{"id":"W4405930877","doi":"10.1016/j.compfluid.2024.106537","title":"Characterization of atmospheric and wind farm turbulence","year":2024,"lang":"en","type":"article","venue":"Computers & Fluids","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Turbulence; Environmental science; Meteorology; Atmospheric turbulence; Characterization (materials science); Atmospheric sciences; Mathematics; Geology; Physics; Optics","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":[0.00004447288,0.00007340352,0.00008565551,0.000004541454,0.00004417904,0.00002631868,0.00007632378,0.00002065351,0.00008985096],"category_scores_gemma":[0.000002101417,0.0000616785,0.00002241636,0.0001481231,0.0001212926,0.00009610446,0.0001480106,0.00003759789,0.0000488782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001816209,"about_ca_system_score_gemma":0.000002900246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001345478,"about_ca_topic_score_gemma":8.380846e-7,"domain_scores_codex":[0.999523,0.000009745953,0.0000954309,0.0001774136,0.00009571479,0.00009871951],"domain_scores_gemma":[0.9998623,0.0000174393,0.00001167452,0.00007590019,0.000002572135,0.00003011332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000007492466,0.00004903047,0.0264841,0.0001100761,0.00003881359,0.00002147381,0.002955802,0.0002440366,0.5654052,0.0003907979,0.002204335,0.4020889],"study_design_scores_gemma":[0.0003162413,0.000274438,0.7450103,0.0003156515,0.00004117588,0.00002626625,0.000079053,0.147876,0.01382405,0.0003656977,0.09140458,0.0004665875],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900662,0.000314649,0.008137647,0.0002104347,0.0003418401,0.00005870115,0.000003236544,0.00004385076,0.0008234094],"genre_scores_gemma":[0.9978763,0.0001192982,0.001469174,0.0001253462,0.00006231371,0.000001287177,0.00000331255,0.000006411926,0.000336529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7185262,"threshold_uncertainty_score":0.2515176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005539018425663779,"score_gpt":0.1946181266768405,"score_spread":0.1890791082511767,"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."}}