Study of the diversity of microbial communities in a sequencing batch reactor oxic–settling–anaerobic process and its modified process
Bibliographic record
Abstract
To further reveal the mechanism of sludge reduction in the oxic-settling-anaerobic (OSA) process, the polymerase chain reaction - denaturing gradient gel electrophoresis protocol was used to study the possible difference in the microbial communities between a sequencing batch reactor (SBR)-OSA process and its modified process, by analyzing the change in the diversity of the microbial communities in each reactor of both systems. The results indicated that the structure of the microbial communities in aerobic reactors of the 2 processes was very different, but the predominant microbial populations in anaerobic reactors were similar. The predominant microbial population in the aerobic reactor of the SBR-OSA belonged to Burkholderia cepacia, class Betaproteobacteria, while those of the modified process belonged to the classes Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria. These 3 types of microbes had a cryptic growth characteristic, which was the main cause of a greater sludge reduction efficiency achieved by the modified process.
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) | 0.000 | 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 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".