{"id":"W3132004500","doi":"10.1029/2020ea001465","title":"On the Localization in Strongly Coupled Ensemble Data Assimilation Using a Two‐Scale Lorenz Model","year":2021,"lang":"en","type":"article","venue":"Earth and Space Science","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Data assimilation; Kalman filter; Ensemble Kalman filter; Covariance; Component (thermodynamics); Computer science; Algorithm; Extended Kalman filter; Mathematics; Artificial intelligence; Meteorology; Statistics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009250049,0.0004577222,0.0004083451,0.000332357,0.0004391033,0.0006258517,0.0004958792,0.0004712588,0.0004295039],"category_scores_gemma":[0.003461426,0.0003132179,0.0004793288,0.0003020315,0.00076705,0.001201768,0.001198942,0.0007346219,0.00007489377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005148994,"about_ca_system_score_gemma":0.000724389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01858681,"about_ca_topic_score_gemma":0.007546241,"domain_scores_codex":[0.9996766,0.0001546961,0.00001439706,0.00007133505,0.00005238686,0.00003049306],"domain_scores_gemma":[0.9994192,0.0002846803,0.0000797743,0.00005696332,0.0001264912,0.00003284871],"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":[0.00004765244,0.00001264356,0.00247897,0.00002636406,0.00004224052,0.00005509801,0.00008078064,0.9623123,0.002102151,0.02207796,0.0002437301,0.0105201],"study_design_scores_gemma":[0.000001852211,0.000003681523,0.0001254315,0.000001101433,0.000002618945,0.000001931,0.000003093184,0.9985575,0.0001286499,0.001116721,0.00005443547,0.000003011508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1485334,0.0002289292,0.8487632,0.0003388104,0.00003197513,0.00002009702,0.00003936397,0.0001330991,0.001911153],"genre_scores_gemma":[0.974245,0.0001902363,0.02451846,0.00004512806,0.00001846768,0.00003022465,0.00004299691,0.00001968641,0.0008898246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01858681,"threshold_uncertainty_score":0.03695726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0732997122427921,"score_gpt":0.2765030839853651,"score_spread":0.203203371742573,"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."}}