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Record W4220717405 · doi:10.3390/f13040523

Physical and Mechanical Properties of Oriented Strand Board Made from Eastern Canadian Softwood Species

2022· article· en· W4220717405 on OpenAlexafffundabout
Biaorong Zhuang, Alain Cloutier, Ahmed Koubaa

Bibliographic record

VenueForests · 2022
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSoftwoodOriented strand boardComposite materialMaterials scienceYoung's modulusFlexural strengthSwelling

Abstract

fetched live from OpenAlex

This study aims to investigate the feasibility of producing OSB from softwood species used in the Eastern Canadian softwood lumber industry in the context of the overcapacity of softwood chips traditionally produced for the pulp and paper industry. Balsam fir, black spruce, and jack pine logs were used to make 15 mm thick OSB panels with a target density of 600 kg/m3. The panels were manufactured at a temperature of 210 °C during a pressing cycle of 300 s. Strands with different thicknesses were used to obtain a constant specific surface of 6.7 m2/kg for the three species. The bending modulus of the rupture and modulus of elasticity, internal bond, and thickness swelling of the OSB panels were determined and compared to the CSA standard requirements. The species significantly affected the physical and mechanical properties of OSB. The bending properties of OSB decreased with an increase in the species wood density. The internal bond strength of OSB increased with the increase in species wood density. The panels made from softwood species showed physical and mechanical properties exceeding the standard requirements, except for high thickness swelling. The combination of softwood and aspen strands significantly improved the thickness swelling of softwood-based OSB. The reduction in the surface layer density could also be explored to reduce the thickness swelling of the OSB made from the softwoods considered in this study.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.993

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 head0.015
GPT teacher head0.175
Teacher spread0.160 · 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 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

Citations25
Published2022
Admission routes3
Has abstractyes

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