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Record W2168328981 · doi:10.1109/elinsl.2004.1380501

Equipment health rating of power transformers

2005· article· en· W2168328981 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsPowertech Labs (Canada)
Fundersnot available
KeywordsReliability engineeringTransformerAsset managementEngineeringComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Transformers are major components of the power delivery system. In North America, a large proportion of them are approaching their end of design life and in need of replacement or refurbishment A program has been developed to assist engineers to diagnose and assess the health of power transformers. The program uses test and inspection data and equipment information such as nameplate, known design problems, operating history, and age to determine the equipment's health rating. The program calculates condition indexes of transformer components then combines them into an equipment health rating. Although the program automatically calculates such values, it also allows for experts to provide diagnostics and make recommendation on intervention, and to review all the final rating . The results can be used to quickly assess equipment health and provide comparison within a substation or the entire utility for asset management. Examples and case histories are used to show the merits and applications of the program for BC Hydro's system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.724
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.231
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it