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Record W2152275746 · doi:10.1109/tdc.2005.1546885

Effective Sounding Depths for HVDC Grounding Electrode Design: Wenner versus Schlumberger Methods

2005· article· en· W2152275746 on OpenAlexaff
W. Ruan, Robert Southey, Simon Fortin, F. Dawalibi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsDepth soundingVertical electrical soundingElectrical resistivity and conductivityGeologyGeotechnical engineeringSoil resistivityElectrical resistivity tomographySoil scienceEngineeringElectrical engineeringGroundwaterAquifer

Abstract

fetched live from OpenAlex

This paper compares the performance of the Wenner and Schlumberger soil resistivity measurement methods for vertical electrical sounding. The effective sounding depths of the two methods are examined, based on computer simulations of soil resistivity measurements in various two-layer soil structures. Also studied are uncertainties associated with both methods in the prediction of soil models, when near-surface local soil volumes with distinct electrical properties are present. It is shown that the Schlumberger method is particularly sensitive to such finite soil volumes, potentially resulting in significant error in the estimated deep soil resistivity and therefore in HVDC grounding electrode design

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)0.007
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.026
GPT teacher head0.352
Teacher spread0.326 · 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

Citations15
Published2005
Admission routes1
Has abstractyes

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