Fungal treatment for recalcitrant compounds removal in raw leachate and synthetic solutions
Bibliographic record
Abstract
Landfill leachate is a strongly polluted wastewater. Although different strategies have been developed for landfill leachate treatment, several drawbacks, such as high costs and complexity, are still unresolved. Fungi, and especially White-Rot Fungi (WRF) with their extracellular enzymes, are gaining considerable research interests among bio-based industries as they resulted effective toward several types of pollutants. Besides the promising results achieved with WRF on difficult wastewaters, at the moment only a limited number of studies has been reported about the use of WRF in landfill leachate treatment. The present work is focused on the treatment of leachate and diverse recalcitrant compounds using the White-rot fungus Bjerkandera adusta MUT2295 through batch tests. The fungal strain was inoculated in raw leachate (RL) from a Canadian landfill (Brady Road) and 2 recalcitrant synthetic solutions prepared with tannic acid (TA) and humic acid (HA).
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".