{"id":"W4206158718","doi":"10.2514/6.2022-1669","title":"Aerodynamic state estimation from sparse sensor data by pairing Bayesian statistics with transition networks","year":2022,"lang":"en","type":"article","venue":"AIAA SCITECH 2022 Forum","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Aerodynamics; Computer science; Control theory (sociology); Noise (video); Angle of attack; Pairing; Flow (mathematics); State (computer science); Wake; Algorithm; Artificial intelligence; Engineering; Control (management); Aerospace engineering; Physics; Mechanics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001716853,0.0001962126,0.0001824056,0.00005531394,0.0005210876,0.00008552739,0.0003034811,0.00002443378,0.001286648],"category_scores_gemma":[0.000001444428,0.0001982426,0.00003371149,0.0002931284,0.00004537297,0.0003048782,0.0001783445,0.0004382177,0.000007606811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005232203,"about_ca_system_score_gemma":0.00003914017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005544849,"about_ca_topic_score_gemma":0.00006823969,"domain_scores_codex":[0.9984288,0.00010954,0.0002552304,0.000496064,0.0003262137,0.0003841323],"domain_scores_gemma":[0.9991353,0.00005670057,0.0001448666,0.0005339426,0.00002672019,0.0001025212],"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":[0.0001292841,0.0001258315,0.001010422,0.000004886689,0.0000934879,0.000009177055,0.0001402625,0.8673955,0.0005105062,0.0006016034,0.05128273,0.07869634],"study_design_scores_gemma":[0.0004840399,0.00009066491,0.00008897192,0.00001123527,0.00004138901,0.000003276718,0.0004809324,0.992515,0.00006638352,0.00211938,0.003851072,0.0002475992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05094874,0.00004998095,0.9430567,0.0008638206,0.0002752561,0.0002920147,0.00433572,0.00008525782,0.00009250815],"genre_scores_gemma":[0.9774429,0.000008975068,0.008515364,0.0002258064,0.00009142894,0.0000596046,0.01322893,0.00004339562,0.0003835889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9345413,"threshold_uncertainty_score":0.9996263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009711020802161647,"score_gpt":0.223332186849832,"score_spread":0.2136211660476704,"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."}}