First assessment of pollutant exposure in two balaenopterid whale populations sampled in the Svalbard Archipelago, Norway
Bibliographic record
Abstract
Pollutant concentrations are poorly known for the largest animals on Earth, blue whales Balaenoptera musculus and fin whales Balaenoptera physalus. In this study, concentrations of persistent organic pollutants (POPs) were determined in blubber biopsies and stable isotope values for nitrogen (δ15N) and carbon (δ13C) were measured using skin biopsies for 18 blue whales and 12 fin whales sampled in waters surrounding the Svalbard Archipelago, Norway. The samples were collected in summer during the period 2014–2018. POPs were dominated by DDTs, PCBs and toxaphenes, with median concentrations in blue/fin whales being 208/341, 127/275 and 133/233 ng/g lipid weight, respectively. Linear models indicated that pollutant concentrations were 1.6–3 times higher in fin whales than in blue whales, which is likely related to the higher trophic positions of fin whales, as indicated by their higher δ15N. Lower δ13C in fin whales suggests that they feed at higher latitudes than blue whales; these values were not correlated with pollutant concentrations. Pollutant levels were approximately twice as high in males compared to females (intraspecifically), which indicates that females of these species offload pollutants to their offspring during gestation and lactation, similar to many other mammalian species. Pollutant concentrations in balaenopterid whales from Svalbard waters were generally much lower than in conspecific whales from the Mediterranean Sea or the Gulf of California, but higher than those in conspecifics from the Antarctic Peninsula.
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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 | 0.000 | 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".