{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008263049,0.000887626,0.0006526803,0.0006637916,0.0004593578,0.00142656,0.0006262154,0.00105615,0.01220966],"category_scores_gemma":[0.001201057,0.0003921719,0.0008020637,0.0005126707,0.0006202739,0.0006366179,0.0008481814,0.0006560958,0.001344312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009440375,"about_ca_system_score_gemma":0.001197963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002135627,"about_ca_topic_score_gemma":0.002038706,"domain_scores_codex":[0.9996375,0.0001342071,0.00001100418,0.00003867509,0.0001419242,0.00003670221],"domain_scores_gemma":[0.999747,0.00008929663,0.00003347637,0.00002083897,0.0000966554,0.00001272418],"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":[0.00001713689,0.000009564895,0.00008577797,0.00009718194,0.000007386936,0.00004028961,0.00002456601,0.965291,0.002545339,0.02417998,0.0006109417,0.007090789],"study_design_scores_gemma":[0.00002513769,0.00007658285,0.0001837807,0.00003159787,0.00001523974,0.00003226007,0.00003398026,0.9741393,0.000993135,0.01350929,0.01094753,0.00001201099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02314209,0.0007460393,0.9048802,0.0004641437,0.0001519896,0.0002823206,0.0004009364,0.0002952496,0.06963701],"genre_scores_gemma":[0.7266006,0.00123349,0.2512012,0.0001748581,0.00007604135,0.001264618,0.0005652099,0.0002310539,0.01865282],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01220966,"threshold_uncertainty_score":0.04084533,"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."}}