Bibliographic record
Abstract
Achieving energy efficiency with thermal control in residential houses is crucial for the reduction in the energy consumption. Timber framing as the main structural component in the building envelope has a big influence on the effective R-value depending on the framing percentage, and this impacts the overall thermal performance of the building. This project, carried out in Canada, measured the typical framing percentages that are achieved in residential construction sites and compares them with code recommendations. It provides framing factors measured for 17 residential units under construction including detached, row-housing, and semi-detach dwelling units in three different locations in the Toronto area. Detailed on site measurements provide data for numerical calculation to evaluate the amount of framing within external walls, ceilings, and exposed floors. The overall framing factor calculated for each dwelling is found to exceed the recommended percentage by Canadian Model National Energy code for dwellings and ASHRAE Handbook- Fundamental. The research considers the impact that additional regular thermal bridging from the increased framing percentage will have on the effective R-value, and consequently, the impact on thermal effectiveness of the envelope leading to an increase in the overall energy above the expectations of the codes and standards.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".