Estimating Maximum Water Absorption of Wood Fiber/Polymer Fluff Composites
Bibliographic record
Abstract
The objective of this study was to develop a model to estimate the maximum water absorption (MWA) of wood fiber/polymer fluff composites as a function of polymer fluff content and board density. Polymeric diphenylmethane diisocyanate (PMDI) resin bonded dry-process wood fiber/polymer fluff composites were used in this study. Six polymer fluff contents (0, 15, 30, 45, 60, and 100%) and four target oven-dry board densities in the range of 0.50-1.00 g/cm3 were studied. A water immersion test was conducted on these boards. The effect of irreversible thickness swelling after water immersion (TSi) on the estimation of the maximum water absorption was evaluated. It was shown that the irreversible thickness swelling had a quadratic relationship with polymer fluff content and a linear relationship with oven-dry board density. The TSi of the composites used in this study was in the range of only 0.04-4.20%, which was negligible in the estimation of maximum water absorption. The prediction of maximum water absorption from the MWA model developed in this study was over 95% accuracy for most of the specimens. The maximum water absorption had a linear relationship with the polymer fluff content and a reciprocal relationship with board density.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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 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".