{"id":"W2028738100","doi":"10.1175/1520-0493(2003)131<2492:dvolmf>2.0.co;2","title":"Distribution-Oriented Verification of Limited-Area Model Forecasts in a Perfect-Model Framework","year":2003,"lang":"en","type":"article","venue":"Monthly Weather Review","topic":"Climate variability and models","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Nested set model; Range (aeronautics); Variable (mathematics); Unified Model; Forecast skill; Scale (ratio); Geopotential height; Function (biology); Boundary (topology); Geopotential; Boundary value problem; Computer science; Mathematics; Econometrics; Precipitation; Statistics; Meteorology; Geology; Data mining; Climatology; Mathematical analysis; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004140166,0.0004609285,0.0008407051,0.0004806748,0.0004272175,0.001032988,0.001550433,0.0006948751,0.001293635],"category_scores_gemma":[0.01853251,0.0003333423,0.0007587596,0.0002510656,0.001102256,0.001501952,0.001004721,0.0006569718,0.0001448871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008301871,"about_ca_system_score_gemma":0.001705362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01420944,"about_ca_topic_score_gemma":0.006223943,"domain_scores_codex":[0.9988422,0.0004964687,0.00008446074,0.0001893413,0.0002689156,0.0001187052],"domain_scores_gemma":[0.9902641,0.00631032,0.0009572636,0.001003755,0.001233259,0.0002313067],"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":[0.00006071265,0.00002254395,0.002998956,0.00002784568,0.00002053919,0.00009810256,0.00003377702,0.9855776,0.0006955203,0.008018548,0.0001301969,0.002315577],"study_design_scores_gemma":[0.000008754482,0.00001113855,0.0002563217,0.000002562207,0.000001878516,0.000008364426,0.000007465032,0.9973617,0.0002526875,0.002030289,0.00005602882,0.000002729599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5635961,0.0001444473,0.4292474,0.000390445,0.00006351975,0.00006262084,0.0004627884,0.0009149959,0.005117842],"genre_scores_gemma":[0.9773226,0.00002259346,0.02211294,0.00003001041,0.000009671137,0.00002904305,0.0001657948,0.00006265012,0.0002446999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01420944,"threshold_uncertainty_score":0.0282535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03098242160238031,"score_gpt":0.2626705343124136,"score_spread":0.2316881127100333,"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."}}