Comparison of different mechanical refining technologies on the enzymatic digestibility of low severity acid pretreated corn stover
Bibliographic record
Abstract
The effect of mechanical refining on the enzymatic digestibility of pretreated corn stover (PCS) was investigated. Low severity, dilute sulfuric acid PCS was subjected to mechanical refining using a bench-scale food processor blender, a PFI mill, a 12-inch laboratory disk refiner, and a 25 mm co-rotating twin-screw extruder. Glucose yields from enzymatic hydrolysis were improved by 10-15% after blending and disk refining, while PFI refining and twin-screw extrusion showed a glucose yield improvement of 16-20%. A pilot scale refining test using a Szego mill was performed and showed approximately 10% improvements in biomass digestibility. This suggests the possibility to scale up a mechanical refining technique to obtain similar enzymatic digestibility glucose yield enhancement as achieved by PFI milling and extrusion technologies. Proposed mechanisms of each mechanical refining technology are presented and reasons for improvements in biomass digestibility are discussed in this paper.
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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 | 0.001 |
| 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 | 0.000 | 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".