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Record W7103342892

Watching the Grid

2007· article· en· W7103342892 on OpenAlexaboutno aff

Bibliographic record

VenuePurdue e-Pubs (Purdue University System) · 2007
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsBlackoutReliability (semiconductor)Context (archaeology)GridSynchronization (alternating current)Power gridPower (physics)
DOInot available

Abstract

fetched live from OpenAlex

In August 2003, a major blackout shut power to a significant portion of the eastern United States and Canada. In the aftermath of that blackout, a joint commission from the US and Canada made several recommendations to improve the reliability of the power grid. These recommendation included establishing an independent source of reliability information, increasing research into reliability related tools and technologies, and the use of time synchronized data recorders. Research was conducted towards each of the these recommendations. An independent, inexpensive means of obtaining power grid data was developed using simple data acquisition units connected to wall outlets with the data being returned through the Internet. Various methods of time synchronization were explored, including NTP and wwvb. In addition, a computer model was developed to assist in the interpretation of the data and provide a means of exploring grid stability under various conditions. An evaluation of the simulation results and an analysis of the collected data is presented. The results include a summary of the normal conditions on the power grid and and examination of the results of certain abnormal occurrences. The results lead to an increased understanding of the operation of the power grid. When these results are taken in the context of the current social, economic, and political environments in which the power grid operates, they make progress toward the mitigation of the impacts of blackouts.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.003
GPT teacher head0.141
Teacher spread0.138 · 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 designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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