{"id":"W4401810792","doi":"10.1016/b978-0-443-21432-5.00010-3","title":"Advanced control of power electronics−based machine learning","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Power electronics; Electronics; Control (management); Power (physics); Computer science; Electrical engineering; Engineering; Artificial intelligence; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001203972,0.0004676102,0.0006347348,0.0002041636,0.00003959323,0.00003451552,0.0002354533,0.0002722512,0.0004736052],"category_scores_gemma":[0.000005605961,0.00044611,0.0003694131,0.0000122125,0.00006211607,0.0000310102,0.00002470572,0.001076428,0.0001449251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001397679,"about_ca_system_score_gemma":0.0000697307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.891811e-7,"about_ca_topic_score_gemma":0.000005124225,"domain_scores_codex":[0.9986455,0.00001106109,0.0004646242,0.0002779131,0.0002526939,0.0003482255],"domain_scores_gemma":[0.9993523,0.00005135769,0.0001111225,0.0003150464,0.00006461967,0.0001055352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002507391,0.00000261257,0.000001720447,0.0002942784,0.0003482405,0.00003764606,0.0000989964,0.0009030011,0.0006610638,0.001977283,0.00007456677,0.9955755],"study_design_scores_gemma":[0.0006432135,0.0001039396,8.326434e-7,0.0005155329,0.0001636472,0.000009306877,0.000003622819,0.09698609,0.0003241714,0.001493083,0.8993192,0.0004373203],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001955435,0.01456279,0.001286481,0.00002075351,0.0008389067,0.0003286569,0.00005651347,0.0002777764,0.9826086],"genre_scores_gemma":[0.1501983,0.0002146941,0.0001160856,0.0001625833,0.00008178203,0.00002170648,0.00002346078,0.0002428076,0.8489386],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9951382,"threshold_uncertainty_score":0.9997991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005265525077165604,"score_gpt":0.1913962123345648,"score_spread":0.1861306872573992,"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."}}