{"id":"W3207376892","doi":"10.1109/icra48506.2021.9561357","title":"Tailored Magnetic Torsion Springs for Miniature Magnetic Robots","year":2021,"lang":"en","type":"article","venue":"","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Health Research","keywords":"Torsion spring; Torsion (gastropod); Bistability; Magnet; Torque; Robot; Stiffness; Actuator; Spring (device); Computer science; Millimeter; Mechanical engineering; Materials science; Engineering; Control theory (sociology); Structural engineering; Physics; Electrical engineering; Optoelectronics; Artificial intelligence; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008852238,0.0002257928,0.0001463205,0.0001778928,0.0001789249,0.0002133047,0.0003199061,0.0003602075,0.001522774],"category_scores_gemma":[0.0003031453,0.0001691457,0.0001014267,0.0001253954,0.000256001,0.0003332035,0.0002340802,0.0002300305,0.0003945209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002252462,"about_ca_system_score_gemma":0.0001380875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009732306,"about_ca_topic_score_gemma":0.0004007633,"domain_scores_codex":[0.9999369,0.000008434025,0.000003230961,0.00001182132,0.00003273706,0.000006842685],"domain_scores_gemma":[0.9999013,0.00003076681,0.0000365542,0.00001242511,0.00001063455,0.000008274886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004251534,0.00003079664,0.0003281309,0.0002089374,0.000007871023,0.0001392564,0.00005409517,0.01831343,0.9422112,0.01279206,0.001032823,0.02483884],"study_design_scores_gemma":[0.00009115669,0.0007675331,0.002380401,0.00005787501,0.0000273548,0.0007477903,0.00006788599,0.4637916,0.4778751,0.006873542,0.04725144,0.00006837556],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4820639,0.003077819,0.4899808,0.0007663307,0.0003951099,0.0001478295,0.0002645122,0.001599542,0.02170424],"genre_scores_gemma":[0.8612201,0.000597159,0.1333406,0.0000597219,0.00004443881,0.0001172581,0.00006253683,0.00005700203,0.0045011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001522774,"threshold_uncertainty_score":0.00509423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006668821840527629,"score_gpt":0.2170192639803247,"score_spread":0.2103504421397971,"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."}}