MétaCan
Menu
Back to cohort
Record W2076136622 · doi:10.1109/pes.2004.1373160

Data management issues associated with the August 14, 2003 blackout investigation

2004· article· en· W2076136622 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE Power Engineering Society General Meeting, 2004. · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsnot available
FundersPacific Northwest National LaboratoryNatural Environment Research Council
KeywordsBlackoutElectricityWork (physics)EngineeringInterimTask (project management)Scope (computer science)Task forceAeronauticsElectric power industryElectric powerOperations researchOperations managementComputer securityComputer scienceElectric power systemPower (physics)Systems engineeringPolitical scienceElectrical engineeringPublic administration

Abstract

fetched live from OpenAlex

The largest blackout in the history of the North American electric power grid occurred on August 14, 2003. An extensive investigation into what happened (and why) began immediately. The joint U.S.-Canadian task force led the effort, including support from the electric utility industry and several federal agencies, e.g. the U.S. Department of Energy. The North American Electric Reliability Council (NERC) supported the task force, including particularly the electricity working group. The overall blackout investigation team drew expertise from a large number of organizations, assembled into teams to address specific attributes of the blackout. This work describes the data management issues associated with supporting the blackout investigation, beginning with the immediate response in the days and weeks following the blackout, supporting the interim report, to the long-term plans for deriving lessons learned for implementing improvements in the overall process of outage disturbance reporting. The sole focus of This work is the electricity working group activities at NERC; the security and nuclear working groups are outside the scope of this paper.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score1.000

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 head0.012
GPT teacher head0.208
Teacher spread0.197 · 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