Insulating heritage mass masonry buildings from the interior: a best practice guide to mitigate risk of freeze-thaw damage
Bibliographic record
Abstract
Heritage buildings play a significant role in the Canadian government building stock; it is estimated that there are 1272 recognized federal heritage designated buildings in Canada, with 280 of these being classified as Federal Heritage Buildings. The majority of these heritage buildings are unlikely to have a building envelope which meets the thermal requirements of modern construction codes. The Government of Canada, through the Greening Government Strategy, has introduced increasingly ambitious greenhouse gas (GHG) emissions reduction targets for its real property portfolio. Introduced in 2017 and updated in 2020, the Greening Government Strategy commits the Government of Canada to reducing GHG emissions by 40% below 2005 levels by 2025, and by at least 90% below 2005 levels by 2050 (Government of Canada, 2021). Departments are expected to ensure that all major building retrofits, including heritage rehabilitation projects, prioritize GHG emission reduction and resiliency to climate change. For heritage buildings where the unique architectural features of the façade are to be conserved, achieving these ambitious GHG reduction requirements, as well as meeting modern thermal comfort requirements for building occupants, typically implies that insulation is required to be added to the interior of roofs, foundations and walls. However, it has been widely identified that for a heritage building, the addition of insulation on the interior of the building risks the exterior layers to be colder and wetter during the winter season. This can increase the risk to freeze thaw damage of heritage components in the envelope, thereby potentially risking the long term durability to heritage defining characteristics of the building.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.029 |
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".