{"id":"W2152661282","doi":"10.1109/coase.2010.5584003","title":"Optimal motion control of magnetically levitated microrobot","year":2010,"lang":"en","type":"article","venue":"","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Levitation; Electromagnet; Magnetic levitation; Motion control; Workspace; Control theory (sociology); Magnetic field; Yoke (aeronautics); Flywheel; Range (aeronautics); Control system; Magnet; Physics; Computer science; Mechanical engineering; Engineering; Robot; Electrical engineering; Control (management); Artificial intelligence; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000415662,0.0005315983,0.000529395,0.0001959574,0.0003558648,0.0006119527,0.0004857819,0.0004411699,0.0006528368],"category_scores_gemma":[0.0005873644,0.0003249246,0.0002744638,0.0001538435,0.0006412642,0.0003372785,0.0004884881,0.0002933728,0.0001601376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000645061,"about_ca_system_score_gemma":0.0006966318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003620048,"about_ca_topic_score_gemma":0.002514535,"domain_scores_codex":[0.9997428,0.0000542844,0.00001153685,0.0000708079,0.00007202956,0.000048502],"domain_scores_gemma":[0.9997507,0.00007769123,0.0000719188,0.00001274422,0.00006825805,0.00001874406],"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":[0.0002332242,0.00006880342,0.0005117827,0.0002566952,0.00003925527,0.0001790989,0.0002205231,0.7965058,0.1532876,0.01092961,0.0007389259,0.03702872],"study_design_scores_gemma":[0.00002986515,0.0001840566,0.0003419679,0.000006229316,0.000007642616,0.00001569932,0.00002040933,0.9892853,0.007897204,0.001462188,0.0007367261,0.00001274415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1636152,0.0007349916,0.8273509,0.0003805439,0.0001065991,0.00006962182,0.00005750139,0.0005584703,0.007126263],"genre_scores_gemma":[0.9703999,0.0001691928,0.02726345,0.00004479701,0.00001416238,0.00007884014,0.00002793198,0.00002315375,0.001978632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003620048,"threshold_uncertainty_score":0.007197976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004278844528344293,"score_gpt":0.2110266691750847,"score_spread":0.2067478246467404,"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."}}