Oxidative Pretreatment of Spruce to Facilitate Enzymatic Hydrolysis of Polysaccharides
Bibliographic record
Abstract
Brown rot fungi employ extracellular Fenton oxidation systems to degrade the wood cell wall structure, exposing structural polysaccharides to the action of hydrolytic enzymes. In an attempt to improve the enzymatic accessibility of cellulose and hemicelluloses by partially degrading the wood cell walls with an oxidative pretreatment, spruce pin chips and wood meal were treated with autoxidation, Fenton oxidation, and peracetic acid (PAA) oxidation. The extent of polysaccharide accessibility was assayed by hydrolyzing treated wood samples with Cellulysin and determining the amount of glucose released with high pH anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Autoxidation and Fenton oxidation did not significantly increase the hydrolytic glucose yield, while PAA treatment afforded a slight increase in the amount of released glucose. Aromatic and dibasic acid lignin degradation products in the MeCl2 extracts of PAA oxidation filtrates were identified with gas chromatography-mass spectrometry (GC-MS), with vanillin and vanillic acid appearing as the predominant products. GC-MS analysis of MeCl2 extracts of the autoxidation and Fenton oxidation yielded only trace amounts of vanillin. Attempts to detect methanol in the oxidation product solutions yielded negative results.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".