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Record W2118769984 · doi:10.1144/1470-9236/08-079

Application of resistivity method in environmental study of the appearance of soil water in the central part of Tenth of Ramadan City, Egypt

2010· article· en· W2118769984 on OpenAlexaff
Mohamed Eleraki, Mohamed M. Gadallah, Khaled S. Gemail, Mohamed Attwa

Bibliographic record

VenueQuarterly Journal of Engineering Geology and Hydrogeology · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsElectrical resistivity and conductivityGeologySoil scienceGeotechnical engineeringEnvironmental scienceHydrology (agriculture)MineralogyEngineering

Abstract

fetched live from OpenAlex

Abstract Tenth of Ramadan City is an important industrial and urban area in Egypt. The appearance of soil water seepages in the central part of the city represents a great environmental problem. Direct current resistivity measurements in the form of 1D and 2D surveys were carried out to show the relation between this problem and both lateral and vertical variations of a clay layer that may act as a geological barrier in the area. Twenty-seven Schlumberger sounding points were distributed over a grid with unequal spacing depending on the civil constructions and topography of the area. These sounding points were quantitatively interpreted to obtain the subsurface layer distribution and define the expected clay barrier. Five 2D resistivity profiles were measured along some interpreted anomalies from the 1D sounding survey. A Wenner array was selected because of its sensitivity in detecting vertical changes in the subsurface resistivity. The results of the resistivity inversion indicate that the subsurface resistivity can change rapidly within a short distance. However, from the resulting models it was possible to correlate the resistivity ranges with subsurface geological data obtained from shallow boreholes. This correlation shows the importance of 2D resistivity imaging for mapping of the clay barrier layer.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.203
Teacher spread0.198 · 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

Citations28
Published2010
Admission routes1
Has abstractyes

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