{"id":"W2413319434","doi":"10.1016/j.ast.2016.06.006","title":"Full-altitude attitude angles envelope and model predictive control-based attitude angles protection for civil aircraft","year":2016,"lang":"en","type":"article","venue":"Aerospace Science and Technology","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"China Scholarship Council; Fudan University; Concordia University","keywords":"Envelope (radar); Altitude (triangle); Flight envelope; Attitude control; Function (biology); Process (computing); Control theory (sociology); Aerospace engineering; Control (management); Aircraft flight mechanics; Model predictive control; Dual (grammatical number); Engineering; Computer science; Aeronautics; Wing; Mathematics; Aerodynamics; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0002999052,0.0002051795,0.00025563,0.0003333657,0.00028261,0.00004877821,0.0002134787,0.000194505,0.000001311342],"category_scores_gemma":[0.0003171556,0.0001601677,0.00002110669,0.0005148215,0.00080342,0.0005408948,0.00005261435,0.0001005546,0.000002544224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001518109,"about_ca_system_score_gemma":0.00009499877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005267964,"about_ca_topic_score_gemma":0.0001815929,"domain_scores_codex":[0.9986732,0.00001026093,0.0001926759,0.0004755208,0.0002085731,0.0004397398],"domain_scores_gemma":[0.999221,0.00006181304,0.00007388311,0.0002661473,0.0002912872,0.00008581454],"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":[0.0001352572,0.00004355265,0.004461311,0.0001197855,0.00005976255,0.000002465631,0.0001272879,0.1842026,0.7862095,0.0062184,0.0001050795,0.01831498],"study_design_scores_gemma":[0.002857522,0.0004937933,0.0009969751,0.0001388965,0.00003488578,0.00001833978,0.00008175688,0.971992,0.01981597,0.002784781,0.0004109138,0.0003742148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06424214,0.0006013407,0.9306847,0.002531764,0.0001106671,0.001048475,0.00002977283,0.0006852809,0.00006581381],"genre_scores_gemma":[0.9840227,0.00009409246,0.01521277,0.00004226651,0.0000289195,0.0005281623,9.987116e-7,0.00002585846,0.00004424166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9197806,"threshold_uncertainty_score":0.6531451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007025656527167645,"score_gpt":0.2109490293623194,"score_spread":0.2039233728351517,"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."}}