{"id":"W2053802558","doi":"10.1109/tmag.2011.2126049","title":"Novel Transmission Line Modeling Method for Nonlinear Permeance Network Based Simulation of Induction Machines","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Permeance; Nonlinear system; Computer science; Transmission line; Iterative method; Rotor (electric); Induction motor; Newton's method; Finite element method; Control theory (sociology); Electric power transmission; Line (geometry); Algorithm; Mathematics; Engineering; Voltage; Physics; Mechanical engineering","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":[0.0001778262,0.0001569521,0.0002073734,0.0001474352,0.00007911123,0.000006956813,0.00007865006,0.0001229452,0.00007391108],"category_scores_gemma":[0.000003133795,0.0001578044,0.0001550179,0.0003640487,0.00001132077,0.00006206204,1.683488e-7,0.0001640092,0.000001120116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002281734,"about_ca_system_score_gemma":0.00001539823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002469619,"about_ca_topic_score_gemma":0.00001358164,"domain_scores_codex":[0.9991775,0.00002596913,0.0003208928,0.0001638192,0.0001325662,0.0001792546],"domain_scores_gemma":[0.9995418,0.0001012082,0.00003908658,0.0001598508,0.0001028983,0.00005519388],"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":[0.00007211676,0.00008453838,6.24612e-7,0.00005334548,0.00002567733,1.014101e-7,0.0000962124,0.7786651,0.02211776,0.00000314957,0.000002891465,0.1988785],"study_design_scores_gemma":[0.0004692128,0.0002735472,0.000004062414,0.00003543217,0.0001747708,6.805349e-7,0.000003726108,0.9613792,0.03734331,0.00008984023,0.0000765963,0.000149674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002648275,0.00009761548,0.9966069,0.00001505469,0.0001871814,0.0002312032,0.00002995204,0.0001242115,0.00005963086],"genre_scores_gemma":[0.5159643,0.0000438833,0.4837989,0.00001427909,0.00006548398,0.00001692986,0.000006450315,0.00002915855,0.00006071397],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.513316,"threshold_uncertainty_score":0.6435077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04386004115449486,"score_gpt":0.2684376807347748,"score_spread":0.22457763958028,"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."}}