{"id":"W2290610200","doi":"10.1109/tmag.2015.2481924","title":"New Approach for Accurate Prediction of Eddy Current Losses in Laminated Material in the Presence of Skin Effect With 2-D FEA","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Eddy current; Skin effect; Finite element method; Electrical conductor; Current (fluid); Materials science; Magnet; Mechanics; Eddy-current testing; Mechanical engineering; Structural engineering; Physics; Composite material; Engineering; Thermodynamics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004281243,0.0001185241,0.0001850074,0.00008616058,0.00003218752,0.0000279251,0.0002638366,0.00005110455,0.00006942814],"category_scores_gemma":[0.00001598408,0.00007716365,0.00002922472,0.0002996197,0.0001088772,0.00007703138,0.000002254021,0.00009201148,0.000002659896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000021314,"about_ca_system_score_gemma":0.00009362864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003332469,"about_ca_topic_score_gemma":0.0001065366,"domain_scores_codex":[0.9989574,0.0001228503,0.0003175559,0.0002032363,0.0002341548,0.0001647804],"domain_scores_gemma":[0.9993687,0.000125633,0.00009897788,0.0002853797,0.00007976541,0.00004153525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006093259,0.00410774,0.0004905275,0.001733905,0.00002576661,0.000002599285,0.009340028,0.2653801,0.5422219,0.0005722916,0.002543995,0.1674878],"study_design_scores_gemma":[0.003614625,0.003944922,0.00199403,0.0001672066,0.000104378,0.00001044195,0.0006445447,0.03115042,0.956989,0.000206986,0.0009402508,0.0002331474],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.644803,0.00005933286,0.3530913,0.00009591643,0.0002427826,0.001300761,0.0001918393,0.00001747164,0.0001975514],"genre_scores_gemma":[0.9935995,0.00003194473,0.00588863,0.000005322825,0.00002853081,0.0003035978,0.000009009613,0.000009998174,0.000123445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4147671,"threshold_uncertainty_score":0.3146642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03436979169219773,"score_gpt":0.2680083075597123,"score_spread":0.2336385158675146,"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."}}