Bibliographic record
Abstract
Adhesives used in engineered wood products, such as I-joists and laminated veneer lumber (LVL), manufactured in North America are required to meet specific requirements of adhesive standards, such as ASTM D2559 in the U.S. and CSA Standards for Wood Adhesives O112 Series in Canada. However, these standards do not address the adhesive performance at temperatures above 180°C (356°F) even though the general expectation has been that the adhesives used in engineered wood products will not lose the bond strength more than wood does when exposed to elevated temperatures in unprotected assemblies, such as in most residential construction in North America. However, there is no existing standard in the world that addresses the performance of structural adhesives at an elevated temperature near unpiloted wood ignition. In lack of an international standard, a task committee was formed in 2004 by the engineered products industry in North America to develop an industry standard for the evaluation of adhesive performance at elevated temperatures with input from many key adhesive suppliers to the industry. Through coordinated efforts, an industry standard was adopted by the engineered wood products industry in March 2005. Test data suggests that this standard can be used to screen out those adhesives that significantly lose adhesive bond strength at the temperature near the wood ignition temperature. The test method given in the industry standard was submitted to the ASTM D14 Committee on Adhesives for adoption in July 2005 and was approved for publication in April 2006 as ASTM D7247, Standard Test Method for Evaluating the Shear Strength of Adhesive Bonds in Laminated Wood Products at Elevated Temperatures. This paper presents the background information used to support the test method and the next step for implementation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.694 | 0.513 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".