Case-Study: Fully Prefabricated Wood Wall Connection to Improve Building Envelope and On-Site Efficiency
Bibliographic record
Abstract
As fully prefabricated wood walls (FPWW) are envisioned to increase building envelope performance, the junction between panels becomes crucial. Since FPWW restricts access to the inter-panel joints, it is preferable to generate an upstream mechanism to complete the joint automatically on-site. This study aimed to design a self-sealing joint for FPWW that would achieve high energy standards and accelerate on-site construction. Airtightness tests and thermal bridge assessments were conducted in the laboratory to compare the developed self-sealing joints with different sealing materials. These same tests were conducted on-site, in addition to observations of the assembly speed of conventional prefabricated walls and FPWW. Of all the materials tested, butyl tape showed the tightest connections. This material helps the joint developed to automatically seal adjacent walls spaced up to 7 mm apart. FPWW maximize the industrialization of conventional prefabricated walls by realizing the sealing details and the installation of doors, windows and exterior siding offsite. This way, FPWW could reduce the duration of a conventional single-family residential project. FPWW maximize quality control while reducing transportation costs associated with conventional modular solutions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".