Quality Pulp from Mixed Softwoods as an Added Value Coproduct of a Biorefinery
Bibliographic record
Abstract
Increasing prices for biomass and growing competition generated by the emerging biofuels sector will require drastic changes in current methods used for the transformation of lignocellulosic biomass to achieve profitability. In this work, a methodology known as “feedstock impregnation rapid and sequential steam treatment” (FIRSST) was used for the production of pulp from mixed softwoods. This method allows the isolation of the extractives, hemicelluloses, lignin, and most significantly, the cellulose fiber from the feedstock. The isolation of the cellulosic pulp was done via two successive steam treatments in which only the second required the addition of a catalyst (10 wt % NaOH) for delignification. The macromolecular contents of the residual solids along the different steps of the transformation were evaluated using ASTM and TAPPI standard methods. Carbohydrates were identified and quantified using high-performance liquid chromatography with an anion-exchange stationary phase. The quality of the FIRSST and Kraft pulp produced from the same feedstock was evaluated using standard ATPPC methods.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".