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Record W4396817342 · doi:10.35483/acsa.am.112.7

Seven Generations for Wood

2024· article· en· W4396817342 on OpenAlexaboutno aff
AnnaLisa Meyboom, Kaia Nielson-Roine

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsLaminated veneer lumberDemolitionReuseOriented strand boardEngineered woodWaste managementDeconstruction (building)Construction wasteEngineeringEnvironmental scienceCivil engineeringMaterials scienceVeneerComposite material

Abstract

fetched live from OpenAlex

While there is much interest from both the construction industry and government to develop new pathways for salvaging and recycling wood products there has not been significant movement in imple-menting large scale wood recycling initiatives. Despite having one of the strictest recycling programs in the country, the city of Vancouver still a significant construction and demolition (C&D) waste problem. The Zero Waste Policies from Metro Vancouver Municipalities has allowed 78% (1.3 million tonnes) of all waste streams to be diverted from regional landfills, but wood C&D waste (31% of all C&D waste) still largely ends up in the landfill.1,2 Given that about 57% of new buildings in Vancouver are light-wood type buildings and the Vancouver Landfill is slated to be decommissioned in 2037, the city needs a strategy to divert these large volumes of wood from being landfilled.3 This proj-ect presents a method to recycle salvaged wood from deconstructed light-wood buildings and use those materials in new deconstructa-ble assemblies. Common wood waste such as dimensional lumber, plywood, oriented strand board (OSB), laminated strand lumber (LSL),and laminated veneer lumber(LVL) can be recycled into new wood products including finger-jointed lumber, OSB, OSB/LSL or Plywood/LVL crosslam tiles, and wood fibre insulation. Typical light- wood frame construction can then be altered to incorporate these recycled materials and to facilitate deconstruction and further reuse. This project proposes that with proper recycling infrastructure and construction practices the value of wood extracted from the urban environment can be maintained across multiple generations of build-ings creating a true circular economy of wood materials.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.311
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0060.005
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.3110.133

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 head0.019
GPT teacher head0.215
Teacher spread0.195 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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