{"id":"W1971432865","doi":"10.2514/6.2007-4305","title":"Investigations of Nonlinear Aeroelasticity Using A Reduced Order Fluid Model Based on POD method","year":2007,"lang":"en","type":"article","venue":"18th AIAA Computational Fluid Dynamics Conference","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Aeroelasticity; Point of delivery; Nonlinear system; Computer science; Model order reduction; Aerodynamics; Applied mathematics; Control theory (sociology); Mathematics; Engineering; Algorithm; Physics; Aerospace engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002568205,0.0002434754,0.0002834277,0.0001896876,0.0001858986,0.00004633639,0.000195055,0.00007591704,0.0001262386],"category_scores_gemma":[0.00004011998,0.0002537546,0.000110941,0.0004481374,0.0001254288,0.0001295052,0.00004715353,0.0002612115,0.000006791018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007596713,"about_ca_system_score_gemma":0.0005999728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008608276,"about_ca_topic_score_gemma":0.000008713699,"domain_scores_codex":[0.9983052,0.000080873,0.0005294436,0.000382073,0.0004029632,0.0002994636],"domain_scores_gemma":[0.9983135,0.0003470807,0.0002042218,0.0002150148,0.0007320645,0.0001880435],"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":[0.00004985041,0.000144386,0.0002585223,0.000008405071,0.00002400452,6.202494e-7,0.00005146082,0.8454381,0.002739326,0.1478268,0.00002505453,0.003433402],"study_design_scores_gemma":[0.0004993087,0.00004975428,0.000314529,0.00005434426,0.00003167005,0.000002103073,0.00004022606,0.9798559,0.001025726,0.01789524,0.000006735852,0.0002244371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2098093,0.000002201343,0.78771,0.0002200353,0.0001316367,0.0001807927,0.0001369446,0.00003206667,0.001776992],"genre_scores_gemma":[0.6555343,2.476644e-7,0.3438697,0.0001320767,0.00008026494,0.00000459366,0.0003034293,0.00001682638,0.000058676],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4457249,"threshold_uncertainty_score":0.9999915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03614947639072719,"score_gpt":0.3102812044814313,"score_spread":0.2741317280907041,"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."}}