{"id":"W2331649965","doi":"10.2514/6.2016-0088","title":"Formulation of Torque-Optimal Guidance Trajectories for a CubeSat with Degraded Reaction Wheels","year":2016,"lang":"en","type":"article","venue":"AIAA Guidance, Navigation, and Control Conference","topic":"Spacecraft Dynamics and Control","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Aeronautics and Space Administration","keywords":"CubeSat; Torque; Computer science; Control theory (sociology); Automotive engineering; Aeronautics; Aerospace engineering; Engineering; Physics; Artificial intelligence; 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":[0.0001862035,0.0002203091,0.0003344682,0.00006904319,0.00009295716,0.0000450938,0.0001107384,0.0001089364,0.00000451321],"category_scores_gemma":[0.00003990606,0.0001616457,0.00005829427,0.0001348856,0.00009324462,0.0004111482,0.000005714845,0.00006158138,0.000001093996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005933064,"about_ca_system_score_gemma":0.00006710011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003455882,"about_ca_topic_score_gemma":0.00008946613,"domain_scores_codex":[0.9989187,0.00002385733,0.0003860005,0.000251128,0.0001610805,0.0002592219],"domain_scores_gemma":[0.998938,0.0001837087,0.0001393216,0.0002215741,0.0004562497,0.00006112967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006704582,0.00003706051,0.02790016,0.0002256224,0.000257751,0.000001261,0.000446373,0.0006472126,0.8699682,0.06224425,0.0001580116,0.03744369],"study_design_scores_gemma":[0.02567324,0.001254233,0.255187,0.002171189,0.000481604,0.00002927823,0.0004832251,0.6232032,0.05608898,0.02076064,0.01309331,0.001574081],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4621462,0.0004817931,0.5361371,0.0002186693,0.0001383833,0.0004732593,0.0000566876,0.00009922114,0.0002486507],"genre_scores_gemma":[0.9980583,0.00009174321,0.001273573,0.00003282716,0.0000865882,0.0002647601,0.00001485428,0.0000291185,0.0001482075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8138792,"threshold_uncertainty_score":0.6591722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007099228203784472,"score_gpt":0.2043370638228224,"score_spread":0.1972378356190379,"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."}}