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Record W1819897779 · doi:10.1109/pess.2001.970339

Fast processing of resistivity sounding measurements in N-layer soil

2001· article· en· W1819897779 on OpenAlexafffund
F.H. Shoui, P.J. Lagacé, Xuan-Dien Do

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsPolytechnique MontréalÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrical resistivity and conductivityDepth soundingVertical electrical soundingInversion (geology)GeologySoil resistivityReliability (semiconductor)Electrical resistivity tomographyMaterials scienceGeometryMineralogyGeotechnical engineeringMechanicsMathematicsElectrical engineeringPhysicsThermodynamicsEngineeringGroundwater

Abstract

fetched live from OpenAlex

This paper presents a new method and derives the theoretical equations for calculation of the apparent resistivity standard curves of horizontally multilayered models. For known earth parameters, the apparent resistivity distribution can be computed efficiently by this method. The profile of the apparent resistivity calculated with Schlumberger electrode arrangement for an arbitrary number of layers is presented. However, to prove the reliability of the present method, the apparent resistivity of given three to five layer models is calculated for the Wenner array using existing methods and the presented one. Also, this paper uses an inversion method to find the electrical grounding parameters of an N-layered earth (resistivities and thicknesses) corresponding to a specific mathematical model. Parameters estimation is carried out in such a way as to get a fitting between the set of resistivity values measured by means of Schlumberger's method, and those calculated from the mathematical model using such 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.075
GPT teacher head0.286
Teacher spread0.211 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2001
Admission routes2
Has abstractyes

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