Isolation and molecular identification of extracellular polymeric substances (EPS) producing bacterial strains for sludge settling and dewatering
Bibliographic record
Abstract
One of the major problems in overall wastewater treatment process is sludge settling and dewatering. In general, sludge settling and dewatering is carried out using conventional physico-chemical methods that are known to be expensive, and these processes further increase the sludge volume and ultimate disposal costs. To overcome this problem, a suitable alternative could be the use of bioflocculants for sludge settling and dewatering. To achieve bioflocculation, extracellular polymeric substances (EPS) producing bacterial strains were isolated from the complex microbial community of wastewater sludge. Crude EPS produced in the form of bacterial broth was used to test kaolin flocculation activity. Three out of 10 bacterial strains (B2, B8 and B9) were pre-selected for sludge settling. Based on sludge settling and dewatering results, B8 possessed better flocculating property than other bacterial strains. These sludge microorganisms were identified based on their 16S rDNA sequences and bacterial strain B8 was identified as Serratia sps.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".