Prospects for Appearance Wood Products Ecodesign in the Context of Nonresidential Applications
Bibliographic record
Abstract
Abstract As environmental awareness grows, societal demand for more environmentally friendly products increases. Demand for environmental responsibility also reached the building material and construction sector. Green building has become more widespread over the past decade and can be considered a challenge for specifiers and building products manufacturers. Ecodesign, an application of the sustainable development concept, is one of the available tools to address this challenge. This article aims at proposing an ecodesign pathway for appearance wood products in the nonresidential building sector. Through extrapolating results from a previous interior wood door case study, it has been possible to obtain environmental profiles for the main segments of the appearance wood products family for nonresidential buildings. These profiles have allowed devising ecodesign solutions. Results show that for this whole family of products, raw materials are what cause the most environmental impacts, followed by shipping and end-of-life stages. Product component weight tends also to influence the environmental profile. Ecodesign solutions for composite-based products are strongly related to decreasing the composite component weight by design and remanufacturing. For solid wood–based products, ecodesign can be approached through remanufacturing or reclaiming, using locally certified sustainable wood. The use of hardwood waste may be available for energy purposes, but this may not be as relevant as reuse and recycle in the context of the province of Quebec energy grid mix.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".