Full-Scale Comparison of Two Envelope Systems for Lightweight Wooden Framing in Cold Climates
Bibliographic record
Abstract
Residential homes and apartments’ cooling and heating needs account for 63% of total building energy consumption. Improvements in the properties of building envelopes are among the best ways to reduce their energy consumption. The project’s general objective was to compare the performance of externally insulated and traditional envelopes of light wooden frame buildings at full scale. Two houses were constructed and equipped with relative humidity sensors and temperature probes to assess the physical properties of the building envelope. The first house was built according to the conventional method (insulation between the studs), and the second house was built according to the method with the insulation outside the wall (also known as the perfect wall). The results showed that external insulation effectively mitigates internal condensation risks by relocating dew points to the exterior surface, thereby enhancing structural durability and thermal stability. Thermographic imaging confirmed reduced thermal bridging and improved thermal performance in the externally insulated walls. Overall, this study supports, with a full-scale experiment, the adoption of external insulation as a viable strategy for enhancing energy efficiency, thermal comfort, and durability in residential buildings.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".