Vitamins A and E in liver, kidney, and whole blood of East Greenland polar bears sampled 1994–2008: reference values and temporal trends
Bibliographic record
Abstract
Vitamins A (retinol) and E (α-tocopherol) are dietary vitamins, essential for, e.g., growth and development, reproduction, and immune function. Persistent organic pollutants (POPs) have been found to be related to vitamin A and E metabolism. However, few investigations have been published on this health issue in polar bears ( Ursus maritimus ). The aim of this study was thus to provide reference values for concentrations of vitamin A in liver, kidney cortex, and whole blood and vitamin E in kidney cortex and whole blood from 166 East Greenland polar bears, as well as to assess the relationship between POPs and vitamin concentrations. In addition, vitamin concentrations were analyzed for temporal trends (1994–2008). Results showed vitamin A in liver to be higher in adult bears and the concentrations of vitamin E in kidney and blood to likewise be generally higher in adult bears. In addition, all analyzed contaminant groups were correlated with at least one of the vitamin parameters, predominantly in a negative way. Finally, vitamin A liver concentrations as well as concentration of vitamin E in kidney and blood showed a temporal increase. Together, these results add to the weight of evidence that POPs could be disrupting polar bear vitamin status. However, while the observed temporal increases in vitamin concentrations were likely POP related, the question remains as to whether they stem from influence of contaminants only or also, e.g., changes in prey species. Further studies are needed to tease apart the causes underlying these changes in vitamin concentrations.
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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 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".