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Record W2158113978 · doi:10.1109/mper.2001.4311176

Experimental Performance Evaluation of a Wavelet-Based on-Line Voltage Detection Method for Power Quality Applications

2001· article· en· W2158113978 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

VenueIEEE Power Engineering Review · 2001
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVoltageWaveletPower qualityComputer sciencePower (physics)Line (geometry)Set (abstract data type)Scheme (mathematics)Electric power systemElectronic engineeringQuality (philosophy)EngineeringArtificial intelligenceElectrical engineeringMathematics

Abstract

fetched live from OpenAlex

This article evaluates the performance of a wavelet-based, on-line (real-time) voltage detection scheme for power quality applications. The objectives are (1) to demonstrate suitability of the proposed method in detecting faults/disturbances in a power system and (2) to compare its performance with that of a conventional scheme. Two static transfer switch (STS) systems are chosen as frameworks for comparison; a low-voltage laboratory STS set-up for which measured results are provided, and a medium-voltage STS system for which detection times are derived based on simulation, using the EMTDC/PSCAD.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.076
GPT teacher head0.373
Teacher spread0.297 · 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