Densification of wood veneers combined with oil-heat treatment. Part 1: Dimensional stability
Bibliographic record
Abstract
is often a problem due to compression recovery. Alternatively, oil-heat treatment (OHT) improves wood dimensional stability and enhances resistance to biological attack. This study examined combined wood densification and OHT. Large wood veneer 700 700 mm specimens prepared with aspen (Populus tremuloides) were densified using heat, steam, and pressure at 160ºC, 180ºC, and 200°C, respectively. OHT at 180, 200ºC, and 220ºC for 1, 2, and 3h was then applied to the densified veneers. Results show that OHT efficiently improved dimensional stability and reduced compression set recovery. OHT temperature and duration markedly influenced the reduction of compression set recovery: the higher the OHT temperature and duration, the lower the recovery. Less than 5% recovery was obtained under various OHT conditions, and almost 0% recovery under some OHT conditions. Radial and tangential swellings of densified veneers were reduced dramatically. Compared to OHT duration, OHT temperature had a pronounced higher impact on radial and tangential swelling. Irreversible swelling (IS) in the compression direction of densified veneers decreased after OHT, particularly with high temperature and long duration, and anti-swelling efficiency (ASE) in the compression direction improved significantly.
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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) | 0.000 | 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) | 0.001 | 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 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".