{"id":"W2157390189","doi":"10.5194/acp-12-10015-2012","title":"Technical Note: Spectral representation of spatial correlations in variational assimilation with grid point models and application to the Belgian Assimilation System for Chemical Observations (BASCOE)","year":2012,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Belgian Federal Science Policy Office","keywords":"Grid; Data assimilation; Gaussian; Separable space; Fortran; Atmospheric sounding; Univariate; Computer science; Algorithm; Applied mathematics; Meteorology; Mathematics; Geometry; Mathematical analysis; Multivariate statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001922153,0.0001050268,0.0001443861,0.000001221003,0.0001487296,0.00002140058,0.00006308135,0.00007868433,0.00003479899],"category_scores_gemma":[0.00003992593,0.0000789745,0.00002708207,0.0002797159,0.00005664353,0.0002734761,0.000008849824,0.00009738059,0.00000107219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002010225,"about_ca_system_score_gemma":0.00002692015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002468793,"about_ca_topic_score_gemma":0.00007997051,"domain_scores_codex":[0.9991987,0.00002901246,0.0002591667,0.0001980018,0.0001636948,0.0001513773],"domain_scores_gemma":[0.9992383,0.000356884,0.0001185187,0.0001393445,0.00006553617,0.00008146772],"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":[0.0001598589,0.00008137512,0.181578,0.00006782832,0.00001292427,8.84588e-8,0.0006973619,0.7781563,0.004066346,0.003996609,0.00002862896,0.03115474],"study_design_scores_gemma":[0.0002149924,0.00002309675,0.3503565,0.000009323137,0.00002533354,0.000001960225,0.00005778622,0.6469035,0.0003155816,0.001991907,0.00002600572,0.00007393368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2964849,0.00002756457,0.7018359,0.0003249563,0.00003117947,0.0004379198,0.00007580227,0.00001877166,0.0007630067],"genre_scores_gemma":[0.945827,0.0000031651,0.0532617,0.00003598503,0.0002567293,0.00003505662,0.0005618938,0.000003792661,0.0000146884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6493421,"threshold_uncertainty_score":0.3220487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02131827741988265,"score_gpt":0.2331514336585956,"score_spread":0.211833156238713,"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."}}