{"id":"W2105005531","doi":"10.5194/hess-14-2577-2010","title":"Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites","year":2010,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cold Regions Research and Engineering Laboratory; Japan Agency for Marine-Earth Science and Technology; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Snowmelt; Snow; Albedo (alchemy); Environmental science; Biosphere; Surface runoff; Flow routing; Meteorology; Physics; Geology; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001613386,0.0005834306,0.0005341272,0.0003624468,0.0004122562,0.0005701825,0.001316275,0.0006423588,0.001458428],"category_scores_gemma":[0.001842302,0.0002516554,0.0005422059,0.0004546064,0.0002220039,0.0009934073,0.0007522688,0.0007530011,0.0002655078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007433026,"about_ca_system_score_gemma":0.0006777582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.014977,"about_ca_topic_score_gemma":0.01393013,"domain_scores_codex":[0.9996601,0.0001079301,0.00002096492,0.0000718199,0.0001032338,0.00003593597],"domain_scores_gemma":[0.9990219,0.0002610652,0.0000651993,0.0002140267,0.0003437504,0.00009414585],"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":[0.0005853504,0.0008274776,0.09236101,0.0001525292,0.0001844515,0.0002629644,0.00009685931,0.8256698,0.01856158,0.000606035,0.001046015,0.05964597],"study_design_scores_gemma":[0.0001465002,0.0001746425,0.02484553,0.000008874831,0.00003681453,0.000017645,0.00004543404,0.9657765,0.008191405,0.0001673123,0.0005692964,0.00002015852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815419,0.00008212327,0.01421856,0.0001004787,0.0000411324,0.0001359174,0.0008967488,0.0007586883,0.002224338],"genre_scores_gemma":[0.9881167,0.00003046457,0.01084233,0.00001840598,0.000009493579,0.0000478048,0.0006385549,0.00003993902,0.0002561594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.014977,"threshold_uncertainty_score":0.02977967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02863416963673636,"score_gpt":0.23008407722368,"score_spread":0.2014499075869437,"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."}}