{"id":"W4206433092","doi":"10.1109/tie.2020.2988806","title":"IEEE Industrial Electronics Society","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Engineering and Technology Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Southeast University; Università di Bologna; Khalifa University of Science, Technology and Research; Argonne National Laboratory; Indian Institute of Technology Madras; Connaught Fund; University of Technology Sydney; Harbin Institute of Technology; Universidade de Pernambuco; Dalhousie University; Beihang University; York University; University of Wollongong; Keio University; Hamad Bin Khalifa University; Alexandria University; Mississippi State University; Université de Franche-Comté; Universidade de Vigo; Texas Tech University; Northwestern University","keywords":"Electronics; Electrical engineering; Engineering; Manufacturing engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001585712,0.0004046915,0.000368805,0.0001559313,0.0002435242,0.00005662214,0.0003697933,0.001058506,0.0000960887],"category_scores_gemma":[0.00001964742,0.0004709859,0.000258457,0.001576373,0.00007185922,0.0001679476,0.000001488252,0.003777198,0.00009715759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004876637,"about_ca_system_score_gemma":0.000320693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000512508,"about_ca_topic_score_gemma":0.00001176958,"domain_scores_codex":[0.9979378,0.00002760039,0.0004926612,0.0003803114,0.0002922858,0.0008693558],"domain_scores_gemma":[0.9992593,0.00009521462,0.00005591284,0.0003494844,0.00006225374,0.0001778677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001076392,0.0001566186,0.000007446068,0.00002651484,0.0008523333,0.000006846352,0.0002587018,0.8481916,0.03155084,0.00179063,0.04479257,0.0722583],"study_design_scores_gemma":[0.005043153,0.001381323,0.000001211991,0.00005246795,0.0002901891,0.0000308046,0.0001080877,0.1835393,0.5529443,0.0002801458,0.2550247,0.001304318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1411502,0.0005464588,0.8433684,0.003535715,0.003897119,0.0008364594,0.000157975,0.005463054,0.001044598],"genre_scores_gemma":[0.9976652,0.0004950201,0.0003322556,0.000299776,0.0008394594,0.00009881405,0.00001706523,0.0001225785,0.000129822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.856515,"threshold_uncertainty_score":0.9997742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03485086592552464,"score_gpt":0.2170103414484654,"score_spread":0.1821594755229408,"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."}}