Bibliographic record
Abstract
Wood has been discovered as an important construction material since prehistoric time. As time goes, the technology of wood frame construction is developed. Today, it is widely used in many North American and European countries. Wood is a much more sustainable construction material than steel or concrete. During its production, less green house gases are produced. Wood is also a very durable material. Some old wood frame buildings are still used. History has proved the durability and strength of wood structures. In the recent days, in order to achieve stronger and more durable building structures, wooden building components production technology and wood framing technology are further developed. As a result of these developments, I-joists, metal plate connected wood trusses, structural composite lumber, platform framing and plank and beam framing are widely applied in either individual house construction or heavy industrial construction. The purpose of this paper is to provide a detailed explanation of how wood can be a good material for building homes. This paper introduces the methods of moisture and termite protection for wood material, wood and concrete foundation construction, as well as the different types of wood frame constructions and construction processing details. This paper may help to open markets by changing the mind of people who are not used building home with wood to accept wood frame building.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".