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Record W2109686517 · doi:10.1109/tdei.2009.5361568

Some general remarks on the dielectric loss mechanisms in mineral oils

2009· article· en· W2109686517 on OpenAlexaff
R. Bartnikas

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2009
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsMcGill University
Fundersnot available
KeywordsDielectricCopperThermal conductionMineral oilElectrical conductorMaterials scienceParticle (ecology)Dielectric lossCopper sulfideSulfideIonic bondingSulfurParticle sizeComposite materialMineralogyChemical physicsChemistryMetallurgyIonOptoelectronicsPhysical chemistryOrganic chemistryGeology

Abstract

fetched live from OpenAlex

The mechanisms of conduction and dielectric loss pertaining to electrical insulating oils, are examined with specific reference to the conduction and dielectric loss processes involving ionic and macroscopic particle charge carriers. Specific examples are presented; one of the most serious types of conduction by particles is that due to semiconductive copper sulfide particles, which are formed in a reaction between copper conductors or copper particles and the corrosive sulfur components contained in the oils.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.006

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 head0.009
GPT teacher head0.215
Teacher spread0.205 · 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

Citations16
Published2009
Admission routes1
Has abstractyes

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