Persistent organic pollutants in the diet of harbor seals (<i>Phoca vitulina</i>) inhabiting puget sound, washington (USA), and the strait of Georgia, British Columbia (Canada): A food basket approach
Bibliographic record
Abstract
Harbor seals (Phoca vitulina) inhabiting Puget Sound (WA, USA) recently were found to be seven times more contaminated with polychlorinated biphenyls (PCBs) than those inhabiting the adjacent Strait of Georgia (BC, Canada). We carried out a food basket approach to approximate realistic dietary exposures of both new (e.g., polybrominated diphenyl ethers [PBDEs]) and legacy (e.g., dichlorodiphenyltrichloroethane [DDT]) persistent organic pollutants (POPs) for these harbor seals. Food basket homogenates, each consisting of over 200 individual prey items, were constructed using documented dietary preferences for harbor seals in these basins, and analyzed for organochlorine pesticides, flame retardants, and other persistent contaminants. Concentration rankings for the major contaminant classes in the Puget Sound food basket were sigmaPCBs > sigmaPBDEs > sigmaDDT, and for the Strait of Georgia food basket were sigmaPCBs > sigmaDDT > sigmaPBDEs, highlighting the emergence of PBDEs as a significant concern in the regional environment. Consistent with observations in harbor seals, PCB concentrations in the Puget Sound food basket were seven times higher than in its Strait of Georgia counterpart. Based on our food basket results, the estimated daily intake of sigmaPCB toxic equivalents to dioxin by Puget Sound harbor seals exceeds some wildlife consumption guidelines for PCBs. Our results indicate that both legacy and new POPs present a health risk to these marine mammals.
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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 | 0.001 | 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) | 0.001 | 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".