{"id":"W1906019123","doi":"10.1002/hyp.9226","title":"Reconstructing snowmelt runoff in the Yukon River basin using the SWEHydro model and AMSR‐E observations","year":2012,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lehigh University; National Aeronautics and Space Administration","keywords":"Snowmelt; Snow; Environmental science; Surface runoff; Snowpack; Water year; Hydrology (agriculture); Meltwater; Hydrograph; Climatology; Atmospheric sciences; Drainage basin; Geology; Geomorphology","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":[0.0001823826,0.000368476,0.0002441979,0.0004404047,0.0003594201,0.0005103562,0.0005134343,0.0006059544,0.0006776003],"category_scores_gemma":[0.0004656254,0.0002956024,0.0004928925,0.0004727363,0.0002747848,0.0004890276,0.0003390174,0.0001845375,0.0001407413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001606676,"about_ca_system_score_gemma":0.001210796,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1640203,"about_ca_topic_score_gemma":0.1427117,"domain_scores_codex":[0.9999185,0.00001498794,0.000005175744,0.00002875796,0.000009257858,0.00002336659],"domain_scores_gemma":[0.9998457,0.00004340553,0.00001781061,0.00002279302,0.00003531306,0.00003495091],"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":[0.0002236636,0.000170149,0.1274025,0.00003878168,0.0001593703,0.0002586127,0.0001174904,0.8545232,0.00759685,0.0004682764,0.0006666422,0.00837455],"study_design_scores_gemma":[0.00005233542,0.00003055261,0.05190356,0.000005050765,0.00001737333,0.00001263533,0.00008360697,0.9468575,0.0006701283,0.0001363806,0.000215497,0.0000153473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988613,0.00001366792,0.0004072364,0.00002677503,0.000001760835,0.00000543126,0.0003099965,0.00007356674,0.0003002575],"genre_scores_gemma":[0.9992309,0.000009469665,0.0003595948,0.000005759774,9.999331e-7,0.000004194719,0.0002796074,0.000005887474,0.0001037721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8359796,"threshold_uncertainty_score":0.3261313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1111075343907301,"score_gpt":0.2568085267228384,"score_spread":0.1457009923321083,"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."}}