Laboratory and Field Approaches to Characterize the Soil Ecotoxicology of Polynitro Explosives
Bibliographic record
Abstract
Nitro-aromatic and heterocyclic compounds such as 2,4,6-trinitrotoluene (TNT), l,3,5-trinitro-l,3,5-triazacyclohexane (RDX), 1,3,5,7-tetranitro-l,3,5,7-tetrazacyclooctane (HMX), have been identified worldwide in soil and groundwater, at sites related to military activities. Among these chemicals, the toxicology of TNT is better known; however, gaps of knowledge still exist. We characterized the soil ecotoxicology of these energetic polynitro substances and their degradation products. The toxicities of these chemicals on microbial, plants, and invertebrate (oligochaete) species, and to cultured mammalian cell systems were examined using spiked and field soil samples. A sensitivity distribution ranking the responses of species was assembled for establishing soil benchmarks for explosives such as TNT. Preliminary field studies were also carried out using earthworm mesocosms. These approaches will increase the toxicological understanding of energetic compounds and our ability to detect exposure/toxicities of these substances in the field, and aid in establishing environmentally acceptable criteria, which are of great interest to land managers.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".