{"id":"W4385487213","doi":"10.1109/actea58025.2023.10194101","title":"Transformers Faults Prediction Using Machine Learning Approach","year":2023,"lang":"en","type":"article","venue":"","topic":"Power Transformer Diagnostics and Insulation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Université du Québec à Rimouski","keywords":"Transformer; Computer science; Decision tree; Machine learning; Reliability engineering; Voltage; Artificial intelligence; Data mining; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005546747,0.0006313424,0.0007595037,0.001537138,0.0002504634,0.0006747585,0.0005050246,0.0008011188,0.001056234],"category_scores_gemma":[0.001878366,0.0001951173,0.0005789166,0.0007205812,0.0001578036,0.0005746087,0.0002135969,0.0005397859,0.0003697405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004988175,"about_ca_system_score_gemma":0.0005385261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008461374,"about_ca_topic_score_gemma":0.003917564,"domain_scores_codex":[0.9996581,0.0000676534,0.00003495908,0.0000919217,0.00008270346,0.00006464878],"domain_scores_gemma":[0.9990835,0.0005046992,0.00008162053,0.00004027763,0.0002595746,0.00003043262],"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":[0.0001888193,0.0002022792,0.01070635,0.00008361143,0.00006386716,0.0001420267,0.00002632697,0.8104255,0.002582234,0.0003989934,0.001242365,0.1739376],"study_design_scores_gemma":[0.000001777426,0.00001782248,0.0007008253,0.000003473748,0.000004930077,0.00001086843,0.000005221103,0.9984753,0.0005312795,0.0001804525,0.00006541131,0.000002714509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5273565,0.001335725,0.4638342,0.0003924841,0.0001333883,0.0001221726,0.0007539034,0.00246824,0.003603416],"genre_scores_gemma":[0.9746362,0.0001685955,0.02393548,0.00002414386,0.00002337091,0.00003251032,0.000394265,0.000009267332,0.0007762821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008461374,"threshold_uncertainty_score":0.01682425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01860273031341241,"score_gpt":0.2178133335992008,"score_spread":0.1992106032857884,"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."}}