{"id":"W2064991316","doi":"10.2514/6.2004-4655","title":"Preliminary Design of Large Wind Turbine Blades Using Layout Optimization Techniques","year":2004,"lang":"en","type":"article","venue":"10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"École de technologie supérieure","keywords":"Turbine; Wind power; Computer science; Marine engineering; Turbine blade; Aerospace engineering; Engineering; Electrical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003002242,0.00037501,0.0005569893,0.0006538623,0.0002783553,0.0001224578,0.0002140522,0.0002270584,0.0002055831],"category_scores_gemma":[0.00004275684,0.0003667368,0.0001228105,0.001084616,0.00009936827,0.0006869073,0.0001190934,0.0001720565,9.132946e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007072208,"about_ca_system_score_gemma":0.00007104688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003583606,"about_ca_topic_score_gemma":0.000007011947,"domain_scores_codex":[0.9981885,0.00006776861,0.0006636024,0.00046248,0.0002767857,0.0003408534],"domain_scores_gemma":[0.99887,0.00005557955,0.000258051,0.0003421198,0.0003388853,0.0001353736],"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":[0.00006069941,0.0001070614,0.0005922365,0.0001406864,0.0002401748,0.000003640153,0.0008575841,0.9971357,0.000289606,0.000118173,0.000002564176,0.0004518527],"study_design_scores_gemma":[0.0005509971,0.0001351521,0.0007659541,0.0001283402,0.0006356087,0.000004824636,0.0002092129,0.986834,0.01023907,0.00008895376,0.000004582255,0.000403301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02012551,0.0003541368,0.9785485,0.00005233527,0.00005536043,0.0004116609,0.00004270577,0.0002738849,0.000135917],"genre_scores_gemma":[0.6234961,0.0006286706,0.375571,0.000008852769,0.00002791277,0.00001342238,0.0001897473,0.00003283377,0.00003142632],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6033705,"threshold_uncertainty_score":0.9998785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000814146635182,"score_gpt":0.2598698621738828,"score_spread":0.239861720707531,"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."}}