{"id":"W3120345475","doi":"10.2514/6.2021-1234","title":"Aircraft Wing Design Through Concurrent Thickness and Material Optimization","year":2021,"lang":"en","type":"article","venue":"AIAA Scitech 2021 Forum","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Wing; Computer science; Selection (genetic algorithm); Relevance (law); Shell (structure); Focus (optics); Work (physics); Concurrent engineering; Optimization problem; Global optimization; Mechanical engineering; Structural engineering; Mathematical optimization; Engineering; Algorithm; Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005281277,0.0009419444,0.0005133178,0.000718474,0.0004010723,0.0008218545,0.0007784494,0.0006059778,0.002912242],"category_scores_gemma":[0.0009071123,0.0005517961,0.0007033069,0.0003417014,0.000564101,0.000804427,0.001258445,0.0006258406,0.0005743538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004251587,"about_ca_system_score_gemma":0.0008229076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001374964,"about_ca_topic_score_gemma":0.002613574,"domain_scores_codex":[0.999788,0.00004591378,0.000006552727,0.00003042296,0.00009783942,0.00003131634],"domain_scores_gemma":[0.9997211,0.00009747053,0.00005782333,0.00004123518,0.00006008021,0.00002228727],"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":[0.00006361234,0.00004756295,0.000799423,0.00005810487,0.00002825547,0.00006797949,0.00002903049,0.9488913,0.01690462,0.004653034,0.0006232997,0.02783387],"study_design_scores_gemma":[0.00001304299,0.00006891361,0.0001576842,0.000006993976,0.000009005235,0.00003348753,0.00001458165,0.9941474,0.00259368,0.001747116,0.001202961,0.000005124148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09424068,0.0002412543,0.884086,0.0001617696,0.00005847263,0.0001353284,0.00009965291,0.0006001618,0.02037665],"genre_scores_gemma":[0.6255021,0.0001648399,0.3680241,0.00008035052,0.00002640137,0.0001627788,0.0001514595,0.0003325458,0.005555545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002912242,"threshold_uncertainty_score":0.009742439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089224253113747,"score_gpt":0.2204855526898193,"score_spread":0.2095933101586819,"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."}}