Individual variation in milk composition over lactation in harbour seals (<i>Phoca vitulina</i>) and the potential consequences of intermittent attendance
Bibliographic record
Abstract
We studied milk composition over the course of lactation in 21 harbour seal (Phoca vitulina L., 1758) females on Sable Island, Nova Scotia. Milk fat content increased significantly from 40.8% ± 1.01% at parturition to 50.2% ± 1.39% at day 7 and then remained relatively constant throughout the remainder of lactation. Changes in dry matter mirrored changes in fat content. Protein content averaged about 9% over mid to late lactation. There was considerable between-individual variation in the composition of milk and how it changed over lactation, particularly in milk fat content (CV 9.1%–11.4%). In three females that were separated from their pups for 4–6 days, milk fat content declined by 20%–23% and milk protein content increased by 6%–11%. These changes in milk composition indicate that changes in mammary gland function occur rapidly following the onset of milk stasis in harbour seals. The rapid response of the mammary glands to separation suggests that, in direct contrast to the glands of otariids, the glands of harbour seals rely on regular evacuation to maintain normal function. These results suggest that there may be a significant physiological constraint on the duration that harbour seal females, and presumably other phocid seals, can forage without negatively affecting energy transfer to their pups.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".