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Record W2510056611 · doi:10.1680/jgein.16.00017

Physical and hydraulic response of geomembrane wrinkles underlying saturated fine tailings

2016· article· en· W2510056611 on OpenAlexaff
Prabeen Joshi, R. Kerry Rowe, R.W.I. Brachman

Bibliographic record

VenueGeosynthetics International · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeomembraneWrinkleTailingsMaterials scienceHigh-density polyethyleneGeotechnical engineeringLinear low-density polyethylenePolyethyleneComposite materialSlurryGeologyMetallurgy

Abstract

fetched live from OpenAlex

The effect of applied pressure on the deformation of a prescribed wrinkle, with and without a hole, in four different geomembranes (1 and 2 mm thick high density polyethylene (HDPE) and 1 and 2 mm thick linear low-density polyethylene (LLDPE)), placed on a compacted silty-sand underliner and backfilled with saturated fine tailings at 65% solids content, is investigated. For the 1 mm thick geomembranes without holes, the gap beneath the wrinkle was eliminated (but the geomembrane was excessively strained) at an applied total stress of 250 kPa, whereas for the 2 mm thick geomembranes the gap remained even under a total stress of 1000 kPa. The short-term performance was the same for both LLDPE and HDPE. For wrinkles with a hole, any gap that remained beneath the wrinkle was completely filled by tailings. The tailings migrated into the gap beneath the wrinkle partly as free-flowing slurry and partly under the applied hydraulic gradient. There was a difference in the shape of the final wrinkle depending on whether the hole in the wrinkle was present before or after backfilling with tailings. However, the same leakage was measured through a 10 mm diameter hole in both cases. With an increase in applied vertical stress, the leakage decreased.

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 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 score0.458
Threshold uncertainty score0.907

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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.

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

Citations9
Published2016
Admission routes1
Has abstractyes

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