Optimum Refining of TMP Pulp by Fractionation after the First Refining Stage
Why this work is in the frame
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Bibliographic record
Abstract
The pulp used in this work was sampled after the first TMP refining stage of a Canadian newsprint mill. This pulp was fractionated with a pressure screen into multiple fractions of long and fine fibres. We refined the fractions at high consistency in one or two stages and at low consistency. We recombined the refined fractions together to recreate the initial pulp. The initial pulp, itself refined at high consistency as in a typical TMP process, was compared with the recombined pulps. It appears that refining consistency has a strong effect on the quality of the recombined pulp and that it is possible to optimize the pulp quality with this kind of treatment. This optimization is closely related with the fractionation efficiency. The best fractionation process is a pressure screen cascade using baskets with very small apertures. This process is very efficient in separating fibres by length but also able to separate fibres on the basis of wall thickness, leading to fractions of long fibres enriched with latewood and fractions of short fibres enriched with earlywood.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it