Understanding the limits of a screening operation. Part 1: Characterization of screen plugging
Bibliographic record
Abstract
Pressure screening is a critical step in the production of high-quality paper. In efforts to meet sustainable market demands, mill operators are forced to push the limits of screening operation to the point where plugging becomes a recurrent issue. This two-part study provides insights into the limits of screening operations. In the first part, some published imaging data was analyzed to delve into the plugging mechanisms. The observed hysteresis and intermittency were measured by image processing techniques, which revealed that an intermittent behavior of plug-and-release events is intensified as permanent, stable plugs start to form. The intermittency was characterized as changes in the distribution of open area fluctuation peaks. Thus, the kurtosis of the fluctuation peak distribution is proposed as a metric for a plugging soft-sensor. In part 2 of this investigation, the limits of screening operation were characterized by performing a series of screening trials. The utility of the soft-sensor metric for plugging was assessed with the pressure fluctuation data.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".