{"id":"W2749417138","doi":"","title":"Improving the BADA 3 aerodynamic database for trajectory optimization","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Aerodynamics; Trajectory; Aviation; Set (abstract data type); Software; Stability (learning theory); Kinematics; Aerospace engineering; Trajectory optimization; Engineering; Computer science; Control engineering; Simulation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002101092,0.0002346266,0.0001582482,0.0001077147,0.0000940265,0.00007745723,0.0002138488,0.000148751,0.0001353595],"category_scores_gemma":[0.00004825992,0.0001867928,0.00006656154,0.0001376008,0.000007790743,0.0001959071,0.000009878398,0.000139,0.000008961477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008869318,"about_ca_system_score_gemma":0.00004110606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002115783,"about_ca_topic_score_gemma":0.000675119,"domain_scores_codex":[0.999162,0.00001222132,0.0002414604,0.0002095635,0.0001824042,0.0001923712],"domain_scores_gemma":[0.999456,0.00004883665,0.00007022041,0.0002745022,0.0001112625,0.00003919587],"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":[0.00001729725,0.00000661957,3.976131e-7,0.0003541669,0.00003946599,2.358941e-7,0.0001742562,0.9701757,0.00004659092,0.000161635,0.02100592,0.008017655],"study_design_scores_gemma":[0.0002996105,0.00001445723,0.000008026714,0.000028161,0.0001162887,1.644138e-7,0.0008090058,0.9965138,0.00004220207,0.00001116077,0.001918223,0.000238898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001530621,0.0005543832,0.9574839,0.00001849575,0.002476266,0.001556542,0.00006014573,0.0008294948,0.03549015],"genre_scores_gemma":[0.2025138,0.001946827,0.3473067,0.0003325772,0.002988761,0.002916414,0.2292835,0.00149455,0.2112168],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6101772,"threshold_uncertainty_score":0.7617189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009135185953326238,"score_gpt":0.2187856836994384,"score_spread":0.2096504977461122,"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."}}