MétaCan
Menu
Back to cohort
Record W2560976564 · doi:10.1080/20426445.2016.1204514

Reducing the thickness swelling of a model wood composite by creating a three-dimensional adhesive network

2016· article· en· W2560976564 on OpenAlexafffund
Wenchang He, Philip D. Evans

Bibliographic record

VenueInternational Wood Products Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
FundersChina Scholarship CouncilFPInnovationsBangor UniversityAustralian National University
KeywordsSwellingComposite materialAdhesiveMaterials scienceComposite numberPolyurethaneVeneerLayer (electronics)

Abstract

fetched live from OpenAlex

Wood composites undergo irreversible thickness swelling and strength losses when they are exposed to water, and there is strong interest in developing cost-effective solutions to this problem. We hypothesised that a composite with more adhesive connections in the Z-(thickness)-direction would be less susceptible to thickness swelling. We test this hypothesis using a model composite consisting of perforated veneer that allowed a polyurethane adhesive to create cross-links in the Z-direction. Model composite specimens were submerged in water, air-dried and their irreversible thickness swelling and surface topography were measured. Z-direction cross-links significantly reduced the thickness swelling of both yellow cedar and white spruce specimens, but the inter-connected adhesive network retained its integrity better in spruce than in cedar specimens. Further research is needed to develop practical ways of creating Z-direction cross-links in composites that resemble commercial products, and also to evaluate the effects they have on the mechanical properties of composites.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.466

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 integrity0.0000.000
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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueInternational Wood Products JournalSame topicWood Treatment and PropertiesFrench-language works237,207