Chemical Pretreatment and Enzymatic Hydrolysis of Mixed Source-Separated Organic (SSO) and Wood Waste
Bibliographic record
Abstract
This paper examines the effectiveness of two pretreatments on Source-Separated Organic waste (SSO) mixed with wood wastes: long term lime for SSO mixed with forestry waste (hardwoods), and the cellulose solvent-organic lignocellulose fractionation (COSLIF) method, with SSO and demolition waste (softwoods). For long term lime treatment, the highest overall conversions from cellulose to glucose and xylose were 50.4%, and 43.5% respectively. The best temperature found for long term lime pretreatment was 65°C. The COSLIF pretreatment glucose yield was found to be 93.7%. The highest enzyme hydrolysis yield found was 93.5% for a cellulase loading of 30 FPU/g glucan at 50°C. The best hydrolysis yield found at lower loading (10 FPT/g glucan), was 83.5%. At 40 and 50°C, all peak hydrolysis yields were achieved between 12 and 24 hours. A drop in temperature below 40°C caused a slowing of the hydrolysis rate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".