A Moisture index approach to characterizing climates for moisture management of building envelopes
Bibliographic record
Abstract
Premature failures of building envelopes in some North American locations appear to be climate related. An IRC-led research consortium called MEWS (Moisture Management of Exterior Wall Systems) developed a method using hygrothermal modelling to identify locations where walls may experience moisture related problems. The method classifies climates by a Moisture Index (MI) based on wetting and drying potentials. Responses of various wall systems to the climatic inputs of Moisture Reference Years (MRY, selected according to their MI) were examined for seven North American locations spanning the MI range of climate severity. The study linked the likelihood of failure to construction deficiencies allowing excessive amounts of rain into the wall, and generally confirmed a direct relationship between hygrothermal response and MI.Application of MI and MRY did, however, reveal anomalies for some climates. MI can post warning flags, but hygrothermal modelling is required to explore potential problems in depth.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".