MétaCan
Menu
Back to cohort
Record W7057012423

Influencer perceptions of cross-laminated timber in the U.S. South

2019· article· en· W7057012423 on OpenAlexaboutno aff

Bibliographic record

VenueCivil War Book Review · 2019
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsConsumption (sociology)Production (economics)LoggingSustainable developmentConstruction industry
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. Likewise, it has been reaching new heights in Canada, and is recently gaining momentum in the United States. Envisioned as a substitute for the traditional building materials of concrete, masonry, and steel, all forestry stakeholders have reason to be excited about these new timber products. While the Pacific Northwest has been leading efforts in both production and consumption of mass timber products for the past several years, mass timber is still relatively new to the Southern U.S. The main purpose of this article is to provide a brief overview of cross-laminated timber and its market status in the U.S. and the future prospect in the U.S. South.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCivil War Book ReviewSame topicParticle accelerators and beam dynamicsFrench-language works237,207