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Record W2007457396 · doi:10.1049/cp:20010726

Diagnostic of overheating underground distribution cable joints

2001· article· en· W2007457396 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
TopicThermal Analysis in Power Transmission
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsOverheating (electricity)Environmental scienceComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

A great deal of power failures occur at cable joints in Hydro-Quebec's underground conduit network. Many failures are due to the degradation of the electrical connection inside these joints and the corresponding degradation of their electrical insulation. Hydro-Quebec started an infrared thermography program for underground cable joints. This program has been implemented to perform a predictive maintenance and withdraw the defective joints before failure. This program has very strict withdrawal criteria. Those criteria have until now no real scientific and experimental basis. Moreover, there are serious discussions as to whether a punctual measurement of the temperature of a cable joint can really represent the health state of its electrical connection. Also, for how long a temperature measurement is valid and therefore what should be the best frequency of temperature measurement? A computer program based on sound cable joint withdrawal criteria has been developed. It diagnoses defective cable joints by detecting signs of electrical connection degradation before their failure.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.904

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)0.0010.000

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 head0.007
GPT teacher head0.202
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

Citations11
Published2001
Admission routes2
Has abstractyes

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