Soil properties affect the toxicities of 2,4,6-trinitrotoluene (TNT) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) to the enchytraeid worm <i>Enchytraeus crypticus</i>
Bibliographic record
Abstract
The authors investigated individual toxicities of 2,4,6-trinitrotoluene (TNT) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) to the potworm Enchytraeus crypticus using the enchytraeid reproduction test. Studies were designed to generate ecotoxicological benchmarks that can be used for developing ecological soil-screening levels for ecological risk assessments of contaminated soils and to identify and characterize the predominant soil physicochemical parameters that can affect the toxicities of TNT and RDX to E. crypticus. Soils, which had a wide range of physicochemical parameters, included Teller sandy loam, Sassafras sandy loam, Richfield clay loam, Kirkland clay loam, and Webster clay loam. Analyses of quantitative relationships between the toxicological benchmarks for TNT and soil property measurements identified soil organic matter content as the dominant property mitigating TNT toxicity for juvenile production by E. crypticus in freshly amended soil. Both the clay and organic matter contents of the soil modulated reproduction toxicity of TNT that was weathered and aged in soil for 3 mo. Toxicity of RDX for E. crypticus was greater in the coarse-textured sandy loam soils compared with the fine-textured clay loam soils. The present studies revealed alterations in toxicity to E. crypticus after weathering and aging TNT in soil, and these alterations were soil- and endpoint-specific.
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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 | 0.000 | 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".