Bioremediation of highly energetic compounds: a search for remediation technologies
Bibliographic record
Abstract
When TNT (N-source) was treated with anaerobic sludge it biotransformed into triaminotoluene (TAT) in high yield (80%). Results of experiments using 13C-labeling indicate that denitrated or deaminated products such as p-cresol and toluene were not formed. Whereas 14C-labeling showed negligible mineralization (<0.1% 14CO2) despite the complete disappearance of TNT. On the other hand, when TNT (175 μM) was treated with the fungus Phanerochaete chrysosporium it disappeared completely in less than two weeks, but mineralization (liberated 14CO2) did not exceed 1%. Several intermediates, marked with the initial formation of the two monohydroxylamino-dinitrotoluene (HADNT) followed by their transformation to monoamino-dinitrotoluenes (ADNT), diamines (DANT), acetylated TNT products, and azo and hydrazo derivatives were detected. In contrast, high concentrations (ca 20,000 ppm) of RDX and HMX were effectively degraded (ca 70%) in soil slurries using municipal anaerobic sludge. RDX and HMX disappearance was accompanied by the elimination of toxicity associated with RDX and HMX as determined by the Microtox test.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".