{"id":"W4212877782","doi":"10.1080/07055900.2022.2038071","title":"Recherche en Prévision Numérique Contributions to Numerical Weather Prediction","year":2022,"lang":"fr","type":"article","venue":"ATMOSPHERE-OCEAN","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Numerical weather prediction; Data assimilation; Weather prediction; Meteorology; Computer science; North American Mesoscale Model; Numerical models; Range (aeronautics); Ensemble forecasting; Environmental science; Global Forecast System; Computer simulation; Geography; Aerospace engineering; Simulation; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00232508,0.0002954048,0.0003699344,0.00001493775,0.001046602,0.000100363,0.0004641509,0.0003393018,0.07184413],"category_scores_gemma":[0.0009537436,0.0002780455,0.0001848096,0.001098769,0.0000903652,0.0002555606,0.0001425975,0.001241843,0.001220149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002745091,"about_ca_system_score_gemma":0.0002209896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00149852,"about_ca_topic_score_gemma":0.0001017003,"domain_scores_codex":[0.994716,0.002824855,0.0005599823,0.000636266,0.000544349,0.0007185439],"domain_scores_gemma":[0.9970338,0.001741349,0.0001231925,0.0004172236,0.0001182604,0.0005661522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002911064,0.0004540342,0.1494398,0.00002044713,0.000116058,0.00005048247,0.003903893,0.6962499,0.00005134342,0.00608316,0.1039768,0.03936299],"study_design_scores_gemma":[0.0006280496,0.001771434,0.05423652,0.00001944506,0.00005083603,0.00003754823,0.00176098,0.1380323,0.00001391899,0.0162157,0.7868324,0.0004009205],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8390225,0.008135373,0.0323309,0.04731338,0.005390642,0.002080696,0.005303511,0.0004078334,0.0600152],"genre_scores_gemma":[0.9563959,0.0001303288,0.004755637,0.00212332,0.0006427669,0.00001167781,0.0004795689,0.00001873708,0.03544204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6828556,"threshold_uncertainty_score":0.9999672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04791514180643392,"score_gpt":0.2905841132203152,"score_spread":0.2426689714138813,"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."}}