Bibliographic record
Abstract
There is general consensus among sanitary engineering professionals that municipal wastewater and wastewater sludge is not a “waste”, but a potential source of valuable resources. Energy and Resource Recovery from Sludge provides essential knowledge on energy and resource recovery from sludge and focuses on: International cases studies of established technologies existing at full-scale with commercial applications, as well as those that can potentially be commercialized are provided Emerging technologies that have been demonstrated only at pilot-scale or bench (laboratory) scale are included. Energy recovery technologies can be classified into sludge-to-biogas processes, sludge-to-syngas processes, sludge-to-oil processes and sludge-to-liquid processes. The technologies available for resource recovery include those to recover phosphorus, building materials, nitrogen, volatile acids, etc. Technical, capital cost, operating and maintenance (O&M) costs information available are documented to the extent possible for each technology. Possibilities of upgrading biosolids pellets produced from sludge as renewable source of inoculum for bio-hydrogen gas production and also recovering of bio-pesticides from sludge are new research areas. This title belongs to GWRC Report Series . ISBN: 9781780404653 (eBook)
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 | 0.000 | 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) | 0.000 | 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".