Swelling Properties of Hardwoods as Affected by their Extraneous Substances, Wood Density, and Interlocked Grain
Bibliographic record
Abstract
Samples of nine tropical hardwoods from Peru and sugar maple wood from Quebec were selected to perform moisture sorption tests associated with swelling tests using a multiple step procedure at 25°C. Cold-water and hot-water extractives, sequential cyclohexane, acetone, and methanol extracts, ash content, wood density, and interlocked grain also were evaluated on matched samples. Swelling properties were highly variable within and among wood species. The wood density corrected for the extraneous substances was the most significant variable positively affecting the transverse and volumetric swelling of tropical hardwoods. Sequential extraction with organic solvents was the most suitable method for evaluating the effect of extractives on swelling properties of tropical hardwoods. The extractives soluble in cyclohexane were the more accessible, but they virtually did not contribute to wood swelling. The substances dissolved in acetone appeared to be located within cell walls. After wood density, these compounds were the most significant variable negatively affecting the radial swelling. The substances dissolved in methanol were located within cell walls. After wood density, this extracted fraction was the most significant variable negatively affecting the tangential swelling. The acetone and methanol extracted fractions positively affected the dimensional stability of tropical hardwoods. Finally, the effect of the interlocked grain on swelling was only indirect given that this grain pattern reduces the equilibrium moisture content.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".