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Dimensional changes of cross-laminated timber basement walls under ambient humidity variation

2025· article· en· W4410024853 on OpenAlexaffabout
Fernanda Bezerra Tomaduci Imamura, Yuxiang Chen, Lijun Deng, Ying Hei Chui

Bibliographic record

VenueBioResources · 2025
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceCross laminated timberBasementHumidityComposite materialVariation (astronomy)Structural engineeringCivil engineeringMeteorologyEngineeringGeography

Abstract

fetched live from OpenAlex

Advancements in cross-laminated timber (CLT) applications have introduced the potential to use it as an alternative to reinforced concrete in basement construction. Understanding dimensional stability is crucial to ensure the reliability and safety of CLT in below-grade environments. An experimental CLT basement was constructed in Edmonton, Canada, and monitored over a period of two years. Field measurements were analyzed to estimate the dimensional changes and understand the deformation modes of the CLT panels resulting from changes in boundary conditions. A supporting laboratory experiment with specimens made from single pieces of dimensional lumber was conducted to establish a basis for comparing field-measured dimensional changes in CLT and determining the effects of cross-lamination on swelling and shrinkage coefficients. The average swelling and shrinkage coefficients calculated for CLT were approximately twice as large as the longitudinal and 20 times smaller than the transverse coefficients obtained from the laboratory experiments on solid wood specimens, indicating the influence of cross-lamination on these coefficients. Four deformation modes were identified based on measurements from field-installed strain gauges. The study provides new insights into the impact of water ingress on the swelling coefficient and the effects of different drying conditions on the shrinkage coefficients of CLT.

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 score0.106
Threshold uncertainty score0.511

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 head0.244
Teacher spread0.229 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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