Understanding the limits of screening operation. Part 2: Characterizing the operational window
Bibliographic record
Abstract
The limits of the pulp screening operation can be defined as the maximum throughput before the apertures start to plug permanently. This two-part article sought insights into the limits of screening operation. In part two, the operational window of the screen was characterized by performing a series of screening trials with different pulp furnishes, where the plugging point was conventionally measured with the pressure signal. The limits of operation, given by a slot velocity and rotor speed contour, showed a robust linear relationship at the point of plugging, which depended on the ratio of the fibre length to aperture size. For size ratios less than 1.5, the screen did not plug under the conditions tested. In addition, the plugging detection tool was conceptualized in part one based on the kurtosis of the distribution of fluctuation peaks, and it was employed here. Effectively, deviations from the Gaussian distribution of the pressure fluctuation peaks signal the onset of screen plugging. Thus, the utility of this tool was confirmed for detecting plugs using readily available pressure fluctuation data in pilot-scale screening operations.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".