{"id":"W1984115821","doi":"10.1175/mwr-d-14-00104.1","title":"The Impacts of Representing the Correlation of Errors in Radar Data Assimilation. Part I: Experiments with Simulated Background and Observation Estimates","year":2014,"lang":"en","type":"article","venue":"Monthly Weather Review","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Data assimilation; Covariance; Radar; Statistics; Mathematics; Spatial correlation; Correlation; Covariance function; Observational error; Econometrics; Algorithm; Computer science; Meteorology; 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":[0.001189727,0.00008380377,0.0002009887,0.00001587738,0.0001197153,0.0000205565,0.0001992121,0.00002568381,0.0001008027],"category_scores_gemma":[0.000379668,0.00003846675,0.00001760331,0.0002122075,0.00009097228,0.0002152683,0.00002198179,0.00006337095,0.000002158566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002037422,"about_ca_system_score_gemma":0.0000113144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004238264,"about_ca_topic_score_gemma":0.0004172004,"domain_scores_codex":[0.9989417,0.0002236875,0.0003805972,0.0001621869,0.0001800813,0.0001117936],"domain_scores_gemma":[0.9983529,0.0008864143,0.000271855,0.0004216951,0.00003892878,0.00002819448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003437771,0.00001763279,0.934557,0.0001352153,0.00002471274,2.573252e-7,0.0001820714,0.04846612,0.00001988995,0.000136519,0.00009972551,0.01632646],"study_design_scores_gemma":[0.0001805226,0.00006213326,0.6628684,0.000386354,0.00003622609,2.803301e-7,0.0000497498,0.332623,0.000007352387,0.0004985816,0.003232249,0.0000551286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9432023,0.05353857,0.0002257773,0.0006616477,0.00004802103,0.0006355161,0.00002708199,0.00001035147,0.001650691],"genre_scores_gemma":[0.9974004,0.001706536,0.0006077933,0.00009735571,0.00001062534,0.000001276882,0.0001534202,0.000002601108,0.00001998972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2841569,"threshold_uncertainty_score":0.1568629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1024598267298986,"score_gpt":0.3068450469639762,"score_spread":0.2043852202340777,"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."}}