{"id":"W1541872568","doi":"","title":"Study and detection of demagnetization in line start permanent magnet synchronous machines using artificial neural network","year":2012,"lang":"en","type":"article","venue":"International Conference on Electrical Machines and Systems","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Magnet; Demagnetizing field; Artificial neural network; Line (geometry); Computer science; Control theory (sociology); Engineering; Mechanical engineering; Artificial intelligence; Physics; Magnetic field; Mathematics; Geometry","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":[0.0002413438,0.0001456437,0.0002392571,0.0002078551,0.0000421228,0.00005541053,0.00006731816,0.00005581841,0.00001727571],"category_scores_gemma":[0.00002518069,0.0001260718,0.00002602132,0.0002488435,0.00001462541,0.0001054693,0.00001418077,0.0001477004,9.510101e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005364084,"about_ca_system_score_gemma":0.000007312544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003911874,"about_ca_topic_score_gemma":0.0001081995,"domain_scores_codex":[0.9989773,0.0001001665,0.00036406,0.0001487489,0.0002057937,0.0002039122],"domain_scores_gemma":[0.9996837,0.00006224049,0.00006717623,0.00006536465,0.00005837687,0.00006315349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002977034,0.0007717889,0.2940746,0.0001577095,0.000289456,0.00002187898,0.0008104708,0.1759801,0.06435087,0.009374781,0.00002161432,0.453849],"study_design_scores_gemma":[0.0002058168,0.0002408481,0.01903973,0.00002076913,0.00002724404,0.000021053,0.00002051757,0.9800781,0.00005023974,0.0001743175,0.000004610748,0.000116746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936569,0.00119897,0.004246396,0.00001967635,0.0003068511,0.0002369807,0.000004479513,0.00003223072,0.0002975215],"genre_scores_gemma":[0.9994881,0.00008749822,0.00003381171,0.000007577563,0.0003214988,0.0000151447,0.000008044113,0.0000123946,0.00002596706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.804098,"threshold_uncertainty_score":0.514106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03369052878534537,"score_gpt":0.2708441036484364,"score_spread":0.237153574863091,"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."}}