Benchmarking of the advanced hygrothermal model hygIRC: large scale drying experiment of the mid-rise wood frame assembly: report to Research Consortium for Wood and Wood-Hybrid Mid-Rise Buildings
Bibliographic record
Abstract
Constructing mid-rise wood-frame buildings will extend the exposure of the structural wood components to moisture and its effects during the construction phase, unless additional measures are implemented to prevent this from occurring. This means that the wood-based components of the walls will be more exposed to wind-driven rain. Designers should consider these effects when designing and specifying components and systems. A good understanding of material behaviour will significantly minimize the effects of moisture on the building when constructed. However, during construction phase, it is important to prevent the wood studs and wood panels from exposure to moisture for prolonged periods. For example, moisture can be stored in the building envelope components during the construction process. The wood studs can be wet during the construction, and not dry sufficiently before the interior finish is installed and painted. The building materials can get wet during construction due to rain, or by lying on the damp ground. The question to be answered in this report is “how long does the high moisture content of the wood-based elements would take in order to be less than the acceptable limit to enclose and finish the wall (19% moisture content) so as to minimize the risk of biological damage to the wood structure? Furthermore, this report will focus on an experiment of drying potential of an insulated wood-frame wall with spray-in place foam and with initially wet wood studs.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".