{"id":"W3083187437","doi":"10.1109/tro.2020.3016511","title":"Design of Multi-Degrees-of-Freedom Microrobots Driven by Homogeneous Quasi-Static Magnetic Fields","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Degrees of freedom (physics and chemistry); Magnetic field; Robot; Homogeneous; Magnet; Control engineering; Mechanism (biology); Control theory (sociology); Field (mathematics); Computer science; Engineering; Simulation; Mechanical engineering; Artificial intelligence; Physics; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005403187,0.0002630797,0.000434686,0.0000745943,0.00008841239,0.00001624525,0.0003015644,0.0001041884,0.0003435151],"category_scores_gemma":[0.000002688226,0.0002702388,0.0002027065,0.000269466,0.0001203425,0.00005300237,0.000003435213,0.0002756534,0.00004311471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001712717,"about_ca_system_score_gemma":0.00009090158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001119119,"about_ca_topic_score_gemma":0.000007251909,"domain_scores_codex":[0.9986306,0.00009340858,0.0005164976,0.0002844904,0.0001874246,0.0002875603],"domain_scores_gemma":[0.9990472,0.0001837539,0.0001818613,0.0003252545,0.0001062479,0.0001557476],"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":[0.00005182553,0.0007196231,0.00008030465,0.00006103631,0.0001116518,0.000002647994,0.000618777,0.9535162,0.03989036,0.00003573613,0.0007120469,0.004199771],"study_design_scores_gemma":[0.001943435,0.001399678,0.00002398979,0.00007427063,0.0003848792,0.000002982359,0.0002498652,0.8994896,0.09587763,0.00005124795,0.00003829877,0.0004641485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003161644,0.0001211211,0.9955766,0.0002423372,0.0002414612,0.0003957343,0.000189296,0.00003263324,0.00003915413],"genre_scores_gemma":[0.8369711,0.00003878399,0.1625425,0.00005616785,0.00003990422,0.00001067244,0.00001242245,0.00004205262,0.000286395],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8338094,"threshold_uncertainty_score":0.999975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03172393351320166,"score_gpt":0.2427129184488402,"score_spread":0.2109889849356385,"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."}}