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Record W1528099404 · doi:10.1109/ceidp.1989.69552

Measurement of organic and inorganic ions in cable insulation and shields

2003· article· en· W1528099404 on OpenAlexaff
Roland Gilbert, J.‐P. Crine, B. Noirhomme, S. Pélissou

Bibliographic record

VenueConference on Electrical Insulation and Dielectric Phenomena · 2003
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsExtraction (chemistry)PolyethyleneShieldsIonOxalateMaterials scienceIon chromatographyAnalytical Chemistry (journal)ChemistryInorganic chemistryChromatographyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

It was demonstrated that HPIC (high-performance ion chromatography) can detect inorganic and organic ions in PE (polyethylene) and XLPE (cross-linked PE) insulation and shields in concentrations as low as approximately 10 mu g/L in the extraction solutions. This analytical technique requires liquid extraction of the ions prior to their content evaluation. The limitations of the extraction technique used are discussed. The detected inorganic ions correspond to the elements determined by other analytical techniques, but the ionic fraction is small. The actual ionic fraction could be higher, since the extraction technique used is far from being optimized. Manufacturing and aging lead to increased SO/sup 2-//sub 4/ and Cl/sup -/ contamination in XLPE cables. Migration from the contaminated shields appears to be one of the causes for this increase. Use of the much cleaner acetylene black should improve the situation. Organic ions were also detected and appear to be essentially by-products of PE oxidation. It is possible that service aging induces the formation of more oxalate ions. Shields made with ethylene vinyl acetate may also generate some acetate ions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.030
GPT teacher head0.242
Teacher spread0.212 · 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.

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

Citations3
Published2003
Admission routes1
Has abstractyes

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