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Record W2002583700 · doi:10.1002/app.33799

Surface properties of methyl methacrylate hardened hybrid poplar wood

2011· article· en· W2002583700 on OpenAlexaffabout
Ahmed Koubaa, WeiDan Ding, Abdelkader Chaala, Hassine Bouafif

Bibliographic record

VenueJournal of Applied Polymer Science · 2011
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsService de Recherche et d'EXpertise en Transformation des Produits ForestiersUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsMaterials scienceComposite materialHardening (computing)Methyl methacrylateScanning electron microscopeFourier transform infrared spectroscopyPolymerChemical engineeringMonomer

Abstract

fetched live from OpenAlex

Abstract The surface properties of fast‐growing poplar clones and their methyl methacrylate (MMA)‐hardened wood related to potential end uses were investigated. Samples from 24 trees of six hybrid poplar clones in one plantation in Quebec were hardened with MMA. The effects of MMA hardening on the density and surface properties were studied. Scanning electron microscopy and Fourier transform infrared analysis showed that filling the voids in the wood structure was the main hardening mechanism. The incorporation of the polymer increased the density of all of the poplar clones by 120–160%. The Janka hardness was found to be 2.5–4 times higher in the treated poplar wood than in the untreated poplar wood. The treated wood also exhibited superior abrasion resistance compared to the controls. The results indicate that hardening with MMA improved the surface properties and that the MMA‐hardened wood was comparable to natural hardwoods. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.030
GPT teacher head0.199
Teacher spread0.169 · 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 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

Citations26
Published2011
Admission routes2
Has abstractyes

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