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Record W1896678433 · doi:10.1109/ceidp.1988.26314

Impurities in electrical trees grown in field-aged cables

2003· article· en· W1896678433 on OpenAlexaffabout
J.‐P. Crine, S. Haridoss, P.F. Hinrichsen, A. Houdayer, G. Kajrys

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversité de MontréalHydro-Québec
Fundersnot available
KeywordsImpurityPotassiumMaterials scienceAnalytical Chemistry (journal)Tree (set theory)CarbonizationElectrical engineeringChemistryComposite materialMetallurgyMathematicsChromatographyOrganic chemistryCombinatorics

Abstract

fetched live from OpenAlex

The micro-PIXE (proton-induced X-ray emission) facility of the University of Montreal was used to evaluate the impurity content in and out of electrical trees and the breakdown channels grown in a few field-aged cross-linked polyethylene cables. In a typical case, high amounts of Cl, Mg, Al, and K were detected in the electrical tree growing from a water tree. A wide dispersion of local impurity contents was observed in and out of the tree. In breakdown channels, traces of metallic conductor and concentric neutral as well as Si, Cl, K and Ca were observed in the carbonized walls of the channels. It is concluded that from this preliminary study it is difficult to determine whether some specific impurities may enhance the initiation of electrical tree, although very high amounts of chlorine, potassium, and calcium were detected in the studied trees.>

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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 designBench or experimental
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
Published2003
Admission routes2
Has abstractyes

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