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Record W2341626894 · doi:10.1680/jgein.16.00006

Polychlorinated biphenyl diffusion through HDPE geomembrane

2016· article· en· W2341626894 on OpenAlexafffund
R. Kerry Rowe, D. D. Jones, Guy A. Rutter

Bibliographic record

VenueGeosynthetics International · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaMinisterio de Ciencia e Innovación
KeywordsGeomembraneHigh-density polyethyleneComposite numberDiffusionPartition coefficientEnvironmental scienceAquiferVinyl chlorideMaterials scienceMunicipal solid wasteGeotechnical engineeringPolyethyleneEnvironmental engineeringEnvironmental chemistryGroundwaterComposite materialChemistryWaste managementGeologyPolymerChromatographyThermodynamicsEngineering

Abstract

fetched live from OpenAlex

Experiments conducted to evaluate the partitioning coefficient from aqueous solution into and out of high-density polyethylene geomembrane, as well as the diffusion coefficient through the geomembrane are reported. The best estimate partitioning coefficient (S gf ) is about 150 000 with an upper-bound estimate of 325 000. The best estimate diffusion coefficient (D g ) is 1.0 × 10 −14 m 2 /s, with lower and upper bounds of 0.5 × 10 −14 and 5 × 10 −14 , respectively. Using the diffusive properties obtained from the above experiments, the potential impacts on an aquifer of the migration of polychlorinated biphenyls and chloride are compared for a composite liner in a hypothetical municipal solid waste landfill. It is shown that, with good construction quality assurance to limit the number of holes and length of covered wrinkles to acceptably low values, a modern composite liner limited the impact of polychlorinated biphenyls on the aquifer concentration to well below regulatory limits.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.997

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.003

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 head0.227
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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

Citations24
Published2016
Admission routes2
Has abstractyes

Explore more

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