{"id":"W3093240376","doi":"10.1007/s00366-020-01190-w","title":"Scale-adaptive turbulence modeling for LES over complex terrain","year":2020,"lang":"en","type":"article","venue":"Engineering With Computers","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Terrain; Turbulence kinetic energy; Large eddy simulation; Planetary boundary layer; Turbulence modeling; K-epsilon turbulence model; Meteorology; Geology; K-omega turbulence model; Mechanics; Computer science; Physics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00003419309,0.000136144,0.0001324918,0.00001187628,0.00008523344,0.00001921002,0.0001436728,0.0000199229,0.00002532564],"category_scores_gemma":[0.000007193122,0.0001011665,0.00003806075,0.00009481053,0.00003696588,0.00008809657,0.0001023152,0.00007327175,0.00001115388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003962745,"about_ca_system_score_gemma":0.000002182075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003203538,"about_ca_topic_score_gemma":0.000004363682,"domain_scores_codex":[0.9993283,0.000004109821,0.00009227701,0.0002393084,0.000127536,0.0002085422],"domain_scores_gemma":[0.9997824,0.00004017502,0.00001771544,0.00007169112,0.000004168364,0.00008379034],"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":[0.00001532798,0.000007047111,0.0007224664,0.00001387284,0.00001534127,0.000002122006,0.001052021,0.9921324,0.0007495466,0.00001499529,0.001474698,0.003800138],"study_design_scores_gemma":[0.00027139,0.0001102394,0.003338654,0.00003643855,0.000006230716,0.000001410283,0.00005743598,0.9927568,0.00008488714,0.000006213778,0.003156205,0.000174105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1998639,0.00001382535,0.798969,0.0007000506,0.00007324713,0.0001456271,0.000005787178,0.0001170569,0.000111449],"genre_scores_gemma":[0.8991464,0.000001380215,0.1003893,0.0003136346,0.0001045193,0.00001280522,0.00000241703,0.00001652459,0.00001302003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6992825,"threshold_uncertainty_score":0.4125449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01890613592974718,"score_gpt":0.1919424375149565,"score_spread":0.1730363015852093,"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."}}