Bibliographic record
Abstract
While the thermal performance of a roof insulation is an important metric to consider when selecting and specifying products, several other material characteristics need to be evaluated, such as compressive strength, fire resistance, moisture absorption resistance, dimensional stability, and substrate durability. Roofing insulation manufacturers provide laboratory test results for these and other material characteristics. However, limited information is available for the performance of aged in situ materials. This lack of information can potentially lead to issues because the performance of aged, installed material may not match the performance at the time of its manufacturing, and more importantly may no longer meet the project specifications. The reliability of a product's long-term durability is critical to the performance of the complete assembly. This paper will discuss the need to compare actual in-service performance characteristics of aged material to the performance of new as-manufactured material. This type of information can help design professionals and owners make an informed decision about the material's suitability and longevity. To demonstrate this type of evaluation, this paper presents two case studies that reviewed and compared the aged in situ performance of stone wool insulation to new as-manufactured data. The case studies focused on multiple performance metrics tested per ASTM standard test methods. The stone wool insulation was installed in two different roofs and had been in place for 10 years at two separate sites in southern Canada. Multiple insulation specimens were extracted as representative samples for testing. The study reviewed the moisture content, compressive strength, adhesive/cohesive strength, and peel strength of the insulation. The results are compared to newly manufactured specimens to evaluate if or how the insulation's performance has changed over the 10 years.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".