{"id":"W2318376326","doi":"10.2514/6.2003-1493","title":"An Improved Neural Network Model for Nonlinear Aeroelastic Analysis","year":2003,"lang":"en","type":"article","venue":"44th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Texas A and M University","keywords":"Aeroelasticity; Artificial neural network; Nonlinear system; Computer science; Control theory (sociology); Aerodynamics; Artificial intelligence; Engineering; Aerospace engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002889174,0.001029857,0.001402028,0.0002212968,0.0007708886,0.0007783351,0.0006248726,0.0003460175,0.001037198],"category_scores_gemma":[0.00003221398,0.0008963204,0.000396214,0.0004152338,0.0003477804,0.0005678794,0.0001313608,0.0004668522,0.000003195008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007697548,"about_ca_system_score_gemma":0.0001849987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003593739,"about_ca_topic_score_gemma":0.0004016449,"domain_scores_codex":[0.9954316,0.000272162,0.001124257,0.001447405,0.0003596756,0.00136489],"domain_scores_gemma":[0.997381,0.0001085687,0.0006285978,0.0009020725,0.0003726755,0.0006071404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00151116,0.0001318628,0.004515454,0.0003657884,0.002583391,0.00001045011,0.0009455217,0.2811749,0.01835923,0.6345609,0.0006894583,0.05515184],"study_design_scores_gemma":[0.001446401,0.0001824576,0.003522763,0.00002106404,0.0007543942,0.00001808746,0.0001436345,0.9381018,0.001197977,0.05343239,0.000119047,0.001059976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8623198,0.0001042235,0.1316175,0.00009723663,0.002259681,0.00106433,0.002150704,0.0001705454,0.0002159494],"genre_scores_gemma":[0.9812499,0.00004156316,0.01429182,0.0002036279,0.001175166,0.00009914864,0.002314331,0.0001042433,0.0005201576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6569269,"threshold_uncertainty_score":0.999876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323120113496529,"score_gpt":0.256533690701503,"score_spread":0.2433024895665377,"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."}}