{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01004899,0.001404257,0.001561773,0.001723332,0.0007788771,0.004219771,0.001625096,0.002409503,0.006079729],"category_scores_gemma":[0.01856976,0.0006265709,0.001422777,0.00333258,0.003074615,0.004430908,0.002700729,0.00830048,0.003327638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003316097,"about_ca_system_score_gemma":0.006787286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01366834,"about_ca_topic_score_gemma":0.006614525,"domain_scores_codex":[0.9935288,0.001902159,0.0004246583,0.000981758,0.002911288,0.0002513832],"domain_scores_gemma":[0.987754,0.006601468,0.0004353962,0.0009792137,0.003840677,0.0003892329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001060195,0.00007586852,0.001601695,0.005675896,0.0002242638,0.0001469247,0.0005764387,0.0232402,0.002442883,0.3517162,0.07400157,0.5401919],"study_design_scores_gemma":[0.00001950412,0.00006492694,0.00101733,0.001886791,0.00005424926,0.0002345295,0.0001117463,0.008093043,0.001931649,0.06662542,0.9198835,0.00007728249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.002182476,0.8339385,0.09301836,0.01707129,0.01186575,0.00004950911,0.0003302678,0.0003508441,0.04119299],"genre_scores_gemma":[0.04150113,0.8654092,0.0555495,0.002829059,0.01608176,0.00008642478,0.0005665273,0.0006483243,0.01732802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01366834,"threshold_uncertainty_score":0.05314475,"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."}}