Investigation on the uniformity of high‐density polyethylene/wood fiber composites in a twin‐screw extruder
Bibliographic record
Abstract
Abstract Uniform dispersion of wood fiber in high‐density polyethylene can improve the mechanical properties and surface finish of the wood plastic composites. However, it is difficult to achieve uniform dispersion when the wood content is high, due to its low thermal stability, incompatibility with polymer, and affinity for agglomeration. This work was undertaken to improve the uniformity of high‐density polyethylene/wood composites by designing screw configurations, optimizing screw speed, and altering material compositions. The rheological properties and scanning electron microscope micrograph were used to characterize the uniformity. The results showed that the medium dispersive and distributive mixing, medium screw speed, and lubricant were all beneficial in improving uniformity. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".