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Record W2099852503 · doi:10.1049/cp.2009.0584

CIGRE/CIRED/UIE joint working group C4.110, voltage dip immunity of equipment in installations - main contributions and conclusions

2009· article· en· W2099852503 on OpenAlexaff
Math Bollen, Mark Stephens, Sasa Djokic, R. Neumann, Alex McEachern, J.V. Milanović, José Romero Gordon, B. Brumsickle, Gaétan Ethier, Francisc Zavoda, Kurt Stockman

Bibliographic record

VenueIET Conference Publications · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLife Cycle Costing Analysis
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsMandateHarmonicsVoltageJoint (building)Power (physics)Work (physics)Electrical engineeringCzechPower qualityComputer scienceEngineeringTelecommunicationsMechanical engineeringCivil engineeringPhysicsPolitical science

Abstract

fetched live from OpenAlex

This paper presents the results from the work of joint working group C4.110: a cooperation between CIGRE, CIRED and UIE. Its mandate period stretches from early 2006 through early 2009. The group has addressed several aspects of the immunity of especially, industrial equipment against voltage dips. Quantifying or specifying equipment performance is part of the assessment or improvement of the voltage-dip ride-through of an industrial process. (4 pages)

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)0.027
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.051
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.007
Science and technology studies0.0020.002
Scholarly communication0.0080.004
Open science0.0060.004
Research integrity0.0060.002
Insufficient payload (model declined to judge)0.0100.005

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 head0.043
GPT teacher head0.261
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations26
Published2009
Admission routes1
Has abstractyes

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