{"id":"W4416093178","doi":"10.61841/j9qbh297","title":"“Smart” Aircraft: Control in Critical Situations Created by Humans in Flight","year":2025,"lang":"","type":"article","venue":"Journal of Advance Research in Mechanical & Civil Engineering (ISSN 2208-2379)","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Civil Aviation Organization","funders":"","keywords":"Control (management); Artificial neural network; Control system; Automatic control; Air traffic control; Human intelligence; Block (permutation group theory); Situation awareness","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002618808,0.0004080116,0.0001828208,0.0002071607,0.0002713548,0.001003118,0.0003105534,0.0008622918,0.001436939],"category_scores_gemma":[0.0005933204,0.00009273338,0.00013155,0.000130442,0.001144422,0.0009618084,0.0005167045,0.0003290511,0.0002135012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002112697,"about_ca_system_score_gemma":0.0004806838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009913482,"about_ca_topic_score_gemma":0.0009696822,"domain_scores_codex":[0.9998068,0.00004533344,0.00001166916,0.00004787874,0.00006234906,0.00002597572],"domain_scores_gemma":[0.9997873,0.00008273111,0.00004348362,0.00002424032,0.00003977311,0.00002240481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000561299,0.0002645292,0.007346044,0.001450531,0.0001086701,0.001430913,0.002405273,0.11066,0.2356422,0.1672748,0.005785532,0.4670702],"study_design_scores_gemma":[0.0001079589,0.002026324,0.01942838,0.0005830012,0.0001714496,0.002328348,0.002050267,0.6727152,0.05404516,0.1338729,0.1125252,0.000145892],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1980532,0.005651998,0.7271492,0.001859452,0.0005269053,0.0002513215,0.0000680732,0.0008216118,0.06561831],"genre_scores_gemma":[0.9363193,0.002283653,0.05550189,0.0003512853,0.0003001812,0.0000745111,0.00004294457,0.00002830189,0.00509793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001436939,"threshold_uncertainty_score":0.004807055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949752033619076,"score_gpt":0.3528341843926404,"score_spread":0.3333366640564496,"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."}}