MétaCan
Menu
Back to cohort
Record W3008267239 · doi:10.1680/jgrim.19.00088

Stabilisation of a clay soil by ion injection using an electrical field

2020· article· en· W3008267239 on OpenAlexaff
A. R. Estabragh, M J Moghadas, Akbar A. Javadi, J. Abdollahi

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Ground Improvement · 2020
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsDistilled waterSoil waterChemistryCalciumChlorideSoil testPermeability (electromagnetism)Ionic strengthSoil scienceKinetic energyStabiliserClay soilGeotechnical engineeringMaterials scienceEnvironmental scienceGeologyAqueous solutionChromatographyMembrane

Abstract

fetched live from OpenAlex

A programme of experiments was conducted to study the use of the electro-kinetic technique to transport a stabilising chemical agent through a clay soil. The experimental tests were undertaken on a clay soil in a special apparatus by applying a constant voltage gradient across the sample to introduce a solution of calcium chloride (CaCl 2 ) with different concentrations in the soil. The variations of shear strength across the sample resulting from the electro-kinetic process were determined. The experiments were conducted in two groups. In the first group, the electro-osmosis method was used for soil samples with distilled water. In the second group, the electro-kinetic technique was applied to the soil to transport the solution of calcium chloride with varying concentrations through the pores in the soil. The results showed that the strength of soil increased for both groups and the amount of increase in the second group was dependent on the concentration of calcium chloride injected into the soil. The injection of this stabiliser also increased the electric current and electro-osmotic permeability.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.209
Teacher spread0.199 · 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 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

Citations9
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Ground ImprovementSame topicElectrokinetic Soil Remediation TechniquesFrench-language works237,207