Ecotoxicity of Nitrogen, Sulfur, or Oxygen Heterocycles and Short-Chained Alkyl Phenols Commonly Detected in Contaminated Groundwater
Bibliographic record
Abstract
Abstract Nitrogen, sulfur, or oxygen heterocyclic aromatic hydrocarbons (NSO-HETs) and short-chained alkyl phenols (SCAPs) are commonly detected in groundwater at contaminated sites and in the surrounding environment. It is now scientific consensus that these chemicals pose a risk to human and ecosystem health. However, toxicity data are comparably fragmentary, and only few studies have addressed the ecotoxicity of NSO-HETs and SCAPs in a systematic and comparative fashion. To overcome this shortcoming, we tested 18 SCAPs, 16 NSO-HETs, as well as the homocyclic hydrocarbons indane and indene in the Microtox® assay with Aliivibrio fischeri, the growth inhibition test with Desmodesmus subspicatus, the acute immobilization assay with Daphnia magna, as well as the fish embryo toxicity test with embryos of the zebrafish (Danio rerio). Because of the physicochemical properties of the tested chemicals (limited water solubility, volatility, and sorption to test vessels), actual exposure concentrations in test media and their dissipation over time were analytically quantified by means of gas chromatography with mass spectrometry. Analytically corrected effect levels (median effect and lethal concentrations) ranged from 0.017 to 180 mg L–1, underlining the environmental relevance of some NSO-HETs and SCAPs. Para-substituted phenols showed the overall greatest toxicities in all 4 toxicity tests. We provide, for the first time, a complete high-quality data set in support of better environmental risk assessments of these chemicals. Environ Toxicol Chem 2019;38:1343–1355. © 2019 SETAC
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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 | 0.000 | 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".