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Record W4254926859 · doi:10.1109/mei.2018.8507710

IEEE Transactions on Dielectrics and Electrical Insulation [Executive Committee]

2018· article· en· W4254926859 on OpenAlexaff
Maga Zine, Reimund Gerhard, Axel Mellinger, Stanislaw Gubanski, Resi Zarb, Iris Power, Fleming Robert, John Cherney, J. Densley, William Tanaka, E Phil, Yoshimichi Ohki, Davide Fabiani, J.J. Shea, Bruce Bernstein, Gian Carlo Montanari, David Allan, Susan Pollock, Louise Adam, C.H.J. Davies, Mandy Eastin-Allen, Sharon Frick, Asst Horger, Ron Keller, Lisa Krohn, Mark David, P.H.F. Morshuis, Andrea Cavallini, Éric David, Simon Rowland, Brian Stewart, Kai Wu

Bibliographic record

VenueIEEE Electrical Insulation Magazine · 2018
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsDielectricMaterials scienceElectrical engineeringDielectric strengthExecutive committeeElectric breakdownEngineering physicsAutomotive engineeringForensic engineeringMechanical engineeringEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0600.053

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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2018
Admission routes1
Has abstractno

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