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Record W4384697940 · doi:10.22215/etd/2023-15481

Testing the Applicability of Older Wood Taken from Fire-Damaged Buildings

2023· dissertation· en· W4384697940 on OpenAlexaffabout
Benjamin R. Hamilton

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsCarleton University
Fundersnot available
KeywordsReuseDeconstruction (building)EngineeringArchitectural engineeringFire testBending momentFire protectionForensic engineeringCivil engineeringBendingTest (biology)Structural engineeringWaste managementGeology

Abstract

fetched live from OpenAlex

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.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.223
Teacher spread0.201 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes2
Has abstractyes

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Same topicWood Treatment and PropertiesFrench-language works237,207