{"id":"W2092409312","doi":"10.1029/2007jd009232","title":"Enhancing the estimation of continental‐scale snow water equivalent by assimilating MODIS snow cover with the ensemble Kalman filter","year":2008,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ensemble Kalman filter; Data assimilation; Environmental science; Moderate-resolution imaging spectroradiometer; Snow; Climatology; Forcing (mathematics); Meteorology; Kalman filter; Remote sensing; Satellite; Geology; Extended Kalman filter; Geography; Statistics; Mathematics","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":[0.0005482793,0.0003898476,0.0002464849,0.0003378972,0.00017291,0.0002898924,0.0002509125,0.0002657026,0.0002990356],"category_scores_gemma":[0.001633258,0.0002112536,0.0004127002,0.0002975693,0.0001179372,0.0007993917,0.0004026963,0.0002981423,0.0001273834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002130949,"about_ca_system_score_gemma":0.0006839272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03744329,"about_ca_topic_score_gemma":0.03847618,"domain_scores_codex":[0.9998672,0.00002799719,0.000009505608,0.00003645749,0.00004114096,0.00001766225],"domain_scores_gemma":[0.9996692,0.0001271142,0.00003748387,0.00003631225,0.0001210411,0.00000878341],"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":[0.0001064237,0.0000965134,0.03333161,0.00006234049,0.0002261183,0.00007080911,0.0002030152,0.684463,0.0263462,0.001555255,0.0009436547,0.2525952],"study_design_scores_gemma":[0.000007085241,0.00001458004,0.007044409,0.000003505201,0.00001921395,0.000008552514,0.00001385338,0.9903533,0.001865866,0.0002881066,0.0003728666,0.000008690246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3535422,0.0002731353,0.6438938,0.00009049011,0.0000416013,0.00002291591,0.0001636469,0.00061358,0.001358463],"genre_scores_gemma":[0.8618857,0.0002262713,0.1365823,0.00003100046,0.00002462436,0.00002799248,0.0003845932,0.00003856076,0.0007989323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03744329,"threshold_uncertainty_score":0.07445067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03649009204964341,"score_gpt":0.2783228409763189,"score_spread":0.2418327489266755,"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."}}