{"id":"W2491259336","doi":"10.1109/tie.2016.2592866","title":"Parallel Computation of Wrench Model for Commutated Magnetically Levitated Planar Actuator","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Magnetic Bearings and Levitation Dynamics","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wrench; Thread (computing); Finite element method; Computer science; Computation; Actuator; Electromagnetic coil; Computational science; Magnet; Halbach array; Mechanical engineering; Engineering; Electrical engineering; Algorithm; Structural engineering; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0001452359,0.0001871654,0.000242756,0.0001403253,0.00007308584,0.00001806803,0.0001327262,0.0002370089,0.00004615261],"category_scores_gemma":[0.00001566609,0.0001622614,0.0001025569,0.0001998169,0.00005463963,0.00008702775,4.638798e-7,0.0002673133,0.000007344596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001345996,"about_ca_system_score_gemma":0.000131949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000871996,"about_ca_topic_score_gemma":0.00005213706,"domain_scores_codex":[0.9988643,0.00002912983,0.0004245794,0.0001716682,0.0001758689,0.0003344663],"domain_scores_gemma":[0.999323,0.0002491848,0.00006797117,0.0001583827,0.0001158072,0.00008561642],"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":[0.0002446643,0.0000930414,0.000001088447,0.00002660707,0.00008973086,2.944489e-7,0.0001197337,0.8745323,0.01763693,0.0009472641,0.000649385,0.1056589],"study_design_scores_gemma":[0.002900622,0.0005734771,0.000005390072,0.00004894881,0.00007185508,0.000002171966,0.00001274391,0.9888819,0.005450798,0.001317007,0.0005180623,0.0002169934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05249553,0.00003649429,0.9460577,0.0002736473,0.0002348825,0.0004630396,0.0001635848,0.0001646342,0.0001104256],"genre_scores_gemma":[0.9917642,0.0001372194,0.007586007,0.00002741845,0.00002953568,0.00007892261,0.00001662025,0.00004465298,0.0003153702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9392687,"threshold_uncertainty_score":0.661683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03211607506233936,"score_gpt":0.2385000576740976,"score_spread":0.2063839826117583,"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."}}