Deresination options in sulphite pulping
Bibliographic record
Abstract
Three methods for improved deresination of sulphite pulps were evaluated, namely, alkaline washing, enzyme treatment, and pulp fractionation. Alkaline washing appears to come at a high cost, because caustic is expensive and affects cellulose chain length, as indicated by lower viscosity of the pulps. Thus this is not a viable option for pulps that are sensitive to changes in viscosity. Enzyme treatment did not completely degrade the glycerides under the mill conditions used. Fibre fractionation studies showed that the fines fractions contained 8 to 13 times more residual lipophilic extractives than the whole pulps. Removing this fraction, which represents only a small percentage of the whole pulp, could reduce by about a half the amount of lipophilic extractives in the remaining pulp. Thus pulp fractionation appears to be a viable option to achieve further deresination of sulphite pulps.
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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) | 0.000 | 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 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".