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Record W4386605339 · doi:10.1201/9781003386889-88

Effect of aged geomembrane extrusion welding on antioxidant depletion

2023· book-chapter· en· W4386605339 on OpenAlexaff
Mamdouh M. Ali, R. Kerry Rowe

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeomembraneExtrusionWeldingAntioxidantMaterials scienceMetallurgyComposite materialChemistryBiochemistry

Abstract

fetched live from OpenAlex

High-density polyethylene geomembranes (HDPE GMBs) are in-situ welded to create an “impermeable seal”. Extrusion welds are primarily used for repairs, curves, and other welds not accessible to fusion welding machines. A welding rod which is fed into the extrusion machine is made from the same raw materials for adherence/compatibility requirements between the two materials. The examined geomembrane was welded using preheat and barrel temperatures of 230°C and 250°C, respectively. In a municipal solid waste (MSW) landfill, an extrusion weld facing upward will be in contact with leachate that can lead to chemical degradation. In this paper, the antioxidant depletion rate from welding bead and HDPE GMB sheet away from welding immersed in MSW landfill simulation is examined over an 11-month period at 85°C, 75°C, and 65°C. Preliminary results shows that antioxidant depletion rate of the welding bead was faster than that for the GMB sheet material at lower temperatures (i.e. 65°C)

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 score0.001
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)0.0010.000

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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