Immobilization strategies for bioaugmentation of anaerobic reactors treating phenolic compounds
Bibliographic record
Abstract
Degradation of phenol, ortho- and para-cresol was investigated in upflow anaerobic sludge bed (UASB) reactors bioaugmented with a methanogenic enrichment consortium able to degrade a mixture of phenolic compounds, in comparison to a reactor, which was inoculated only with anaerobic granules: 1) natural attachment of free cells to the granules, and 2) encapsulation within alginate beads. The increase of the percentage of enrichment from 2 to 5% improved considerably the startup of the reactors. Going from 5 to 10% had no effect on the removal of the phenolic compounds. Following a period of continuous operation at a hydraulic retention time of 3 days, the bioaugmented reactors showed specific activities on phenol, ortho- and para-cresol, at least twofold higher than those of the control reactor. This increase was attributed to the immobilization of phenol, ortho- and para-cresol-degrading bacteria on the granules.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".