Hygrothermal Performance Assessment of Stucco-Clad Wood Frame Walls Having Vented and Ventilated Drainage Cavities
Bibliographic record
Abstract
The long-term performance in respect to moisture management within any wood frame wall assembly depends on the hygrothermal response of the wall to local climate moisture loads. Estimating the wood moisture content, temperature, and time of exposure to conditions suitable for the onset, growth, and propagation of mold or rot are critical parameters when assessing the longevity of wood frame structures. A number of approaches for assessing the vulnerability of wood frame structures to deterioration have been developed in recent years; one of which has been used by NRC-Construction for evaluating the performance of wall assemblies based on the results from hygrothermal simulation. In this paper, an example of the use of this approach for the assessment of a stucco-clad wall incorporating drainage cavities is described as is the use of a mold index to capture the risk of the formation of mold in walls. An example is given in assessing the moisture management of a stucco-clad wood frame wall incorporating vented and ventilated drainage cavities for three Canadian locations.
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 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 | 0.000 |
| 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 | 0.001 | 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 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".