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Record W2084933259 · doi:10.1139/t10-018

Preferential flow in geosynthetic clay liners exhumed from final covers with composite barriers

2010· article· en· W2084933259 on OpenAlexvenueno aff
Joseph Scalia, Craig H. Benson

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
FundersU.S. Nuclear Regulatory CommissionU.S. Environmental Protection Agency
KeywordsGeosynthetic clay linerHydraulic conductivityBentoniteGeotechnical engineeringWater flowGeomembraneGeologySoil waterSoil science

Abstract

fetched live from OpenAlex

Geosynthetic clay liners (GCLs) were exhumed from final covers with composite barriers (geomembrane over GCL) at two municipal solid waste landfills in the USA. Preferential flow and high hydraulic conductivity (>2 × 10 −9 m/s) was observed in eight of the 18 GCL samples collected from both sites. At one site, manganese oxide precipitate was concomitant with bundles of needle-punched fibers that conducted preferential flow. Nearly complete replacement of Na by Ca on the bentonite surface occurred in all GCL samples. GCLs with and without preferential flow could not be differentiated by physical and chemical properties commonly used to differentiate GCLs with high and low hydraulic conductivities (exhumed water content, swell index, mole fraction monovalent cations, soluble cation concentrations). The relative abundance of soluble cations in the pore water of GCLs exhibiting preferential flow was comparable to the relative abundance in the subgrade pore water, whereas the pore water in GCLs with distributed flow was more sodic than the pore water in the subgrade. Hydration experiments indicated that bentonite in GCLs initially hydrates in a zone surrounding bundles of needle-punching fibers. Cation exchange during this hydration process may create zones of higher hydraulic conductivity surrounding the fiber bundle, permitting preferential flow.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.991

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations27
Published2010
Admission routes1
Has abstractyes

Explore more

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