Vitamin E status and the dynamics of its transfer between mother and pup during lactation in grey seals (<i>Halichoerus grypus</i>)
Bibliographic record
Abstract
Concentrations of vitamin E, a powerful antioxidant, were measured in milk and serum of 18 grey seal (Halichoerus grypus) mothers and in the serum of their pups sampled up to 6 times between parturition and weaning on the Isle of May, Scotland, in 1998 and 2000. The vitamin E concentration in colostrum (89.4 ± 22.5 mg/kg milk; mean ± SD) was 4.5 times greater than that in later milk (20.9 ± 5.0 mg/kg milk). It then remained constant until the end of lactation. The decline in concentration of vitamin E in grey seal milk corresponded to a drop in the vitamin E concentration in mothers' serum between parturition (14.0 ± 4.8 mg/L serum) and the second half of the lactation period during which the serum vitamin E concentration remained stable (9.6 ± 3.2 mg/L serum). Circulating vitamin E concentrations varied significantly among mothers but there was no relationship with mother's age. Despite these differences between mothers, individuals produced milk with very similar vitamin E concentrations. The vitamin E concentration in grey seal pups' serum was low at birth (lowest concentration 3.1 mg/L serum) but increased sharply to a peak around days 13 (31.2 ± 5.2 mg/L serum). It then fell, before stabilizing until the end of lactation (21.1 ± 4.5 mg/L serum), reflecting the changes reported in the milk.
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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".