A Nondestructive Longitudinal Laboratory Test Method for Detection of Incipient Ultrastructural Changes in Wood
Bibliographic record
Abstract
ABSTRACT The established methods for determining the effects of ultrastructural changes in structural wood members rely upon traditional, possibly outmoded, testing paradigms. These methods usually involve destructive testing of wood specimens that are exposed to environmental conditions infrequently experienced in buildings. Understanding how the ultrastructure changes with time within the same specimen is crucial for building practitioners in assessing risks to life-safety, assessing remaining service life of structural components, and aiding in the identification of mitigation or remediation measures. The primary agents causing ultrastructural modifications to wood are wood rotting basidiomycetes but may also include other biotic and abiotic agents; the methods contained herein should be applicable to all such longitudinal experiments. This article reviews existing literature on decay testing and validates a new method to assess longitudinal changes in mechanical properties with time using nondestructive test measures at relevant moisture contents. The validation testing shows this method has a good degree of repeatability and should permit the initial detection and monitoring of ultrastructure changes (e.g., decay). The method uses a repeatable, nondestructive four-point testing procedure for specimens controlled to specific moisture contents using energy dissipation as the salient performance metric. Recommendations are provided to refine this novel test method.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".