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Record W4212879586 · doi:10.1109/pes.2008.4596816

IEEE Power Engineering Society 2008 General Meeting Control Center Issues NERC Reliability Standards Development

2008· article· en· W4212879586 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSmart Grid and Power Systems
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)Center (category theory)EngineeringControl (management)Reliability engineeringSystems engineeringEngineering managementPower (physics)Computer scienceElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

The North American Electric Reliability Corporation (NERC) is a nonprofit corporation formed for the purpose of becoming the North American electric reliability organization (ERO). NERC's predecessor organization, the North American Electric Reliability Council, was formed in 1968 as a result of the Northeast blackout in 1965 to promote the reliability of the bulk power systems of North America. Since its formation in 1968, NERC has been committed to ensuring the reliability of the North American bulk power system. To achieve that, NERC develops and enforces reliability standards; assesses North American bulk power system adequacy annually; audits owners, operators, and users for preparedness; and educates trains, and certifies industry personnel. NERC is a self-regulatory organization, subject to oversight by the United States (U.S.) Federal Energy Regulatory Commission (FERC) and governmental authorities in Canada. This paper discusses the NERC control center issues and the development of reliability standards for power systems.

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)0.004
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.072
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0720.034

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 head0.007
GPT teacher head0.202
Teacher spread0.196 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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