{"id":"W4416788416","doi":"10.1016/j.ifacol.2025.11.570","title":"Brain-Inspired Decision Learning for Fault-Tolerant Flight Control under Active/Passive Wing Deformations","year":2025,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"China Scholarship Council","keywords":"Aerodynamics; Control reconfiguration; Control system; Controller (irrigation); Hierarchical control system; Control (management); Key (lock); Stability (learning theory); Parallels; Control theory (sociology)","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":[0.0004374568,0.0004608668,0.0003750796,0.000199058,0.0001976846,0.0003866787,0.0006010279,0.0004720582,0.0007605934],"category_scores_gemma":[0.0008658771,0.0001193341,0.0003174364,0.0001427114,0.0005822628,0.0003164113,0.0006237339,0.0006031455,0.00007851992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004502619,"about_ca_system_score_gemma":0.0005579718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002068768,"about_ca_topic_score_gemma":0.002028264,"domain_scores_codex":[0.9998294,0.00003313952,0.000007485315,0.00004260762,0.00005489721,0.00003237931],"domain_scores_gemma":[0.9997882,0.00009285002,0.00004393049,0.00001489622,0.00004332731,0.00001668966],"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":[0.00003486268,0.00003506936,0.0002866341,0.00004006151,0.00002530426,0.00005879071,0.00005410814,0.9472921,0.005654831,0.01341372,0.0002572561,0.03284726],"study_design_scores_gemma":[0.000004426127,0.00003469705,0.00005690899,0.000002165129,0.000003405443,0.000006816465,0.000003272192,0.9967193,0.0005820075,0.002435404,0.000149602,0.00000205253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03663351,0.0001908673,0.9596131,0.0001435434,0.00002879424,0.00002980856,0.00001374774,0.0001276607,0.003218885],"genre_scores_gemma":[0.9649658,0.00008194854,0.0337476,0.0000614588,0.00001839698,0.00004870613,0.00001333222,0.000009525631,0.001053243],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002068768,"threshold_uncertainty_score":0.004113436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008595142921064418,"score_gpt":0.2488070317289896,"score_spread":0.2402118888079252,"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."}}