{"id":"W2317221425","doi":"10.2514/6.2001-4260","title":"In-flight technique for calibrating air data systems using Kalman filtering and smoothing","year":2001,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference and Exhibit","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Biological Sciences","funders":"","keywords":"Kalman filter; Smoothing; Computer science; Extended Kalman filter; Fast Kalman filter; Artificial intelligence; Computer vision","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":[0.0002690413,0.000274256,0.0003722806,0.00002431469,0.0001509398,0.0001057551,0.0002890985,0.0002649434,0.00001735447],"category_scores_gemma":[0.00003543291,0.0002815774,0.0000234065,0.0002718098,0.0000252916,0.0006907865,0.0002312052,0.000233179,0.000001998456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005073305,"about_ca_system_score_gemma":0.00003139188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001315973,"about_ca_topic_score_gemma":0.0000658335,"domain_scores_codex":[0.998596,0.00002141266,0.000382594,0.0004621789,0.0001111134,0.0004267436],"domain_scores_gemma":[0.9993262,0.00006282104,0.00008602915,0.000396643,0.00004364527,0.00008469857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005080923,0.00007180413,0.001783723,0.001381736,0.0001640097,0.0001626837,0.002007094,0.01213407,0.8527801,0.1157539,0.001108001,0.01260206],"study_design_scores_gemma":[0.0003995255,0.00005455931,0.00001822882,0.000290568,0.00002706624,0.0001022574,0.0007402271,0.974467,0.01491419,0.002322054,0.006235413,0.0004288576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1403113,0.001319912,0.8565272,0.0002511994,0.0002796635,0.0006718836,0.00001942624,0.0003277576,0.0002916929],"genre_scores_gemma":[0.9708942,0.0007881661,0.02788717,0.00008250925,0.00008557047,0.00009409153,0.00002010188,0.00005669904,0.00009148878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.962333,"threshold_uncertainty_score":0.9999636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03090925251884515,"score_gpt":0.2446900276994944,"score_spread":0.2137807751806492,"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."}}