Risk-based analysis of polychlorinated biphenyl toxicity in harbor seals
Bibliographic record
Abstract
Persistent organic pollutants (POPs) have been associated with adverse health effects in marine mammals. However, the complex mixtures to which free-ranging populations are exposed constrain the elucidation of cause-and-effect relationships between specific POPs and the observed health risks. In this study, we 1) assembled data from studies showing polychlorinated biphenyl (PCB)-associated effects on the health of free-ranging harbor seals in the northeastern Pacific Ocean, 2) carried out additional POP analyses on seal samples to broaden the available data on contaminant residues, and 3) derived estimates of individual POPs and their toxic risks. Taken together, these components were used to generate a new toxicity reference value (TRV) for the protection of marine mammal health. In this case study of seals in British Columbia, Canada, and Washington State, USA, PCBs were the single most abundant POP and were correlated with several adverse health effects. PCB exposures consistently exceeded regulatory toxicity thresholds for fish-eating wildlife. Nursing seal pups were at particular risk, reflecting their greatly increased dietary intake of PCBs and their sensitivity to developmental toxicity. Based on the collective evidence obtained, we propose TRVs (consisting of 5% tissue residue concentration and dose) of 1.3 mg/kg lipid weight tissue residue in blubber and 0.05 mg/kg lipid weight tolerable daily intake in prey. Insofar as the TRVs are lower than previously established TRVs and regulatory guidelines, our study highlights the current underestimation of risks associated with PCBs in high-trophic-level 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".