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Record W6986302440

An overview of cross-laminated timber in North America

2018· article· en· W6986302440 on OpenAlexaboutno aff

Bibliographic record

VenueCivil War Book Review · 2018
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)LoggingSustainable developmentSustainable forest managementSustainabilityCross laminated timber
DOInot available

Abstract

fetched live from OpenAlex

Mass timber products, wood-based engineered construction materials, are becoming widely prevalent in the design and construction sector. Being a cost-effective, carbon efficient, durable, and sustainable building option, mass timber construction has already had a profound impact in residential and non-residential applications in Europe, and it has been reaching new heights in Canada, and recently gaining momentum in the United States. All architects, builders, designers, and forestry communities including the forest product industry, landowners, rural communities, and environmentalists have reason to be excited about these promising new timber products. Mass timber products are envisioned as substitutes for traditional building materials like concrete, masonry, and steel. The most widespread mass timber product is cross-laminated timber (CLT), which was first introduced in the early 1990s in Austria and Germany. It is currently on a rapid upward trajectory in North America. The main purpose of this article is to provide a brief overview of CLT and its market status and future prospects in North America.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.005

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 head0.035
GPT teacher head0.299
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2018
Admission routes1
Has abstractyes

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