MétaCan
Menu
Back to cohort
Record W2167405038 · doi:10.1002/vnl.20025

Thirty‐year durability of a 20‐mil PVC geomembrane

2004· article· en· W2167405038 on OpenAlexaff
Erik Newman, T. D. Stark, F. P. Rohe, P. W. Diebel

Bibliographic record

VenueJournal of Vinyl and Additive Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsCanadian General-Tower (Canada)
Fundersnot available
KeywordsGeomembraneDurabilityClearanceMoistureGeotechnical engineeringEnvironmental scienceFish <Actinopterygii>Water contentMaterials sciencePulp and paper industryComposite materialGeologyEngineeringFisheryBiology

Abstract

fetched live from OpenAlex

Abstract In 1971, twenty circular aquaculture ponds were constructed for the W. K. Kellogg Biological Research Station in Hickory Corners, Michigan. The 30.5‐m‐diameter research ponds were lined using a 0.51‐mm‐thick fish‐grade PVC geomembrane. Over the years the ponds became congested with dense, persistent stands of cattails, trees, and other vegetation, which required the ponds to be cleared and relined in September 2000 in order to allow the initiation of new experiments. The lack of holes in the exhumed geomembrane suggests that it resisted biological attack from microorganisms and also root penetration. Laboratory testing shows that the tensile behavior of the nearly 30‐year‐old PVC geomembrane is within current specifications for new 0.51‐mm‐thick PVC geomembranes. Test results also indicate that performing laboratory tests at in‐situ moisture conditions provides a better estimate of the field properties of PVC geomembranes than desiccating the material prior to testing, as is required by ASTM Standard Test Methods. J. Vinyl Addit. Technol. 10:168–173, 2004. © 2004 Society of Plastics Engineers.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.003
GPT teacher head0.182
Teacher spread0.179 · 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

Citations13
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vinyl and Additive TechnologySame topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207