Satellite Telemetry Informs PCB Source Apportionment in a Mobile, High Trophic Level Marine Mammal: The Ringed Seal (<i>Pusa hispida</i>)
Bibliographic record
Abstract
Marine mammals are typically poor indicators of point sources of environmental contaminants as a consequence of their often complex feeding ecologies and extensive movements, all of which mask the contributions of specific inputs. The release of polychlorinated biphenyls (PCBs) by a military radar station into Saglek Bay, Labrador (Canada) has contaminated marine sediments, bottom-feeding fish, seabirds, and some ringed seals, but attributing the PCBs in the latter highly mobile animals to this source is exceedingly difficult. In addition to the application of such tools as stable isotopes (δ(15)N and δ(13)C) and univariate and multivariate statistical exploration of contaminant patterns and ratios, we used satellite telemetry to track the movements of 13 seals in their transient use of different feeding areas. Reduced size of home range and core area (i.e., areas of concentrated use), as well as increased time in coastal inlets, were important determinants of increased PCB concentrations in seals reflecting the contribution of Saglek Bay. Seals were classified into the same feeding groups using both space use and their contaminant burdens 85% of the time, highlighting the link between feeding ecology and exposure to PCBs. While the PCB source at Saglek provided a strong local signal in a remote environment, this first use of satellite telemetry demonstrates the utility of evaluating space-use strategies to better understand contaminant exposure, and more specifically the contribution of contaminant hotspots to mobile predators.
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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 | 0.000 | 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) | 0.001 | 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".