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Record W2088576342 · doi:10.1109/tpwrd.2007.905566

Evaluation of LV and MV Arc Parameters

2008· article· en· W2088576342 on OpenAlexaff
A. Gaudreau, Bohdan Koch

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2008
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsArc (geometry)ComputationElectric arcVoltageElectrical engineeringArc-fault circuit interrupterFault (geology)Circuit breakerElectronic engineeringComputer scienceEngineeringReliability engineeringAlgorithmMechanical engineeringPhysicsElectrodeShort circuit

Abstract

fetched live from OpenAlex

This paper presents an overview of the characteristics of arcing faults that occur on distribution systems, together with simple evaluation methods designed to assess their respective arc parameters. The approach proposed here is based on approximation curves and formulas derived from research studies including many laboratory tests as well as digital computations. Various practical tools are presented for estimating the arc voltage, low-voltage arc current and for taking into consideration the asymmetry of medium-voltage currents in order to evaluate the fault energy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.234
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations18
Published2008
Admission routes1
Has abstractyes

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