Harbor seals (<i>Phoca vitulina</i>) in British Columbia, Canada, and Washington State, USA, reveal a combination of local and global polychlorinated biphenyl, dioxin, and furan signals
Bibliographic record
Abstract
The harbor seal (Phoca vitulina) can serve as a useful indicator of food web contamination by persistent organic pollutants (POPs) because of its high trophic level, wide distribution in temperate coastal waters of the Northern Hemisphere, and relative ease of capture. In 1996 through 1997, we live-captured 60 harbor seal pups from three regions, spanning remote (Queen Charlotte Strait, BC, Canada), moderately industrialized (Strait of Georgia, BC, Canada), and heavily industrialized (Puget Sound, WA, USA) marine basins straddling the Canada-United States border. Biopsy samples of blubber were taken and analyzed for congener-specific polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs) by using high-resolution gas chromatography-high-resolution mass spectrometry. Harbor seals in Puget Sound were heavily contaminated with PCBs, whereas seals from the Strait of Georgia had relatively high concentrations of PCDDs and PCDFs. Pattern evaluation and principal components analysis suggested that proximity to sources influenced the mixture to which seals were exposed, with those inhabiting more remote areas being exposed to lighter PCB congeners (those with lower Henry's law constant and K(ow)) that disperse more readily through atmospheric and other processes. Total toxic equivalents to 2,3,7,8-tetrachlorodibenzo-p-dioxin for the PCBs, PCDDs, and PCDFs suggest that Puget Sound seals are at greatest risk for adverse health effects, and that PCBs represent the class of dioxinlike contaminants of greatest concern at all sites.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".