Biomagnification of polychlorinated biphenyls in a harbor seal (<i>Phoca vitulina</i>) food web from the strait of Georgia, British Columbia, Canada
Bibliographic record
Abstract
Polychlorinated biphenyl (PCB) biomagnification was characterized in a harbor seal food web in the Strait of Georgia, British Columbia, Canada. Trophic magnification factors (TMFs) for PCBs averaged 3.6, with a range of 0.7 to 9.4. The TMFs for individual congeners correlated with log K(OW) (r(2) = 0.56, p < 0.001), reflecting the role that physicochemical properties play in driving the biomagnification of PCBs in marine food webs. However, TMFs differed among PCB structure activity groups, clearly indicating an additional role for metabolic transformation of certain PCBs. The known feeding preferences of harbor seals enabled the calculation of trophic level-adjusted biomagnification factors (BMF(TL)) for PCBs in this species, which averaged 13.4 and ranged from 0.2 to 150.6. Metabolic transformation in seals explained some of the variation in congener-specific biomagnification, with lower BMF(TL) values for PCB congeners with meta- and parachlorine unsubstituted positions. Principal components analysis revealed the distinct roles played by trophic level, log K(OW), and metabolic transformation in explaining the notable differences in PCB patterns among harbor seals, their pups, and their prey. In the present study, the authors estimate there to be approximately 76 kg of PCBs in the biota of the Strait of Georgia, of which 1.6 kg is retained by harbor seals.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".