{"id":"W2188171131","doi":"10.1017/s000192400000659x","title":"Aircraft conceptual design for optimal environmental performance","year":2012,"lang":"en","type":"article","venue":"The Aeronautical Journal","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; University of Toronto","funders":"","keywords":"Airframe; Airplane; Takeoff and landing; Takeoff; Cruise; Propulsion; Conceptual design; Aviation; Engineering; Multidisciplinary design optimization; Genetic algorithm; Propulsive efficiency; Automotive engineering; Aerospace engineering; Computer science; Aeronautics; Multidisciplinary approach; Mechanical engineering","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":[0.0006615894,0.0001712198,0.0001433186,0.00001594364,0.0005212431,0.00002804329,0.0004738589,0.00008581967,0.001426182],"category_scores_gemma":[0.00006535916,0.000106024,0.00008847633,0.00006569582,0.001078422,0.000470258,0.0001874779,0.0003865365,0.0005844596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001844688,"about_ca_system_score_gemma":0.000008793844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.548131e-7,"about_ca_topic_score_gemma":9.180509e-8,"domain_scores_codex":[0.9985401,0.00007349033,0.000229362,0.0001471853,0.0003202008,0.0006896725],"domain_scores_gemma":[0.999281,0.0002454915,0.00007747573,0.0002063219,0.000002826332,0.0001868667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001734408,0.001810814,0.09703349,0.00001746026,0.0002721879,0.00003605271,0.005152974,0.05151699,0.1307986,0.0139042,0.04858087,0.649142],"study_design_scores_gemma":[0.00841822,0.005774566,0.2784387,0.00008524631,0.0005178468,0.005872349,0.007580983,0.05982305,0.140359,0.02339127,0.4664864,0.003252345],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5918268,0.0003503264,0.4055987,0.00103363,0.000250369,0.0003587869,0.000004736076,0.00008163686,0.0004950479],"genre_scores_gemma":[0.9484935,0.00009800858,0.05042303,0.0003635372,0.0001937911,0.00002869821,0.000001216856,0.00001887461,0.0003793489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6458896,"threshold_uncertainty_score":0.9994866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03186858817412897,"score_gpt":0.2446891086798539,"score_spread":0.212820520505725,"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."}}