What causes the decrease in haematocrit during egg production?
Bibliographic record
Abstract
Summary Anaemia has been reported in wild animals, typically associated with traumatic events or ill health. However, female birds routinely become ‘anaemic’ during egg‐laying; we sought to determine the causes of this reduction in haematocrit. Haematocrit in female European Starlings (Sturnus vulgaris Linnaeus) decreased between pre‐breeding and egg‐laying in 3 out of 4 years (the decrease was marginally non‐significant in the fourth year). This was independent of changes in ambient temperature altering the metabolic requirements for thermoregulation. There was a positive relationship between haematocrit and plasma levels of the yolk precursor vitellogenin among egg‐laying birds, supporting the hypothesis that the initial reduction in haematocrit is caused by increased blood volume associated with osmoregulatory adjustments to elevated levels of yolk precursors. However, haematocrit did not always recover upon cessation of egg production, remaining low at clutch completion (2 of 4 years), incubation (1 of 2 years) and chick rearing (1 of 4 years), suggesting an additional cause of the prolonged reduction in haematocrit. Given the magnitude and prolonged nature of the changes in haematocrit we report, and the interannual variation in haematocrit even during chick‐rearing (47–54%), we suggest that ‘anaemia’ associated with egg production might have implications for aerobic performance during later stages of breeding.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".