Predatory fish consumption by adult female Steller sea lions is positively related to mercury contamination of pups
Bibliographic record
Abstract
Environmental mercury has been an increasing concern in Arctic marine ecosystems and biomagnifies in marine food webs to impact apex predators through chronic exposure. We utilized stable isotopes of carbon (δ13C) and nitrogen (δ15N) measured in the vibrissa (whiskers) of Steller sea lion ( Eumetopias jubatus Schreber, 1776) pups and in the muscle tissue of 13 species of marine fish and cephalopods in Bayesian stable isotope mixing models to estimate prey composition of 658 adult female sea lions during late gestation (winter). Our objective was to determine if the proportional composition of the dam diet reflected in these pups were related to the total mercury concentration ([THg]) in the pups’ lanugo (natal hair), time period (2011–2015 vs. 2017–2019), and/or region (east vs. west of Amchitka Pass). There was no consistent pattern of change over time in [THg] of prey muscle tissue within predatory or non-predatory fish in the locations sampled in contrast to significant increase in lanugo [THg] found in Steller sea lion pups over this period. In both regions, adult females that gave birth to pups with higher lanugo [THg] consumed a greater proportion of predatory prey during late gestation foraging.
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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) | 0.002 | 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".