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Record W7046536428

Dielectric spectroscopy characteristics of new and aged high voltage insulating polymeric materials

2017· dissertation· en· W7046536428 on OpenAlexafffund

Bibliographic record

VenueMspace (University of Manitoba) · 2017
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaManitoba HydroUniversity of Manitoba
KeywordsDielectricHigh voltageReliability (semiconductor)VoltageThermalSensitivity (control systems)AgeingPower (physics)Dielectric spectroscopy
DOInot available

Abstract

fetched live from OpenAlex

Increased use of solid polymeric materials in the insulating structures of high voltage equipment for electric power systems over the past years has occurred despite a lack of understanding about how these materials age while in service. Therefore, studies of ageing are crucial for power system reliability and are important for both key participants of the electric power industry: utilities and consumers. The development of an accelerated ageing procedure that mimics the presence of the thermal gradient across the insulating structure is reported. A test module that applies a constant thermal gradient across a sample of insulation material has been designed, built, and tested. An additional study was conducted into evaluation protocols for ageing of polymeric materials used for outdoor applications based on the dielectric spectroscopy measurements: certain refinements to this method are proposed. A comprehensive sensitivity analysis has been developed to estimate uncertainties of the measured dielectric parameters.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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
Published2017
Admission routes2
Has abstractyes

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