{"id":"W2146371490","doi":"10.1109/ccece.2008.4564664","title":"Finite element analysis of a Virtual Air Gap Variable Transformer","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite element method; Transient analysis; Transformer; Electromagnetic coil; Autotransformer; Electrical engineering; Air gap (plumbing); Transient (computer programming); Energy efficient transformer; Engineering; Computer science; Electronic engineering; Isolation transformer; Distribution transformer; Transient response; Structural engineering; Materials science; Voltage","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002950756,0.00025803,0.000341491,0.0004011098,0.0002351176,0.0006035955,0.0005515944,0.0008530717,0.002151533],"category_scores_gemma":[0.0006585527,0.0002363471,0.0003538617,0.0002574442,0.0006848951,0.0003584836,0.0002537501,0.0002515456,0.0003488305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003756266,"about_ca_system_score_gemma":0.0004976324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002203146,"about_ca_topic_score_gemma":0.001296104,"domain_scores_codex":[0.999775,0.00004703203,0.00000763233,0.00002846224,0.0001187554,0.00002318085],"domain_scores_gemma":[0.9997688,0.0001173814,0.00002772764,0.00002112754,0.00005520341,0.000009776586],"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":[0.00009974862,0.00003457816,0.001062772,0.0000834242,0.00001732023,0.0002093805,0.0001531257,0.9301179,0.03992572,0.01417402,0.0004812051,0.01364085],"study_design_scores_gemma":[0.000004188537,0.0000286097,0.0002120715,0.00000670239,0.000003641313,0.00003899444,0.0000281327,0.9949512,0.002956799,0.0006622268,0.001103023,0.000004476014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2128743,0.0002933215,0.7583362,0.0002688942,0.00006255452,0.00006228937,0.0001696495,0.0004054965,0.0275272],"genre_scores_gemma":[0.9527774,0.0001249264,0.04012248,0.00002875546,0.000007964994,0.00004215957,0.00007365709,0.00003698727,0.006785567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002203146,"threshold_uncertainty_score":0.007197559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01883699545866545,"score_gpt":0.1910425032993461,"score_spread":0.1722055078406807,"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."}}