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Record W4402651630 · doi:10.1051/e3sconf/202456904003

Study pertaining to leak simulations in electrical leak location dipole testing. A better understanding of dipole testing calibration using various plate sizes and shapes

2024· article· en· W4402651630 on OpenAlexaff
Francis Labonté, C. Charpentier

Bibliographic record

VenueE3S Web of Conferences · 2024
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsLeakCalibrationDipoleLeak detectionReliability engineeringMaterials scienceComputer sciencePhysicsEngineeringMathematicsStatisticsThermodynamics

Abstract

fetched live from OpenAlex

According to standard ASTM D7007 for geoelectrical leak location (ELL) surveys on earth materials, a hole simulation or calibration must be performed before starting the actual survey. The standard also states that a 1/4 in diameter metal plate must be detectable based on specific signal strengths, if not, the survey cannot be considered completed by the ASTM standard and must be conducted on a 1 m x 1 m grid. Most ELL companies only perform the 1/4 inch test to see if the surveying speed will be fast or slow. The better the signal, the larger the grid, the faster the survey. Usually, leak location practitioners will then proceed to the leak location either way. The number of projects that fail the 1/4 inch test is quite important, so how do we push things further to ensure the best efficiency on site? What information is necessary to understand how the site responds to the test and what can we do to improve the quality of the survey? Here we will compare data gathered within 11 years with various calibration plate sizes and will explain the effects of field specific parameters, such as the simulation’s position, moisture, thickness, cover material homogeneity, and the most important factor of all: peripherical electrical isolation.

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)0.008
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.066
GPT teacher head0.291
Teacher spread0.224 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueE3S Web of ConferencesSame topicElectrostatic Discharge in ElectronicsFrench-language works237,207