{"id":"W2063091370","doi":"10.1175/2010waf2222401.1","title":"The Canadian Regional Data Assimilation and Forecasting System","year":2010,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Data assimilation; Meteorology; Computer science; Spherical harmonics; Environmental science; Errors-in-variables models; Variable (mathematics); Mathematics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0007960928,0.00007666129,0.00008206343,0.00003176203,0.001292228,0.0001778203,0.0001395709,0.00005766063,0.00007544365],"category_scores_gemma":[0.000196642,0.0000464385,0.00001112174,0.00006782051,0.0001007141,0.0001505149,0.00002010637,0.0001610936,0.000004902103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002598776,"about_ca_system_score_gemma":0.00003414579,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02594105,"about_ca_topic_score_gemma":0.5254676,"domain_scores_codex":[0.999267,0.00003736477,0.0001635102,0.0001997748,0.0001090134,0.0002233548],"domain_scores_gemma":[0.9990357,0.0005401614,0.00006179549,0.0001746164,0.0000258646,0.0001619082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001145446,0.000001212241,0.7143067,0.00001044625,0.00001094298,0.000003667636,0.0001655911,0.0004237371,0.00001989301,0.003824977,0.00008040812,0.281141],"study_design_scores_gemma":[0.00009032027,0.00001606137,0.449161,0.000007322135,0.000006439234,0.00003396254,0.0001190753,0.5436777,2.773703e-7,0.001118493,0.005695538,0.00007382197],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9379238,0.0003398071,0.0001146535,0.0004305934,0.0002289928,0.0001370123,0.00006875424,0.00002721061,0.0607292],"genre_scores_gemma":[0.998348,0.000004820974,0.001190422,0.00007861621,0.0001839366,6.462371e-7,0.00007786538,0.000002543451,0.0001131467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.543254,"threshold_uncertainty_score":0.9938903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1133382856328241,"score_gpt":0.2372557081907364,"score_spread":0.1239174225579123,"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."}}