{"id":"W4312813253","doi":"10.1109/tec.2022.3219097","title":"Modified Efficiency Estimation Tool for Three-Phase Induction Motors","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Energy Conversion","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Induction motor; Dependency (UML); Software; Electric motor; Computer science; Range (aeronautics); Control engineering; Brushed DC electric motor; Engineering; Automotive engineering; Voltage; Artificial intelligence; Electrical engineering","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":[0.0001176764,0.0001395091,0.00013364,0.0003426235,0.0004358378,0.000017265,0.0001066844,0.00006045684,0.0002102817],"category_scores_gemma":[0.00000188975,0.0001577107,0.000149366,0.000499136,0.00001393521,0.0001305992,7.289907e-7,0.0001552759,0.000005658576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002562263,"about_ca_system_score_gemma":0.00002264765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000536086,"about_ca_topic_score_gemma":0.000006070835,"domain_scores_codex":[0.9991556,0.00003119952,0.0001894063,0.0002045059,0.0002282355,0.0001910242],"domain_scores_gemma":[0.9996582,0.00005940138,0.00003417471,0.000169869,0.00002961738,0.00004876636],"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":[0.00005986351,0.0001191225,3.276733e-7,0.00001165788,0.00004011742,8.829466e-7,0.00003878422,0.8151193,0.01330679,0.0001034935,0.0002353969,0.1709643],"study_design_scores_gemma":[0.0009719775,0.000285306,0.000002043509,0.000003792741,0.00007339635,0.000003373348,0.00001375926,0.9537265,0.04353167,0.0001096743,0.001111423,0.0001670235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09409954,0.00002429599,0.904574,0.00003408821,0.0007433402,0.0001568884,0.00002482904,0.0002626675,0.00008030312],"genre_scores_gemma":[0.9984626,0.00001874768,0.0007398651,0.00003783067,0.00003185247,0.0002342215,0.00003096158,0.00002784192,0.0004161303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.904363,"threshold_uncertainty_score":0.6431257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310256728669236,"score_gpt":0.218226121107028,"score_spread":0.2051235538203357,"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."}}