Vitellogenin dynamics during egg‐laying: daily variation, repeatability and relationship with egg size
Bibliographic record
Abstract
Daily variation in circulating levels of the avian yolk precursor, vitellogenin (VTG), throughout the laying cycle was investigated in female zebra finches Taeniopygia guttata and compared with predicted ovarian follicle demand (based on a model of follicular development for this species). In general, the pattern of variation in plasma VTG matched the predicted demand from the developing ovarian follicle hierarchy. Plasma VTG was non‐detectable in non‐breeders, but increased rapidly with onset of yolk development, remaining high (1.43–1.82 μg/ml, zinc) through to the 3‐egg stage. Plasma levels then declined at the 5‐egg stage (to 0.78±0.32 μg/ml) and were undetectable at clutch completion. This result is consistent with the hypothesis that yolk precursor production is costly and that selection has matched supply and demand. While inter‐individual variation in plasma VTG was marked (e.g. 0.47–4.26 μg/ml at the 1‐egg stage), it also exhibited high intra‐individual repeatability (r=0.87–0.93). Finally, we examined the relationship between plasma VTG and primary reproductive effort. While individual variation in plasma VTG was independent of clutch size, laying interval and laying rate, there was a complex, diet‐dependent relationship between VTG and egg size, with low plasma VTG levels being associated with both very small (<0.90 g) and very large (>1.15 g) egg sizes.
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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 | 0.000 | 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".