":2023,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Global Water Futures; University of Bristol; Leverhulme Trust","keywords":"Snow; Environmental science; Snowmelt; Glacier; Streamflow; Drainage basin; Hydrology (agriculture); Percentile; Climatology; Snowpack; Hydrological modelling; Physical geography; Meteorology; Geology; Geography; Statistics","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":[0.0007003827,0.0007235283,0.0005047272,0.0003371657,0.0005535371,0.0007990824,0.001028274,0.0007547994,0.0008807342],"category_scores_gemma":[0.0009282416,0.0003733969,0.0005718084,0.0006141631,0.0005725452,0.0005705163,0.0005398482,0.0005207168,0.00008137673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00193284,"about_ca_system_score_gemma":0.001557957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1179176,"about_ca_topic_score_gemma":0.09024383,"domain_scores_codex":[0.9998405,0.00006532708,0.00001053038,0.00003492467,0.00001467749,0.00003402827],"domain_scores_gemma":[0.9995227,0.0002399361,0.00005796771,0.00004236283,0.0000757297,0.00006118418],"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":[0.0001482814,0.0002472014,0.04011657,0.00003389905,0.00005541919,0.0007448635,0.000151726,0.9529046,0.00104893,0.0007932942,0.0004770738,0.003278056],"study_design_scores_gemma":[0.00005759991,0.00008052547,0.009202932,0.000006698573,0.00002071263,0.00004040122,0.0001789827,0.9893137,0.0005023075,0.0002855734,0.0003009151,0.000009649735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967836,0.00004171196,0.001758959,0.00005948144,0.000004831716,0.00003490453,0.0002089285,0.00005785799,0.001049736],"genre_scores_gemma":[0.9966981,0.00003851271,0.002174257,0.00001687307,0.000003829471,0.00003958508,0.0002889828,0.00001507749,0.0007247236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1179176,"threshold_uncertainty_score":0.2344625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05421590241258585,"score_gpt":0.2724950489293931,"score_spread":0.2182791465168073,"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."}}