The Enantioselective Bioaccumulation of Chiral Chlordane and α-HCH Contaminants in the Polar Bear Food Chain
Bibliographic record
Abstract
The enantiomer ratios (ERs) of α-HCH and chlordane related compounds (CHLs) were examined in the polar bear food chain (arctic cod−ringed seal−polar bear), using chiral gas chromatography−mass spectrometry (GC-MS). The cod showed near-racemic mixtures (ER = 1) for most of the compounds. In contrast, ERs in ringed seal and polar bear were frequently nonracemic (ER ≠ 1), due to enantiomer-specific biotransformation. As (+)-α-HCH was transferred up the food chain, it became more abundant relative to (−)-α-HCH. For the CHLs, there was no uniform trend for the ER changes and the increasing trophic level. Apparent chiral biomagnification factors (BFs) were calculated and up to a 20-fold difference in the BF between enantiomers was found. Analysis of chiral BFs relative to CB-153 indicated that oxychlordane was formed by ringed seal and metabolized by polar bears. However, the ERs did not change significantly as a result of these biotransformations. Multivariate statistical methods revealed the clustering of sample categories and were used to investigate the relationships between the ERs, chemical residue concentrations, and biological data. ERs were important variables for the sample groupings and for the class separation of male/female seals and fat/liver tissues. The variance in the cytochrome P450 CYP2B protein content of bear liver could be explained by the variances in chemical residue data. In this analysis the ERs were of secondary importance. The ERs of some highly recalcitrant CHLs in polar bear adipose showed linear relationships with the age of the bears.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".