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Record W1962022108 · doi:10.1139/s04-062

Environmental, geotechnical, and hydraulic behaviour of a cellulose-rich by-product used as alternative cover material

2005· article· en· W1962022108 on OpenAlexaffvenue
Alexandre R. Cabral, Guy Lefèbvre

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBiodegradationLeachateEnvironmental scienceWaste managementRaw materialLeaching (pedology)Environmental engineeringChemistryEngineeringSoil waterSoil science

Abstract

fetched live from OpenAlex

Deinking by-product (DBP), a cellulose-rich by-product produced in the early stages of the paper recycling process, has been used as alternative material for the construction of cover systems for municipal waste disposal facilities and acid-producing mine residues. Because of the high organic content of this material, covers constructed with it are susceptible to biodegradation and, thus, to changes in their properties with time. With the goal of identifying the biodegradation parameters that could influence the long-term behaviour of DBP covers, an experimental laboratory program was developed and a series of 15 samples of DBP were monitored in biodegradation tests for 400 d. Periods of intermittent water percolation allowed for collection of leachate. The evolution of gas and leachate production was monitored in terms of quality and quantity. According to the results obtained, the hydraulic and geomechanical properties of importance for a cover do not seem to be adversely affected by the level of biodegradation of the DBP or by mass loss. Key words: cover systems, deinking by-products, biodegradation, mass loss by gas production, mass loss by leaching.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0000.000

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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 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

Citations10
Published2005
Admission routes2
Has abstractyes

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