{"id":"W3004911649","doi":"10.1109/tpel.2020.2971424","title":"Planar Transformers in LLC Resonant Converters: High-Frequency Fringing Losses Modeling","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Power Electronics","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Converters; Transformer; Inductance; Planar; Topology (electrical circuits); Electrical engineering; Computer science; Electronic engineering; Engineering; Voltage","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007127118,0.0003539682,0.0003367859,0.0002268767,0.00009248279,0.00003208435,0.0002330116,0.000146061,0.00009009142],"category_scores_gemma":[0.000003308651,0.0004079138,0.0001314389,0.0005040455,0.00003285914,0.000416126,5.406075e-7,0.0008627792,0.00006057514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004806355,"about_ca_system_score_gemma":0.00008931413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004428671,"about_ca_topic_score_gemma":0.0001892381,"domain_scores_codex":[0.9981033,0.00002341942,0.0004246559,0.000404046,0.0002569343,0.0007876498],"domain_scores_gemma":[0.999494,0.00005398023,0.00002461625,0.0002186205,0.00002618211,0.0001825997],"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":[0.0001772414,0.00009317059,0.00001490103,0.0001330617,0.0001943022,0.00007042598,0.00316922,0.8792644,0.03766318,0.0004412434,0.00003987794,0.07873901],"study_design_scores_gemma":[0.001101531,0.0002147356,0.000004519496,0.00007479954,0.00003909798,0.00001172997,0.0003145628,0.9833496,0.01355102,0.0003786012,0.0004302806,0.0005295894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04635577,0.0006910607,0.9510268,0.0005209401,0.0004009577,0.0002628456,0.00003002714,0.0005433599,0.0001682616],"genre_scores_gemma":[0.99753,0.0007888083,0.001108955,0.000386304,0.00001926419,0.00004167976,0.000005804379,0.0001072968,0.00001188224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9511743,"threshold_uncertainty_score":0.9998373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026435193306579,"score_gpt":0.201903170350713,"score_spread":0.1916388184176472,"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."}}