Polychlorinated biphenyl (PCB) concentrations and profiles in marine mammals from the North Atlantic Ocean
Bibliographic record
Abstract
Polychlorinated biphenyls (PCBs) can provide crucial information into the bioaccumulation and biomagnification of POPs in marine mammals. Muscle tissue samples were obtained for detailed PCB congener specific analysis of all 209 PCBs in 11 species of marine mammals stranded across the coast of the UK between 2010 and 2013. At least 145 PCB congeners were found in each individual. The highest concentrations of PCBs were recorded in a killer whale (318 mg/kg lipid) and the highest toxic equivalent in a Risso's dolphin (1687 pg/g TEQ2005 wet). Concentrations of PCBs in the majority of samples exceeded toxic thresholds (9 mg/kg lipid) for marine mammals, highlighting the health risk they face from PCB exposure. Many PCB profiles did not fit typical ‘Aroclor’ signatures, but instead indicated patterns of congeners that are resistant to biotransformation and elimination. However, this study identified a novel PCB signature in a sei whale that has not yet been previously observed in marine mammals. The whale had a PCB profile that included lighter and inadvertent PCB congeners such as PCB 11, suggesting that the main source of exposure was through atmospheric deposition, rather than terrestrial discharges. Seven subsamples were chosen for chiral analysis of PCB 95, 136 and 149. The enantiomer fractions (EFs) of C-PCBs 95 and 149 were non racemic suggesting there may be enantiomer selective metabolism in marine mammals. Although there has been a shift in the literature towards emerging pollutants, this study acts as a stark reminder that PCBs continue to pose a significant risk to wildlife.
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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".