Evaluating the Future Moisture Performance of the Stucco-Clad Wall Assembly in Selected Canadian Cities
Bibliographic record
Abstract
Due to climate change, it is expected that the amount of precipitation in most parts of Canada will increase in the coming decades. Consequently, the building envelope exposed to such climate could experience a higher moisture load than in the past, which could have a negative impact on its performance in the long run. The stucco-clad wall assembly, which has been widely employed in the construction of low-rise residential buildings throughout Canada may not be adequately designed to be resilient to the future climate. Thus, in the study described in this paper, the future moisture performance of the stucco-clad wall assembly located in two Canadian cities with different levels of moisture load, i.e., Vancouver and Calgary, subjected to projected future climate is investigated. The analysis includes two phases: conducting watertightness for a full-scale stucco wall specimen to determine the relationship between the climate data and the moisture load in the wall assembly and implementing hygrothermal simulations using the relationship obtained from the watertightness test for the performance assessment. Mould growth index at the exterior surface of the oriented strand board of stucco-clad wall assembly for the historical and projected future time periods is compared and discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".