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Record W1841941055 · doi:10.1109/tdc.2006.1668516

Feeder and Network Evolution for the Distribution System of the Future

2006· article· en· W1841941055 on OpenAlexaboutno aff
Peter E. Sutherland, Frank R. Goodman, T. A. Short

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMerge (version control)AutomationElectric power distributionElectric power systemTelecommunicationsDistribution (mathematics)Electric powerComputer scienceDecentralizationSystems engineeringEngineeringOperations researchPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

Historically, electrical distribution systems have been designed to deliver power from the distribution substations to the end users. The future evolution of the distribution system, as envisioned in EPRI's Advanced Distribution Automation (ADA) initiative, will merge power delivery with distributed intelligent control and communications systems. This paper covers the results of a survey of electric utilities and a follow-up seminar with survey participants. Survey responses were obtained from eleven US and Canadian utilities across a wide spectrum. Responders included large multi-state utilities, companies in large urban areas, publicly and privately owned utilities, and a small rural utility. These results will help to shape future planning as to the most effective pathways to move forward in the evolution of the distribution system of the future

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.001

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 head0.002
GPT teacher head0.149
Teacher spread0.147 · 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 designSimulation or modeling
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

Citations5
Published2006
Admission routes1
Has abstractyes

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