{"id":"W2090270260","doi":"10.1175/2007waf2006046.1","title":"Comparative Analysis of the Local Observation-Based (LOB) Method and the Nonparametric Regression-Based Method for Gridded Bias Correction in Mesoscale Weather Forecasting","year":2007,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"U.S. Geological Survey","keywords":"Mesoscale meteorology; MM5; Nonparametric statistics; Meteorology; Regression; Model output statistics; Computer science; Regression analysis; Weather forecasting; Statistics; Climatology; Mathematics; Geography; Machine learning; Geology","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":[0.004221294,0.0001725026,0.0005040357,0.0002993644,0.0003697063,0.00003920254,0.000131209,0.00009250974,0.00008970548],"category_scores_gemma":[0.0009044114,0.00008649425,0.0001737658,0.001838969,0.0002071871,0.00007127385,0.00001332959,0.0001745373,2.810738e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001016902,"about_ca_system_score_gemma":0.00003052461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001321301,"about_ca_topic_score_gemma":0.003297938,"domain_scores_codex":[0.998176,0.000505785,0.0005249372,0.0003018717,0.000221102,0.0002702436],"domain_scores_gemma":[0.9848198,0.0145172,0.0003382413,0.000160724,0.00009851413,0.00006553523],"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":[0.0003845854,0.00001889133,0.4765621,0.00001367376,0.00007697648,3.581882e-7,0.0007395835,0.4386536,0.00002500673,0.000123132,0.000005876608,0.08339618],"study_design_scores_gemma":[0.0008609577,0.00006174683,0.290381,0.00002451455,0.0001790428,8.145666e-7,0.0004103467,0.7069147,0.0001311943,0.000913295,0.00003952813,0.00008282251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4545949,0.0002366266,0.5433158,0.0001053676,0.0001041988,0.0004364916,0.00002653969,0.00001088352,0.001169137],"genre_scores_gemma":[0.9519476,0.000001303836,0.04767155,0.0002386703,0.00003216713,0.000008601664,0.00002976644,0.000003977119,0.00006639786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4973527,"threshold_uncertainty_score":0.3527133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059797548002944,"score_gpt":0.3128596125025068,"score_spread":0.2068798577022123,"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."}}