Treatments to Improve the Dimensional Stability of Refractory Woods
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
Changes in wood moisture content below the fiber saturation point result in dimensional changes. This creates stresses in the wood which may manifest as checks and cracks. These impact the appearance of wood products and limit the use of wood in some applications. Many chemical treatments to improve wood stability have been developed, though they are generally only applied to wood species with high permeability. The present work investigates several commercial-scale and lab-scale modification treatments for their ability to stabilize white spruce, a refractory softwood. Modified white spruce was evaluated for weight percent gain after treatment, dimensional stability in humidity and immersion, total color change after accelerated UV exposure, and coating adhesion before and after UV exposure. All treatments improved stability with anti-swelling efficiency between 11 and 59%. However, these treatments were also associated with increased color change after accelerated UV exposure and poorer adhesion of a water-based stain. The improvements in dimensional stability were generally lower than those reported for permeable species, and it’s unclear if they would meet end-user expectations. Additional research is needed to further enhance performance and to overcome the resulting photostability and coating adhesion challenges.
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 | 0.001 | 0.000 |
| 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 | 0.014 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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