{"id":"W2744802077","doi":"10.1109/icuas.2017.7991324","title":"Optimal control for the trajectory planning of micro airships","year":2017,"lang":"en","type":"article","venue":"","topic":"Aerospace Engineering and Energy Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Underactuation; Trajectory; Control theory (sociology); Limiting; Optimal control; Computer science; Trajectory optimization; Control (management); Control engineering; Mathematical optimization; Engineering; Mathematics; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001472624,0.00008532671,0.000131629,0.0000148834,0.0001189317,0.00002996009,0.000217555,0.00004844613,0.000005983001],"category_scores_gemma":[0.00003127539,0.00005927928,0.00006501454,0.000009767112,0.00002840404,0.00005054101,0.000007329686,0.00006275714,0.000002419055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001080917,"about_ca_system_score_gemma":0.000004554492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002920434,"about_ca_topic_score_gemma":0.000006433073,"domain_scores_codex":[0.9996238,0.000003355595,0.0001080279,0.00006125828,0.0000503474,0.0001532574],"domain_scores_gemma":[0.9995123,0.0001223431,0.00002779544,0.0002947341,0.00001556315,0.00002730815],"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":[0.000007327769,0.000002097133,0.0005135262,0.00004831646,0.00007113708,4.610026e-7,0.0001617008,0.9869969,0.009424487,0.0003016337,0.002233524,0.0002388427],"study_design_scores_gemma":[0.001308789,0.00005160132,0.01350453,0.00008942573,0.00004890477,0.000006646876,0.0004569965,0.9346979,0.02785078,0.000006357243,0.02169941,0.0002786892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2553805,0.001350329,0.7362849,0.0001263181,0.001309788,0.0002126803,0.00001545431,0.000289289,0.005030788],"genre_scores_gemma":[0.997299,0.000005148294,0.001646493,0.000005470817,0.0001787184,0.00003124698,7.412427e-7,0.00002372683,0.0008094803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7419185,"threshold_uncertainty_score":0.2417339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01911235986986058,"score_gpt":0.2228941823632616,"score_spread":0.203781822493401,"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."}}