{"id":"W2319897051","doi":"10.2514/6.2015-1132","title":"High-Fidelity Aerostructural Optimization with Integrated Geometry Parameterization and Mesh Movement","year":2015,"lang":"en","type":"article","venue":"56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Movement (music); Computer science; Geometry; Fidelity; Computer graphics (images); Mathematics; Physics; Acoustics; Telecommunications","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":[0.0002681602,0.0008073737,0.0008830967,0.0002555063,0.0002342165,0.000825984,0.0003388826,0.0003103523,0.0001404563],"category_scores_gemma":[0.00009932458,0.0006652061,0.00005516422,0.0003318699,0.0003135627,0.0005747398,0.0001979469,0.0003195403,0.000001880452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003039023,"about_ca_system_score_gemma":0.0001275087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007401733,"about_ca_topic_score_gemma":0.0005920709,"domain_scores_codex":[0.9968792,0.0001357554,0.000968195,0.0008168842,0.0005734129,0.0006265749],"domain_scores_gemma":[0.998208,0.00006995992,0.0002947961,0.0004616516,0.000562822,0.0004027238],"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":[0.0008582718,0.00002389701,0.003126713,0.0007643425,0.000584592,0.00004494958,0.0009493597,0.6499351,0.01689328,0.2937799,0.0001473643,0.03289228],"study_design_scores_gemma":[0.001639564,0.0002176162,0.07250112,0.00008121163,0.00009701183,0.0001062256,0.0001873295,0.895867,0.001042521,0.0272612,0.00001496769,0.0009842345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9113826,0.0001349496,0.08451037,0.00008692702,0.001559773,0.0006159196,0.001362866,0.0002980404,0.00004851543],"genre_scores_gemma":[0.9609967,0.0002048029,0.03470966,0.0001294781,0.0001540692,0.00002443424,0.003646569,0.00008994285,0.00004431081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2665187,"threshold_uncertainty_score":0.9995799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008277172818354394,"score_gpt":0.1968443788172424,"score_spread":0.188567205998888,"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."}}