{"id":"W2314388938","doi":"10.1115/imece2014-37570","title":"Lateral Navigation Optimization Considering Winds and Temperatures for Fixed Altitude Cruise Using Dijsktra’s Algorithm","year":2014,"lang":"en","type":"article","venue":"","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Cruise; Trajectory; Climb; Descent (aeronautics); Computer science; Fuel efficiency; Trajectory optimization; Flight planning; Algorithm; Altitude (triangle); Aerospace engineering; Control theory (sociology); Simulation; Mathematics; Engineering; Artificial intelligence; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005890527,0.0009554912,0.001193933,0.0009855269,0.0005561459,0.00116989,0.00100128,0.001472408,0.004474984],"category_scores_gemma":[0.001540277,0.0005677644,0.001074276,0.0009272829,0.0005438176,0.0005417371,0.0008874024,0.0008154549,0.0005014841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001158561,"about_ca_system_score_gemma":0.001999306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04195,"about_ca_topic_score_gemma":0.02608216,"domain_scores_codex":[0.9997622,0.0000594198,0.00001357406,0.00004668648,0.00005885823,0.00005916033],"domain_scores_gemma":[0.9994842,0.0003132724,0.00004090542,0.00001719082,0.0001194333,0.00002504412],"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":[0.00001735599,0.00001452101,0.0003338787,0.00002289637,0.00001211593,0.00002262027,0.00001516638,0.9906757,0.0002039579,0.001697234,0.0003489019,0.006635717],"study_design_scores_gemma":[0.00000772646,0.00001574575,0.00008438843,0.000005049601,0.000004196351,0.000004830988,0.00000947672,0.9988335,0.0000803177,0.0006351196,0.0003165597,0.000003076438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06090548,0.0005836397,0.9140151,0.0004217828,0.000100801,0.0001748329,0.0003125193,0.0004398616,0.02304608],"genre_scores_gemma":[0.6769068,0.0003757095,0.3083895,0.0002228403,0.00003673692,0.0004667694,0.0007321162,0.0001856546,0.01268383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04195,"threshold_uncertainty_score":0.08341163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009527985106492215,"score_gpt":0.2158912517634855,"score_spread":0.2063632666569933,"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."}}