{"id":"W2015960841","doi":"10.1088/0022-3727/39/18/002","title":"Eddy current damping for magnetic levitation: downscaling from macro- to micro-levitation","year":2006,"lang":"en","type":"article","venue":"Journal of Physics D Applied Physics","topic":"Magnetic Bearings and Levitation Dynamics","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Levitation; Magnetic levitation; Eddy current; Electrodynamic suspension; Current (fluid); Macro; Physics; Magnetic damping; Mechanics; Materials science; Acoustics; Magnetic field; Computer science; Thermodynamics; Magnetic energy; Magnet; Magnetization; Vibration","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001595647,0.000254642,0.0003636606,0.00006575632,0.00009499589,0.0001446263,0.0002101266,0.00005804382,0.00001349883],"category_scores_gemma":[0.00001080054,0.0002726831,0.0001872447,0.0003010473,0.00002515429,0.0001902091,0.00002394534,0.0002721866,0.00002249694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001059617,"about_ca_system_score_gemma":0.00004001799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008595971,"about_ca_topic_score_gemma":0.00000305332,"domain_scores_codex":[0.9985434,0.00001404907,0.0006460501,0.0001883036,0.0003258038,0.0002824275],"domain_scores_gemma":[0.998997,0.0001867411,0.0002772823,0.0001682,0.000268302,0.0001024526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003354381,0.0001133364,0.00004261953,0.0001696146,0.00004136496,7.188561e-7,0.0007675088,0.5444262,0.2444712,0.01732988,0.002224297,0.1903797],"study_design_scores_gemma":[0.005964545,0.0005117861,0.005074646,0.0007208883,0.0007300789,0.000007566353,0.0007902258,0.397242,0.1127015,0.4378573,0.03617601,0.002223428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2699627,0.0003725062,0.7278047,0.00006524267,0.0008327125,0.0003883083,0.00007107994,0.00005472746,0.0004480216],"genre_scores_gemma":[0.9075748,0.00003145548,0.08880597,0.00008632239,0.003237278,0.00004175432,0.0001122546,0.0000815814,0.00002862933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6389988,"threshold_uncertainty_score":0.9999725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108123766489381,"score_gpt":0.2267174745583253,"score_spread":0.2159050979093872,"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."}}