Repeatability in lactation performance and the consequences for maternal reproductive success in gray seals
Bibliographic record
Abstract
In mammals, the most significant maternal effect on offspring growth during lactation is the ability of females to efficiently transfer milk energy to their neonates. However, despite the importance of the transfer of milk energy to both maternal and offspring fitness, nothing is known about the extent to which variation among females may be attributed to differences in individual quality or environmental variation in natural populations. We measured repeatability over multiple lactation periods in components of lactation performance in free-ranging, multiparous gray seal (Halichoerus grypus) females to examine to what extent variation among females in pup weaning mass may be attributed to inherent differences in their physiological capacity to deliver milk energy. Levels of repeatability were high for milk composition (r = 0.38-0.50), daily milk output (r = 0.46), and the duration of lactation (r = 0.57), demonstrating that there are consistent differences among females in these characters across lactations and that the overall capacity of gray seal females to deliver milk energy to their pups is characteristic of individuals. The repeatability in pup weaning mass (r = 0.48) was consistent with the values for the components of total milk energy output and suggests that, over a large proportion of their reproductive life, individual gray seal females will consistently wean pups with greater or lesser probabilities of survival. Our results suggest that inherent differences among females in their physiological capacity to deliver milk energy may be an important component of variation in individual quality and, thus, lifetime reproductive success in mammals. High levels of repeatability also suggest that components of milk energy transfer may have a significant heritable genetic basis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".