Contaminant-related disruption of vitamin a dynamics in free-ranging harbor seal (<i>Phoca vitulina</i>) pups from british columbia, canada, and washington state, usa
Bibliographic record
Abstract
Abstract Marine mammals can bioaccumulate high concentrations of lipophilic environmental contaminants, such as polychlorinated biphenyls (PCBs), polychlorinated dibenzo-para-dioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs), through the diet. Both laboratory and wildlife studies have shown that these persistent chemicals can disrupt the regulation of vitamin A (retinol), a dietary hormone required for immune function, reproduction, growth, and development. To determine whether environmental contaminants affect the circulatory vitamin A dynamics of free-ranging harbor seals (Phoca vitulina), we live-captured 61 pups from British Columbia, Canada, and Washington State, USA, and obtained blood and blubber biopsy samples. Harbor seal pups from Washington State were six times more contaminated with total PCBs than pups from British Columbia and had significantly lower circulatory retinol levels. However, when data were corrected for differences in nursing status and analyzed as ungrouped sets of data, circulatory retinol levels were positively correlated with contaminant levels in the blubber of nonnursing pups. This increase in retinol may have resulted from a mobilization of liver vitamin A stores into circulation following exposure to milk-derived contaminants; this has been observed in laboratory animals exposed experimentally. The contaminant-related disruption of vitamin A dynamics observed in our study occurs at a time when vitamin A is required for growth and development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".