{"id":"W2789462704","doi":"10.1175/mwr-d-17-0369.1","title":"Scale-Dependent Background Error Covariance Localization: Evaluation in a Global Deterministic Weather Forecasting System","year":2018,"lang":"en","type":"article","venue":"Monthly Weather Review","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Data assimilation; Extratropical cyclone; Covariance; Northern Hemisphere; Environmental science; Scale (ratio); Meteorology; Hotspot (geology); Southern Hemisphere; Computer science; Climatology; Mathematics; Statistics; Geology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001468586,0.0001902797,0.0003724443,0.00003266542,0.0001793497,0.00005849374,0.0002244839,0.00007646049,0.004054792],"category_scores_gemma":[0.0001243723,0.0001289346,0.00007142039,0.0004566321,0.00008486151,0.0001654233,0.00001572607,0.00007841879,0.0006684019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006206024,"about_ca_system_score_gemma":0.0000604384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003203183,"about_ca_topic_score_gemma":0.003242084,"domain_scores_codex":[0.9978495,0.0004579037,0.0005429076,0.0003971737,0.00043959,0.0003129396],"domain_scores_gemma":[0.9991841,0.0001016252,0.0001683011,0.0003045006,0.0001295704,0.0001119419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001176391,0.0001258578,0.4030581,0.002039422,0.00006079004,0.0000638096,0.000427937,0.04808776,0.000002465212,0.0006069889,0.0004893387,0.5449198],"study_design_scores_gemma":[0.0006387947,0.0002615351,0.07778551,0.002299219,0.0001546343,0.0000248664,0.0001130807,0.9042268,7.560344e-7,0.001437485,0.01271678,0.0003405718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3791457,0.2140335,0.02933033,0.001190153,0.00235913,0.008293728,0.0004919057,0.0004277944,0.3647278],"genre_scores_gemma":[0.9978893,0.0001684876,0.0008316203,0.0006958231,0.0001690613,0.00002536779,0.00006474771,0.000005936588,0.00014962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.856139,"threshold_uncertainty_score":0.9968556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08808901427037381,"score_gpt":0.3033745406268398,"score_spread":0.215285526356466,"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."}}