Explosive biodegradation in soil slurry batch reactors amended with exogenous microorganisms
Bibliographic record
Abstract
The present study explores the feasibility of biotreatment of 2,4,6-trinitrotoluene (TNT) and hexahydro-1,3,5-trinitro- 1,3,5-triazine (RDX)-contaminated soils in slurry batch reactors. Radiorespirometric assays showed that anaerobic sludge was able to mineralize 59% RDX to CO2 although significant mineralization of TNT was not observed in all cases. TNT and RDX at concentrations higher than 50 and 100 mg/L respectively were inhibitory to methanogenesis (used as a bioindicator), however, methanogenesis recovered after TNT was transformed into less toxic triaminotoluene. Bioslurry batch reactors containing 40% of contaminated soil (2000 mg RDX and 1000 mg TNT/kg dry soil) were operated under various conditions. Both TNT and RDX were persistent to soil indigenous microbes. Degradation of both TNT and RDX was enhanced by the municipal sludge amendment, although degradation of RDX was only achieved under anaerobic conditions.
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) | 0.001 | 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".