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Record W2141523242 · doi:10.1139/t05-050

Change in leachate chemistry and porosity as leachate permeates through tire shreds and gravel

2005· article· en· W2141523242 on OpenAlexvenueno aff
Reagan McIsaac, R. Kerry Rowe

Bibliographic record

VenueCanadian Geotechnical Journal · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLeachateCloggingHydraulic conductivityDrainageGeotechnical engineeringPorosityEnvironmental scienceNatural rubberGeologyWaste managementSoil scienceMaterials scienceComposite materialEngineeringSoil water

Abstract

fetched live from OpenAlex

Rubber tire shreds are an attractive potential alternative to conventional gravel in the drainage layer of leachate collection systems at the base of landfills, yet the clogging and thus the long-term performance of tire shreds in this application is not known. This paper presents the results of an experimental investigation into the clogging potential of rubber tire shreds used as part of a leachate collection system at the base of a landfill when permeated with leachate. Experimental columns filled with two different rubber tire shreds and a conventional gravel drainage material were used to study the spatial and temporal variation of leachate characteristics and porosity changes within the drainage materials. It is shown that there are significant differences in the pore structures of the drainage materials and that these differences affect clog development and the length of time it takes for the hydraulic conductivity to drop below a threshold of 10 –5 m/s. The gravel is found to have a service life at least three times greater than that of an equivalent thickness of compressed (at 150 kPa) tire shred.Key words: tire shreds, landfill, clogging, hydraulic conductivity, porosity, leachate collection.

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 score0.441
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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

Citations38
Published2005
Admission routes1
Has abstractyes

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