{"id":"W2944838639","doi":"10.1088/1742-6596/1222/1/012005","title":"Enhanced modelling of the stratified atmospheric boundary layer over steep terrain for wind resource assessment","year":2019,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Terrain; Mesoscale meteorology; Meteorology; Orographic lift; Numerical weather prediction; Geology; Downscaling; Discretization; Environmental science; Wind speed; Wind profile power law; Climatology; 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":[0.0002539726,0.00009897058,0.0002466619,0.000006516328,0.0001111936,0.00006673187,0.0002376317,0.00004056172,0.0006295602],"category_scores_gemma":[0.00001422567,0.00005900124,0.0001227909,0.0001030533,0.00009197478,0.0003568498,0.00001123708,0.0001653966,0.000002220109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000511177,"about_ca_system_score_gemma":0.0001867896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002035317,"about_ca_topic_score_gemma":0.00002795665,"domain_scores_codex":[0.9990571,0.00007866137,0.0003430954,0.0001005951,0.0002750957,0.0001454854],"domain_scores_gemma":[0.9990546,0.0001962114,0.0004019423,0.0001476584,0.0001525888,0.00004707055],"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":[0.0002543215,0.0000498868,0.01686771,0.00005303132,0.0000823899,4.763594e-7,0.001395559,0.9396237,0.009703974,0.01005621,0.00004403211,0.02186874],"study_design_scores_gemma":[0.00223585,0.002971568,0.23277,0.0002183854,0.0001516639,0.000005870224,0.004037939,0.4696096,0.01967075,0.262904,0.004847324,0.0005770705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9308196,0.00004200776,0.06366864,0.0001373377,0.0001961299,0.0001811114,0.0000292244,0.000003081037,0.004922919],"genre_scores_gemma":[0.9955366,0.000007519636,0.003906585,0.00007724604,0.00009940253,3.191652e-7,0.000006714354,0.000002650828,0.0003630164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4700141,"threshold_uncertainty_score":0.6893243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04074181607041424,"score_gpt":0.2536874308581082,"score_spread":0.2129456147876939,"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."}}