Removal of benzotriazoles from domestic wastewater using <scp> <i>Pleurotus ostreatus</i> </scp> fungal pellets
Bibliographic record
Abstract
Abstract Benzotriazoles are a group of persistent and mobile substances commonly found in aquatic environments due to inefficient treatment in conventional sewage treatment plants. Hence, it is crucial to explore alternative technologies for their degradation to avoid their adverse effects on the environment and human health. The potential removal capability of four benzotriazoles and one benzothiazole (1H‐benzotriazole, BTR; 4‐methyl‐1H‐benzotriazole, 4TTR; 5‐methyl‐1H‐benzotriazole, 5TTR; 5‐chlorobenzotriazole, CBTR; xylytriazole, XTR; and 2‐Hydroxybenzothiazole, OH‐BTH) from domestic wastewater was investigated using the white‐rot fungus Pleurotus ostreatus in pellet form. The study was conducted in bioreactors operated in repeated batch cycles mode. The results showed that the fungal pellet reactor achieved a higher removal rate for CBTR (70% ± 17%) compared to the control (62% ± 16%). Furthermore, the removal rate for the other compounds (BTR, 5‐TTR, OH‐BTH) ranged from 17% to 19%, whereas the control reactor exhibited no removal for these compounds. Overall, these findings indicate the potential of fungal pellet reactors for the removal of benzotriazoles and benzothiazole from domestic wastewater.
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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) | 0.000 | 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) | 0.001 | 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".