{"id":"W2320578178","doi":"10.2514/6.2009-1547","title":"Design of Wind Turbine Profiles via a Preconditioned Adjoint-based Aerodynamic Shape Optimization","year":2009,"lang":"en","type":"article","venue":"47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Aerodynamics; Turbine; Aerospace engineering; Computer science; Marine engineering; Environmental science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007728553,0.0003907143,0.0003620064,0.0002295422,0.0009571977,0.0002388508,0.0003816769,0.000141483,0.00001903793],"category_scores_gemma":[0.00009177442,0.0003333199,0.0001042481,0.0009440014,0.0002754752,0.0005221687,0.00006516735,0.0002468393,0.000003502199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001462188,"about_ca_system_score_gemma":0.0001394254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004255779,"about_ca_topic_score_gemma":0.00003653776,"domain_scores_codex":[0.997782,0.0001066497,0.0005020315,0.0004954229,0.0005380744,0.0005758254],"domain_scores_gemma":[0.9988602,0.0003255657,0.0002643784,0.0002596538,0.0001306347,0.0001595729],"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":[0.00003800841,0.00003724667,0.0002180014,0.00002460189,0.00001756637,8.40487e-7,0.0001974835,0.9172789,0.07897386,0.001148029,0.0003151073,0.001750342],"study_design_scores_gemma":[0.0006082209,0.0008034788,0.0008694182,0.0003003938,0.0000476764,0.00001587848,0.0003054453,0.990373,0.00497753,0.001310419,0.000008260857,0.0003803028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4241072,0.0004107942,0.5707234,0.003185091,0.00035944,0.0006606111,0.00002179792,0.0002893672,0.0002423031],"genre_scores_gemma":[0.9206535,0.00008757119,0.07887523,0.0001183369,0.0001052725,0.00001473463,0.00007053223,0.00003537652,0.00003940705],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4965464,"threshold_uncertainty_score":0.9999119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210616025038571,"score_gpt":0.2295091531947733,"score_spread":0.2174029929443876,"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."}}