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Record W2058728412 · doi:10.1109/pes.2008.4596770

Performance of Today's Intelligent Controllers and Meters, Elements of an Integrated Monitoring System for ADA

2008· article· en· W2058728412 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsSystems engineeringComputer scienceQuality (philosophy)Product (mathematics)Intelligent NetworkIntelligent sensorEmbedded systemEngineeringWireless sensor networkTelecommunicationsComputer network

Abstract

fetched live from OpenAlex

Nowadays, several manufacturers offer intelligent electronic devices (IED) or intelligent controllers to improve network performance. On the other hand, several reports are produced to define how the intelligent distribution system should look. Hydro-Quebec already proposed that the intelligent distribution network should include: network monitoring equipment monitoring, product monitoring In order to achieve these goals, the actual distribution system infrastructure (especially remotely controlled IED) shall be used to gather as much information as possible related to network, equipment and product (i.e. power quality) to improve the distribution system overall performance. Hydro-Quebec is conducting several projects to qualify and quantify the type of data that can be gathered from major distribution equipment. This paper reports some of the results and conclusions of those projects.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.214
Teacher spread0.195 · 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

Quick stats

Citations7
Published2008
Admission routes2
Has abstractyes

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