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Record W236541261 · doi:10.1201/9781003070580-10

Evaluation of a geosynthetic clay liner water retention curve using vapour equilibrium technique

2020· book-chapter· en· W236541261 on OpenAlexaff
M. A. Rouf, Rao Martand Singh, Abdelmalek Bouazza, Will P. Gates, R. Kerry Rowe

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeotechnical engineeringMaterials scienceGeology

Abstract

fetched live from OpenAlex

The Vapour Equilibrium Technique (VET) has gained popularity as a reliable method for controlling relative humidity as well as vapour suction in various porous media. In this study, super-saturated salt solutions were used to control Relative Humidity (RH) and to infer the water retention curve for a needle punched geosynthetic clay liner with respect to time under free swell and 20 kPa applied stress. Results showed that GCL sample RH plays a key role in moisture absorption/desorption behaviour and equilibration time when RH is in equilibrium with suction. Water absorption isotherms for the bentonite component of GCL agreed well with literature data. It was also observed that the effect of applied stress on water retention was more pronounced at high relative humidity and corresponding low suction. The results presented in this paper can help improve the understanding the water retention behaviour of GCLs in field applications such as waste containment liners and cover systems.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.069
GPT teacher head0.274
Teacher spread0.205 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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