The metabolic cost of avian egg formation: possible impact of yolk precursor production?
Bibliographic record
Abstract
Little is known about the energy costs of egg production in birds. We showed in previous papers that, during egg production, European starlings (Sturnus vulgaris) undergo a 22% increase in resting metabolic rate (RMR) and that the maintenance and activity costs of the oviduct are responsible for 18% of the variation in elevated laying RMR. Therefore, other energy-consuming physiological mechanisms must be responsible for the remaining unexplained variation in elevated laying RMR. Yolk precursor [vitellogenin (VTG) and very-low-density lipoprotein (VLDL)] production is likely to be costly because it signifies a marked increase in the biosynthetic activity of the liver. We documented the pattern of yolk precursor production in response to daily injections of 17beta-estradiol (E2) in zebra finches (Taeniopygia guttata). Based on this pattern we carried out an experiment in order to evaluate the metabolic costs of producing VTG and VLDL. Our E2 treatment resulted in a significant increase in plasma VTG and VLDL levels within the natural breeding range for the species. Although RMR was measured during the period of active hepatic yolk precursor production, it did not differ significantly within individuals in response to the treatment or when comparing E2-treated birds with sham-injected birds. This could mean that yolk precursor production represents low energy investment. However, we discuss these results in light of possible adjustments between organs that could result in energy compensation.
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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".