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Record W2743879743 · doi:10.1680/jenge.17.00001

Polymer-enhanced bentonite–sand to cover calcium-rich soil

2017· article· en· W2743879743 on OpenAlexaff
Mohamed Hosney, R. Kerry Rowe

Bibliographic record

VenueEnvironmental Geotechnics · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsBentoniteGeosynthetic clay linerGeomembraneHydraulic conductivityCalciumSoil coverSoil testGeotechnical engineeringEnvironmental scienceMaterials scienceComposite materialSoil waterSoil scienceGeologyMetallurgy

Abstract

fetched live from OpenAlex

The hydraulic and chemical properties of a polymer-enhanced bentonite–sand mixture (PEBSM) used as cover over calcium (Ca)-rich soil for 4 years is evaluated based on a series of isothermal laboratory-scale experiments. A 0·5 m thick calcium-rich soil (porewater with 1500 mg/l calcium ion (Ca2+)) was compacted into a laboratory column and then covered by a 0·07 m thick PEBSM layer. The PEBSM either was covered by an intact geomembrane (GMB) to mimic a composite liner or was in direct contact with the overlying soil (to simulate the case of a single-liner system). The hydraulic conductivity (k) and exchangeable cations of PEBSM were measured after 9, 21 and 48 months of exposure. The test results show that when PEBSM is used as a barrier over calcium-rich soil, there is only a small difference between the k of PEBSM covered with GMB (2·7 × 10−10 m/s) compared to the case without GMB (7·8 × 10−10 m/s) after 4 years in service. For both cases, k values after 48 months are considered low.

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 score0.005

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)0.0010.000

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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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