Bibliographic record
Abstract
The main purpose of this study was to determine the effect of contour height on the passage ratio of pulp through screen apertures, and determine which operating variable has the greatest affect on screen performance. In addition, a freeness model was to be developed, in hopes of helping to predict the freeness drop between feed and accepts. The study was conducted at The University of British Columbia (UBC) using a laboratory scale pressure screen. Slot velocity, feed consistency and contour height were the changing variables. Samples were collected from which passage ratio, freeness, fibre length and coarseness were determined. From the studies conducted it was found that slot velocity had the greatest influence on the screen operation. As the slot velocity increased a greater force was applied to the fibre to help push it through the screen aperture. However, this increase in slot velocity decreases the fractionation ability (separation of fibres into different lengths) of the screen. The second most important variable was the contour height. The main function of the contour height is to disrupt the flow of thick stock at the wall of the screen and allow for unhindered movement of fibre to the screen wall. The greater the contour height is, the greater the passage ratio (pulp fibre passing through screen). However, there is a decrease in fractionation. The third most important factor was the feed consistency. At low feed consistencies there is less crowding in the screen. Less crowding leads to more loosely-formed flocs, which are easier for the contour height and the rotor to dissipate and thus leads to unhindered movement. Thicker feed stock has a negative effect on passage A Freeness model was developed that showed that freeness had a power law relationship to passage ratio. The passage ratio was raised to a constant B, which is a function of the contour height and the feed consistency.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".