{"id":"W2409260270","doi":"10.2514/6.2016-4208","title":"Aircraft Vertical Reference Trajectory Optimization With a RTA Constraint Using the ABC Algorithm","year":2016,"lang":"en","type":"article","venue":"16th AIAA Aviation Technology, Integration, and Operations Conference","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Trajectory; Constraint (computer-aided design); Computer science; Trajectory optimization; Algorithm; Mathematical optimization; Control theory (sociology); Engineering; Mathematics; Artificial intelligence; Physics; Control (management)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001732671,0.0002312245,0.0001709964,0.000262968,0.0004052269,0.0001570651,0.0001906831,0.0002002959,0.0001879697],"category_scores_gemma":[0.00007782107,0.0001399907,0.00002154618,0.000473065,0.0004072791,0.0005346432,0.00002504241,0.0001934594,0.000009563712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009195448,"about_ca_system_score_gemma":0.0000985693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001942082,"about_ca_topic_score_gemma":0.0003654597,"domain_scores_codex":[0.9988975,0.00005276679,0.0003480972,0.0003022121,0.0001745202,0.0002249081],"domain_scores_gemma":[0.9991606,0.00005189042,0.00003769038,0.0002974473,0.0003983505,0.00005395876],"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":[0.00001892127,0.00008094615,0.0008959791,0.00002823331,0.0001280227,0.00000287496,0.0008403994,0.4791353,0.005041492,0.3513877,0.0003719742,0.1620681],"study_design_scores_gemma":[0.0005152377,0.00008547449,0.000340531,0.00009342927,0.00005750287,0.0000145141,0.0008048415,0.9945045,0.002477069,0.0003712501,0.0004725965,0.000263017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01253054,0.00008059825,0.9836764,0.001737183,0.0001047553,0.0004645032,0.00002097843,0.0005359704,0.0008490806],"genre_scores_gemma":[0.9059206,0.0003776341,0.09322705,0.00006241587,0.00003744255,0.0001042739,0.00006815931,0.00002187848,0.0001805829],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.89339,"threshold_uncertainty_score":0.5708657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337060905063265,"score_gpt":0.2161553923937735,"score_spread":0.2027847833431409,"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."}}