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Record W1708753980 · doi:10.1139/cgj-2013-0306

Intrinsic and relative permeabilities of shredded municipal solid wastes from the Qizishan landfill, China

2014· article· en· W1708753980 on OpenAlexvenueno aff
Xiao Bing Xu, Tony L. T. Zhan, Yunmin Chen, R.P. Beaven

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research Council
KeywordsBoreholePermeability (electromagnetism)Air permeability specific surfaceGeotechnical engineeringWater contentSoil scienceEnvironmental scienceSoil waterMaterials scienceGeologyComposite materialChemistry

Abstract

fetched live from OpenAlex

Testing specimens for laboratory analysis were created from borehole samples of municipal solid waste (MSW) drilled from different depths at the Qizishan landfill, China. Laboratory water retention curve (WRC), water permeability, and air permeability tests were carried out to study the effects of compression and biodegradation on intrinsic permeability and the effect of water content on the relative permeability of the borehole specimens. The value of intrinsic permeability coefficient, k0, in the Kozeny–Carman model was found to be influenced by both the compression and biodegradation processes. Furthermore, the intrinsic permeability, ki, measured by air was found to be about one order of magnitude larger than that measured by water. Based on the regression results of WRC, relative water and air permeabilities were analyzed through the van Genuchten–Mualem (vG–M) model. The measured relative air permeability could be well fitted by the vG-M model. The value of parameter γv was found to be critical for a good prediction of relative water and air permeabilities using the vG-M model.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations64
Published2014
Admission routes1
Has abstractyes

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Same venueCanadian Geotechnical JournalSame topicLandfill Environmental Impact StudiesFrench-language works237,207