Evaluation of the Thermal and Structural Performance of Potential Energy Efficient Wall Systems for Mid-Rise Wood-Frame Buildings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Approximately 30% of energy use in Canada is consumed in buildings. The largest component of this energy consumption in multifamily residential buildings is space heating. One of the primary functions of building enclosure is reducing space-heating energy. Although heat flow cannot be completely prevented, it can be controlled to reduce energy consumption, create a sustainable environment, and implement indoor human comfort. However, this can be achieved by constructing a thermally resistant building enclosure. This study aims at developing and evaluating some innovative potential energy-efficient wall systems for mid-rise, wood- frame buildings in terms of their thermal and structural performances. Regarding the thermal resistance performance, four wall systems were developed, installed in a full-scale testing house, and examined on a long-term period along with a baseline wall system. The selection of the wall systems was based on specific considerations: current practice, preliminary structural analysis, prefabricability, and expected energy efficiency. Several sensors were installed at each wall system: heat flux, thermocouple and humidity sensors. The results from the thermal analysis and the structural tests provide useful directions toward future development of energy-efficient wall systems.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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) | 0.000 | 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 it