{"id":"W2001699039","doi":"10.1109/ecce.2012.6342536","title":"Core loss prediction in electrical machine laminations considering skin effect and minor hysteresis loops","year":2012,"lang":"en","type":"article","venue":"","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Hydro-Québec","keywords":"Lamination; Core (optical fiber); Hysteresis; Materials science; Waveform; Electrical steel; Magnetic hysteresis; Magnet; Skin effect; Magnetic field; Magnetic core; Magnetic flux; Mechanics; Voltage; Electromagnetic coil; Composite material; Physics; Magnetization; Condensed matter physics; Engineering; Electrical 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":[0.0002506521,0.00007634003,0.0001033167,0.0000499863,0.0000778229,0.00003138187,0.00005699431,0.00003882611,0.0007490534],"category_scores_gemma":[0.00005792172,0.00005734395,0.00001328249,0.000111785,0.00005295069,0.0001138079,0.00004769947,0.00005118726,0.00006763229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000022792,"about_ca_system_score_gemma":0.000008025155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000194444,"about_ca_topic_score_gemma":0.0000761236,"domain_scores_codex":[0.9993717,0.00003967866,0.0001538882,0.0001389887,0.00008799973,0.0002077246],"domain_scores_gemma":[0.9996552,0.0001163527,0.0000273616,0.0001199289,0.00001486848,0.00006632419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004149687,0.000255894,0.2428425,0.0001191346,0.000006200077,0.000002998587,0.0005794759,0.00001300914,0.7222925,0.0101049,0.001367593,0.02237426],"study_design_scores_gemma":[0.001639127,0.000423992,0.4881127,0.00005150272,0.00006288104,0.0001651229,0.0000994307,0.01907619,0.4828542,0.0004852366,0.006585816,0.0004436962],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958798,0.0002913394,0.0007569928,0.0001865279,0.00005695056,0.0002609636,0.00001300369,0.00004763635,0.002506789],"genre_scores_gemma":[0.997805,0.00001087531,0.001027667,0.00005219879,0.00004595838,0.00008692683,0.00000517578,0.00000602601,0.0009601598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2452702,"threshold_uncertainty_score":0.820161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01990859658882807,"score_gpt":0.2504522326306832,"score_spread":0.2305436360418551,"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."}}