{"id":"W2883746298","doi":"","title":"Wind turbine aeroacoustic noise prediction using computational models and comparison to experimental measurements","year":2017,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Wind power; Turbine; Noise (video); Airfoil; Marine engineering; Acoustics; Predictive modelling; Engineering; Computational fluid dynamics; Environmental science; Aerospace engineering; Computer science; Physics; Electrical engineering; Machine learning","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":[0.0007259498,0.0007189517,0.000414888,0.0005969891,0.0004098213,0.0008740591,0.0009161881,0.0007371995,0.0008394647],"category_scores_gemma":[0.002452879,0.0003279587,0.000536929,0.000530323,0.0005222059,0.0008514898,0.0003642397,0.000658942,0.0002790752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008979192,"about_ca_system_score_gemma":0.000837522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0192013,"about_ca_topic_score_gemma":0.01391595,"domain_scores_codex":[0.9995565,0.0000786252,0.00003768954,0.00007373809,0.000221895,0.00003162575],"domain_scores_gemma":[0.9987888,0.0006494343,0.00009975767,0.0001202228,0.000316792,0.00002501641],"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":[0.0000520797,0.0001118132,0.003562197,0.00006194558,0.000009661967,0.00003655912,0.00003790965,0.9786902,0.004726842,0.0005122492,0.0002170611,0.0119816],"study_design_scores_gemma":[0.000006672505,0.00002461101,0.001060241,0.000004700683,0.000002351468,0.000005620398,0.00001133506,0.996329,0.002362084,0.00008373694,0.0001040979,0.0000055254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8500899,0.0003846341,0.1372745,0.0001598688,0.00006427459,0.0001391791,0.0006335939,0.001250811,0.01000328],"genre_scores_gemma":[0.9881765,0.0001434181,0.01073809,0.00001071422,0.000006466564,0.00007919604,0.0003379903,0.00003122415,0.0004762211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0192013,"threshold_uncertainty_score":0.0381791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05480924269057533,"score_gpt":0.2711678625592413,"score_spread":0.216358619868666,"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."}}