Fibre Length Fractionation Caused by Pulp Screening, Slotted Screen Plates
Bibliographic record
Abstract
Fibre fractionation and selective processing of each fraction produces higher quality, more uniform pulp. Engineering efficient pressure screening systems requires appropriate performance equations. This study extends previous screening performance equations by comparing pilot screening tri- als with a mechanistic model of fibre passage through the screen to predict the effects of reject rate, slot width, contour type, and slot velocity on frac- tionation and consistency changes. Smooth-hole screen plates were found to fractionate more efficiently than contour-slot screen plates. Fibre passage through slotted screen plates was strongly dependent on the fluid velocity passing through the slot, while smooth-hole apertures were approx- imately independent of aperture fluid velocity. The maximum fractionation efficiency for slotted plates occurred at slot velocities between 0.5 and 1.0 m/s. The maximum fractionation efficiency for both slot and hole plates occurs at a reject ratio that results in a reject thickening factor greater than two.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".