The influence of lignin migration and relocation during steam pretreatment on the enzymatic hydrolysis of softwood and corn stover biomass substrates
Bibliographic record
Abstract
To be effective, steam pretreatment is typically carried out at temperatures/pressures above the glass transition point (Tg) of biomass lignin so that it can partly fluidize and relocate. The relocation of Douglas-fir and corn stover derived lignin was compared with the expectation that, with the corn stover lignin's lower hydrophobicity and molecular weight, it would be more readily fluidized. It was apparent that the Tg of lignin decreased as the moisture increased, with the easier access of steam to the corn stover lignin promoting its plasticization. Although the softwood lignin was more recalcitrant, when it was incorporated onto filter paper, it too could be plasticized, with its relocation enhancing enzymatic hydrolysis. When lignin recondensation was minimized, the increased hydrophobicity suppressed lignin relocation. It was apparent that differences in the accessibility of the lignin present in Douglas-fir and corn stover to steam significantly impacted lignin fluidization, relocation, and subsequent cellulose hydrolysis.
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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".