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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".