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Record W3184665611 · doi:10.1680/jgein.21.00023

Self-healing of laboratory eroded defects in a GCL on silty sand

2021· article· en· W3184665611 on OpenAlexaff
T.-K. Li, R. Kerry Rowe

Bibliographic record

VenueGeosynthetics International · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeosynthetic clay linerBentoniteHydraulic conductivityGeosyntheticsGeotechnical engineeringMaterials scienceDistilled waterComposite materialPondingGeologySoil waterChemistrySoil science

Abstract

fetched live from OpenAlex

The self-healing of five geosynthetic clay liners (GCLs) with laboratory simulated down-slope erosion defects (quasi-circular holes and linear slits where there is little or no bentonite) upon hydration from Godfrey silty sand subgrade with w fdn = 16% under an overburden stress σ v = 20 and 100 kPa is examined. While there was an up to 9.6 mm reduction in hole diameter/slit width, none of the defects fully self-healed. The self-healing of these laboratory eroded specimens with a swell index of 10.2 ± 1.7 ml/2 g after hydration is generally smaller than that of the corresponding virgin GCLs. GCLs with powdered bentonite with an initial SI of 32 ml/2 g generally self-healed better and the intact specimens had a lower hydraulic conductivity than GCLs with granular bentonite with an initial SI of 24–26 ml/2 g. Higher mass per unit area of bentonite and overburden stress led to better self-healing. Ponding of distilled (DI) water above the GCL increased self-healing of GCL slightly more than simulated synthetic landfill leachate (SSL). The post-hydration hydraulic conductivity, k, of GCL specimens with holes/slits is shown to be about 1–3 orders of magnitude higher than that of the intact GCL specimen.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.999

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)0.0010.000

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 head0.009
GPT teacher head0.238
Teacher spread0.230 · 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.

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
Published2021
Admission routes1
Has abstractyes

Explore more

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