Fermentation of thickened waste activated sludge for volatile fatty acids
Bibliographic record
Abstract
The pre-treatment of sludge has gained a lot of attention for treating and handling waste, especially in wastewater treatment plants. Different technologies are being investigated to improve how waste can be reduced, a certain type of pre-treatment used is Free Nitrous Acid (FNA). This technology has been used as a chemical pre-treatment in the anaerobic digestion process to improve the fermentation/hydrolysis stage. The effect of utilizing different doses of the FNA pre-treatment was investigated for this study, and the effect of the pre-treatment on the characteristics of thickened waste activated sludge (TWAS) were identified. It was observed that as the doses of FNA increased, the concentration of soluble chemical oxygen demand (SCOD) increased, with the highest values noticed at an FNA concentration of 0.7 mg N/L for both experiments. The volatile suspended solids (VSS) decreased as the doses of FNA increased, the highest decrease in VSS was observed at FNA dose of 2.8 mg N/L.
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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) | 0.001 | 0.001 |
| 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".