{"id":"W4400878074","doi":"10.1109/tmech.2024.3420762","title":"Model-Free Magnetic Servoing Control: Leveraging Raw Magnetic Data for Robotic Manipulation","year":2024,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Characterization and Applications of Magnetic Nanoparticles","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Visual servoing; Raw data; Computer science; Control (management); Computer vision; Artificial intelligence; Robot","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":[0.0002896641,0.000530018,0.0005155612,0.0003034023,0.0002100078,0.0004406839,0.0009269415,0.0003912575,0.0006583335],"category_scores_gemma":[0.001173179,0.000279072,0.0003058209,0.0002350049,0.000413142,0.0007322154,0.000633323,0.0004669515,0.0002737976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000218848,"about_ca_system_score_gemma":0.0004865329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001832974,"about_ca_topic_score_gemma":0.002447968,"domain_scores_codex":[0.9996827,0.00003189995,0.00001674807,0.00006898443,0.0001781964,0.00002144797],"domain_scores_gemma":[0.9996914,0.00008647985,0.00007553012,0.00007605401,0.00005935074,0.00001116119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002335914,0.0001518258,0.001220609,0.0004017939,0.0000638582,0.0002143718,0.0002297191,0.3752818,0.2027919,0.01375484,0.002091354,0.4035642],"study_design_scores_gemma":[0.00001532974,0.0001065511,0.0005503035,0.00001634069,0.0000111255,0.00008864334,0.000009890261,0.9691983,0.02402365,0.002474359,0.00347704,0.00002832047],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01085797,0.0002097012,0.9867295,0.00005691743,0.00003761474,0.00002344287,0.00002700536,0.0007041276,0.001353705],"genre_scores_gemma":[0.7785518,0.0004002787,0.2184789,0.0001059094,0.00006265062,0.0001091434,0.0001524185,0.0001151072,0.002023806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001832974,"threshold_uncertainty_score":0.003644586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03781265692204294,"score_gpt":0.2458688678912168,"score_spread":0.2080562109691739,"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."}}