Influence of wood fiber size on extrusion foaming of wood fiber/HDPE composites
Bibliographic record
Abstract
Abstract Foaming of wood fiber/plastic composites (WPC) with a fine‐celled structure can offer benefits such as improved ductility and impact strength, lowered material cost, and lowered weight, which can enhance their utility in many applications. Although a great deal of attention is now being focused on these composites in the scientific literature, there are still numerous aspects of WPC processing that need elucidation. In this context, this article investigates the effects of wood fiber (WF) size on fine‐celled extrusion foaming of WPC in terms of cell size, cell size distribution, and foam density. The effects of WF size and coupling agent content on the viscosity of WPC are also investigated. The experimental results revealed that the small‐sized WF provides a better cell morphology, a smaller cell size, and a better cell uniformity in WPC foams. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008
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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) | 0.002 | 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".