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Record W1501679162 · doi:10.1109/mei.2015.7214441

Using the inclined-plane test to evaluate the resistance of outdoor polymer insulating materials to electrical tracking and erosion

2015· article· en· W1501679162 on OpenAlexafffund
Refat Atef Ghunem

Bibliographic record

VenueIEEE Electrical Insulation Magazine · 2015
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsTracking (education)ErosionMaterials scienceComposite materialForensic engineeringEnvironmental scienceEngineeringGeology

Abstract

fetched live from OpenAlex

Evaluating the electrical tracking and erosion resistance of polymeric housing materials is an essential task performed in the development of outdoor insulators. “Tracking” means the formation of a surface carbonaceous path, and “erosion” means weight loss of the housing material. An absolute measurement of the tracking and erosion resistance is not possible; only relative ranking of composites can be achieved using the standard tracking and erosion tests. During the early use of organic insulating materials, failure due to tracking was a major concern, and therefore standard screening methods were proposed to evaluate the tracking rather than the erosion resistance. Erosion has become more important following the development of tracking resistant composites containing high levels of inorganic fillers.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.328
Teacher spread0.259 · 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

Citations39
Published2015
Admission routes2
Has abstractyes

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