Tracking the transformation of persistent organic pollutants in food webs using multi element isotope and enantiomer fractionation
Bibliographic record
Abstract
In order to track the transformation of persistent organic pollutants (POPs) in food webs, field experiments were conducted at two sites using stable isotope and enantiomer fractionation concepts. The enantiomers of α-hexachlorocyclohexane (α-HCH) were selected as representative compounds for POPs. Isotope and enantiomer fractionation allowed the characterization of α-HCH enantiomer biotransformation processes along trophic levels of the food web - from soil and plants to animal livers, fat tissues and milk. The enrichment of heavy isotopes in soils, plants and sediments as well as the changes of enantiomer fractionation indicate that the biotransformation of α-HCH occurred in these compartments. Moreover, the increase of carbon and chlorine isotopic compositions as well as the changes of enantiomer fractionation of liver, fat tissues and milk demonstrated that the overall HCH exposure was much higher than estimates based on concentration levels, while the isotope and enantiomer fractionation revealed the enantiomer specific enantiomer uptake across the blood-brain barriers. Dual element isotope analysis suggested that complex transformation processes have occurred along the potential food web from the HCH sources over different environmental compartments to animal livers, fat tissues and milk. The results imply that the analyses of stable isotope compositions and concentrations has potential to reconstruct the exposure of higher organisms to POPs.
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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) | 0.000 | 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".