Prediction of moisture response of wood frame walls using IRC's advanced hygrothermal model (hygIRC)
Bibliographic record
Abstract
The main objective of this paper is to highlight the research works being carried out on the hygrothermal behaviour of building materials and wall systems at the National Research Council (NRC) Canada. The paper depicts selected results obtained from parametric studies conducted on wood frame stucco walls commonly used in Canadian climatic conditions, using hygIRC, an advanced hygrothermal modelling tool developed over the years at the Institute for Research in Construction (IRC), NRC Canada. Theassumed wall configurations, environmental conditions and material properties used in the study and the rationale behind such assumptions are highlighted. The drying potential of the composite wall systems and drying characteristics of various individual wall components are analysed. A number of parameters which influence the moisture movement to and from the wall have been selected for this study and they are : (1)Presence of ventilation cavity behind the cladding, (2) Size of the vent cavity, (3) Variation of external relative humidity (RH), and (4) Solar radiation on the exterior face of the wall. The parametric studies, based on simulation results, call upon the urgent need to verify these observations by conducting closely monitored field tests.
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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 | 0.001 |
| 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 | 0.001 | 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".