Evaluating process of auto-hydrolysis prior to kraft pulping on production of chemical pulp for end used paper-grade products
Bibliographic record
Abstract
The objective of this work is to systematically evaluate the performance of the hydrolysis-based kraft pulping process and associated pulp and black liquor characteristics. Acacia wood chips were auto-hydrolyzed under various severities, then the hydrolyzed wood chips were kraft pulping. The results indicated that the yield of pulp significantly dropped with intensifying the auto-hydrolysis severity. Meanwhile, the removal rate of pentosan reached 98.6% in the screened pulp at the P-factor of 1 000. The fiber length, fines and fiber crimp of the screened pulp were not affected by the auto-hydrolysis treatment. Auto-hydrolyzed pulps deteriorated fibrillation and beating response of the pulp in a refining process. However, fiber length and fines changed obviously after beating treatment. After auto-hydrolysis, the tensile index of the paper matrices decreased, some particle substances were found on the surface of the pulp fiber, and the solid and organic content of the black liquor were improved.
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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 | 0.000 | 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 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".