The influence of lignin chemistry and ultrastructure on the pulping efficiency of clonal aspen (Populus tremuloides Michx.)
Bibliographic record
Abstract
Abstract The variation in wood chemistry among aspen clones of similar age, harvested from a common site in northern British Columbia, Canada, was evaluated. The aspen clones were evaluated for ease of chemical pulping and differed by as much as 4.5% in pulp yield at a common H-factor. The results demonstrate both the need for understanding the resource and the substantial opportunities that exists in natural population of trees for selecting superior clones for reforestation and afforestation. The syringyl/guaiacyl ratio, as determined by nitrobenzene oxidation, was directly correlated with the ease of pulping, whereas thioacidolysis results were not as predictive. These results were supported by quantitative NMR analysis, which demonstrated differences in the amount of β-O-4/Ar groups and the degree of condensation. Furthermore, it was shown that, in addition to total lignin content, which differed by as much as 5%, structural differences in the lignin may influence pulping efficacy. Among the other parameters evaluated, the distribution of molecular mass and methoxyl content is relevant for pulping. More specifically, among the fractions isolated in this study [milled wood lignin (MWL), MWELsol, and MWELinsol], the insoluble fraction was the most indicative of the pulping efficiency.
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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) | 0.000 | 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 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".