{"id":"W4285504848","doi":"10.1109/lra.2022.3190830","title":"Planar Magnetic Actuation for Soft and Rigid Robots Using a Scalable Electromagnet Array","year":2022,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Tsinghua Shenzhen International Graduate School","keywords":"Electromagnet; Electromagnetic coil; Magnetic field; Robot; Workspace; Actuator; Magnet; Mechanical engineering; Planar; Computer science; Magnetism; Materials science; Acoustics; Physics; Electrical engineering; Engineering; Artificial intelligence; Condensed matter physics","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":[0.00008366253,0.0002541729,0.0001835405,0.0002035352,0.0001700526,0.0001755511,0.000295888,0.0002387397,0.001012324],"category_scores_gemma":[0.0001379417,0.0001522479,0.0001365865,0.0001393242,0.0002746908,0.0003444711,0.000418671,0.0002064705,0.0004349838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001477319,"about_ca_system_score_gemma":0.0001529711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001533064,"about_ca_topic_score_gemma":0.0003295618,"domain_scores_codex":[0.9999012,0.000009366037,0.000004504687,0.00002694816,0.00004368765,0.0000142006],"domain_scores_gemma":[0.9999323,0.00001335542,0.00001867215,0.00000802143,0.00001314547,0.00001446798],"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":[0.00002623786,0.00001566728,0.0000919601,0.00005001176,0.000004909759,0.0000724481,0.0000220819,0.002988644,0.9796996,0.001300431,0.0004885326,0.01523936],"study_design_scores_gemma":[0.00009371933,0.0007986574,0.001900604,0.00002215689,0.0000285646,0.0005788118,0.00006491166,0.1465068,0.8244935,0.002209968,0.02321602,0.00008614764],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3394812,0.001723275,0.6370068,0.000766823,0.0002543092,0.0001510939,0.0001708082,0.002435154,0.01801064],"genre_scores_gemma":[0.8518494,0.0004882271,0.1436036,0.0002158967,0.00007992773,0.00009708867,0.00009485607,0.00005565824,0.003515432],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001012324,"threshold_uncertainty_score":0.003386557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075398871704897,"score_gpt":0.2241799012378421,"score_spread":0.2134259125207932,"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."}}