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Record W2152441726 · doi:10.1109/wescan.1991.160518

A digital TNA for testing relays

2002· article· en· W2152441726 on OpenAlexaff
P.G. McLaren, R. Kuffel, R.P. Wierckx, J. Giesbrecht, L. Arendt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsResearch ManitobaUniversity of Manitoba
Fundersnot available
KeywordsRelayComputer scienceProtective relayTransient (computer programming)Digital protective relayNetwork analyzer (electrical)Power (physics)Spectrum analyzerElectronic engineeringEngineeringTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

The authors describe the design and performance of a digital transient network analyzer (DTNA) for testing relays. The DTNA uses a parallel processing architecture to run power system simulations in real time with a time setup of 50-100 mu s. Relays can be fed with the appropriate signals from the DTNA, and the output from the relay trip circuit can be fed back into the simulation. Examples are given of tests on a commercial distance relay.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

How this classification was reachedexpand

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 score0.972
Threshold uncertainty score0.244

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 head0.027
GPT teacher head0.193
Teacher spread0.166 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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