Comparison of P-RC APMP Pulping Performances of Wood Chips Stored in Different Conditions
Bibliographic record
Abstract
Eucalyptus urophylla×grandis woodchips stored in different conditions were pulped by using the typical P-RC APMP process. The influences of various storage conditions on its P-RC APMP pulping performance were investigated. A fix pulping conditions such as H2O2 dosage 6.0% and NaOH dosage 4.0% were applied,pulping performance varied with the changing of storage conditions of the Eucalypt chips,the results showed that,at a given Canadian Standard Freeness of 300 mL,comparing to fresh eucalyptus woodchips,3.0% and 12.5% higher refining energies were consumed by woodchips sealed in plastic bags and kept in a cool room and air dried woodchips after one year storage,respectively,and pulp yields decreased by 6.8 and 2.9 points,pulp tensile strengths decreased by 49% and 30%,pulp brightness lost about 5.1 and 5.7 points respectively,and the pollution loads of their pulping effluent were lower than those of fresh wood chips.
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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".