Testing the Applicability of Older Wood Taken from Fire-Damaged Buildings
Bibliographic record
Abstract
Given the increasing need to reuse, reduce, and recycle in a sustainable economy, this thesis examines century-old, lightly fire-damaged wood to test if it is reusable in modern projects.It researches the economics of deconstruction and reuse of structural and cosmetic wood in heritage buildings and new builds.Samples were retrieved from older fire-damaged buildings and tested for their bending strength using a Universal Testing Device and the American Standard Testing Method calculations.Using the test results, the bending moment was found and compared to design calculations in the Canadian Wood Design Manual.The best-performing samples were boards from an over 100-year-old property that suffered a fire in 2021.Modern standards rate these samples as non-structural (cosmetic); however, the material could be reused, particularly where the goal is preserving heritage elements.Comparing the samples bending moment to the Canadian Wood Design Manual shows the potential use of older fire-damaged wood.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".