{"id":"W2172473432","doi":"10.1007/s10569-015-9640-5","title":"Long-term dynamic modeling of tethered spacecraft using nodal position finite element method and symplectic integration","year":2015,"lang":"en","type":"article","venue":"Celestial Mechanics and Dynamical Astronomy","topic":"Space Satellite Systems and Control","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Numerical integration; Symplectic geometry; Finite element method; Discretization; Spacecraft; Integrator; Numerical stability; Numerical analysis; Mathematics; Applied mathematics; Control theory (sociology); Runge–Kutta methods; Computer science; Mathematical analysis; Engineering; Aerospace engineering; Structural engineering","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":[0.0002175982,0.0001905239,0.0002881892,0.00007453864,0.00004074866,0.00004928487,0.00005297115,0.00009961556,0.000003935349],"category_scores_gemma":[0.00001274189,0.0001839521,0.00004464985,0.00007870082,0.00001043775,0.0001092103,0.00003708048,0.0001391423,7.563917e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001239982,"about_ca_system_score_gemma":0.00003215793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000728898,"about_ca_topic_score_gemma":0.0001038412,"domain_scores_codex":[0.9990994,0.00004954711,0.0002925563,0.0002112861,0.0001246442,0.0002225488],"domain_scores_gemma":[0.9995687,0.00003467958,0.00006043398,0.0001166683,0.00007182785,0.0001476991],"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":[0.0001043101,0.00005268237,0.0009756399,0.0001682902,0.0001376381,0.000005531708,0.0003612635,0.8684046,0.04229167,0.004751329,4.897905e-7,0.08274652],"study_design_scores_gemma":[0.0006584456,0.0001295476,0.0001321348,0.0000924655,0.00007224468,0.00001469384,0.000123256,0.9971822,0.0002135788,0.001209803,0.000002411466,0.0001692315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3581836,0.0002655856,0.6411847,0.00001523249,0.0001183198,0.0001813523,0.000009230675,0.00003076786,0.00001124341],"genre_scores_gemma":[0.9641483,0.00001458952,0.03570788,0.000003958595,0.00005100177,0.00001290978,0.00002922683,0.00002781804,0.00000434553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6059647,"threshold_uncertainty_score":0.7501347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01419594580181421,"score_gpt":0.2451594447024354,"score_spread":0.2309634989006212,"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."}}