{"id":"W1988400047","doi":"10.1109/tpwrd.2012.2205165","title":"Calculation of a Health Index for Oil-Immersed Transformers Rated Under 69 kV Using Fuzzy Logic","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Power Transformer Diagnostics and Insulation","field":"Engineering","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Transformer; Fuzzy logic; Oil analysis; Transformer oil; Voltage; Reliability engineering; Dissolved gas analysis; Fuzzy set; Engineering; Asset management; Computer science; Electronic engineering; Data mining; Electrical engineering; Petroleum engineering; Artificial intelligence; Business","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":[0.0002433772,0.0002381212,0.0003004991,0.0003110252,0.0001524343,0.00001476572,0.00006903231,0.0001652413,0.00006426282],"category_scores_gemma":[0.000001946974,0.0002524373,0.0002002884,0.0003495505,0.00004421409,0.0004239761,2.656086e-7,0.0001787502,0.000009633292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002425198,"about_ca_system_score_gemma":0.00007020517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001117095,"about_ca_topic_score_gemma":0.0000188488,"domain_scores_codex":[0.9985788,0.00003649397,0.0005244167,0.000169482,0.0002155886,0.0004752061],"domain_scores_gemma":[0.9994496,0.0001022227,0.00007000214,0.0001459445,0.00009676949,0.0001354454],"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":[0.0001841338,0.0004473118,0.0001051138,0.0003105567,0.0003376416,3.884815e-7,0.001757028,0.9327483,0.02692731,0.0002795518,0.00009078671,0.03681189],"study_design_scores_gemma":[0.009028374,0.001068386,0.00849976,0.0007491614,0.0006479127,0.00002577602,0.001646207,0.8224405,0.1497382,0.0007046415,0.003301788,0.002149296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1953528,0.0004788961,0.8019967,0.00007530085,0.001139097,0.0002964404,0.0001102489,0.0001064833,0.0004440428],"genre_scores_gemma":[0.9983661,0.0004594347,0.0008706641,0.000140124,0.00002209549,0.00003400812,0.00002781161,0.00005610776,0.0000237201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8030132,"threshold_uncertainty_score":0.9999928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03411303514187568,"score_gpt":0.2674807606082913,"score_spread":0.2333677254664156,"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."}}