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Record W1973870941 · doi:10.1515/hf.2010.112

Viscoelasticity of aspen wood strands during hot pressing: Experimentation and modeling

2010· article· en· W1973870941 on OpenAlexafffund
Cheng Zhou, Chunping Dai, Gregory D. Smith

Bibliographic record

VenueHolzforschung · 2010
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsFPInnovationsUniversity of British Columbia
FundersFPInnovations
KeywordsViscoelasticityStress relaxationMaterials scienceComposite materialComposite numberRelaxation (psychology)Consolidation (business)Hot pressingPressingStress (linguistics)SoftwoodCreep

Abstract

fetched live from OpenAlex

Abstract To improve the fundamental understanding of wood composite consolidation, the viscoelastic behavior of aspen wood strands is experimentally investigated for a range of temperatures (20–200°C) and moisture contents (0–15%). The results show that the strand stress relaxation modulus and time follows a linear relationship in a log-log plot. The strand stress relaxation rate is highly dependent on the imposed strain levels and the environmental conditions. A model for predicting the stress relaxation of wood strands is developed and compared with the experimental results. It will be useful to further predict the stress relaxation response of strand-based wood composite mats during hot pressing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.389

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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

Citations4
Published2010
Admission routes2
Has abstractyes

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