{"id":"W4407415239","doi":"10.2514/6.2025-1650","title":"Aerodynamic Optimization of Adaptive Wing Configurations With Different Leading-Edge Shapes – Application to the UAS-S45","year":2025,"lang":"en","type":"article","venue":"","topic":"Biomimetic flight and propulsion mechanisms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Aerodynamics; Wing; Aerospace engineering; Leading edge; Control theory (sociology); Enhanced Data Rates for GSM Evolution; Wing configuration; Computer science; Engineering; Physics; 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":[0.0003573879,0.0003346028,0.000257897,0.0002715357,0.0001726206,0.0003945352,0.0001914956,0.0003626577,0.0007129921],"category_scores_gemma":[0.0003854153,0.0001451759,0.0004584416,0.0001568932,0.0002615237,0.0001579904,0.0003692428,0.0002375238,0.00009521577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001618333,"about_ca_system_score_gemma":0.0002940639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008796696,"about_ca_topic_score_gemma":0.0009934391,"domain_scores_codex":[0.9999113,0.00002065741,0.000004807076,0.00001384774,0.0000323795,0.00001702595],"domain_scores_gemma":[0.9998646,0.00005849146,0.00002129061,0.00001783511,0.00002239543,0.00001532602],"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":[0.0001687561,0.0001261445,0.004216315,0.0001585736,0.00003396806,0.0002376402,0.0000830991,0.8937145,0.0597823,0.001555207,0.0003445015,0.03957898],"study_design_scores_gemma":[0.00002200055,0.0003991937,0.003060492,0.00001334804,0.00001245049,0.00009026773,0.0000573554,0.9825262,0.01205326,0.000424326,0.001326677,0.00001441303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208936,0.0002665191,0.07289615,0.00007934177,0.00002483837,0.00004877669,0.00008167227,0.0001643719,0.005544707],"genre_scores_gemma":[0.9713647,0.00007074177,0.02777888,0.00001744852,0.000002704312,0.00002600023,0.00006176459,0.00002291851,0.0006547778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008796696,"threshold_uncertainty_score":0.002385199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006973818594521163,"score_gpt":0.2073838452580865,"score_spread":0.2004100266635653,"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."}}