Anaerobic co-digestion of municipal organic wastes and pre-treatment to enhance biogas production from waste
Bibliographic record
Abstract
Co-digestion and pre-treatment have been recognized as effective, low-cost and commercially viable approaches to reduce anaerobic digestion process limitations and improve biogas yields. In our previous batch-scale study, fat, oil, and grease (FOG) was investigated as a suitable potential co-substrate, and thermo-chemical pre-treatment (TCPT) at pH = 10 and 55 °C improved CH4 production from FOG co-digestions. In this project, co-digestions with FOG were studied in bench-scale two-stage thermophilic semi-continuous flow co-digesters with suitable TCPT (pH = 10, 55 °C). Overall, a 25.14 ± 2.14 L/d (70.2 ± 1.4% CH4) biogas production was obtained, which was higher than in the two-stage system without pre-treatment. The results could provide valuable fundamental information to support full-scale investigations of anaerobic co-digestion of municipal organic wastes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".