Experimental dissociation of the effects of diet, age and breeding experience on primary reproductive effort in zebra finches <i>Taeniopygia guttata</i>
Bibliographic record
Abstract
Reproductive performance varies with age in a wide range of organisms, and increasingly such patterns are interpreted in terms of state‐dependent models. We sought to characterise ‘state’ with regards to age‐related variation in clutch size, egg mass and timing of breeding in captive zebra finches Taeniopygia guttata , focusing on the roles of diet quality, age and breeding experience. Females on a high‐quality diet laid larger clutches of larger eggs than did females on a low‐quality diet. The effect of age on reproductive performance was examined by comparing females breeding (i.e. paired) for the first time at either 3‐ and/or 6‐months of age. Clutch size increased with age but on the low‐quality diet only, not on the high‐quality diet. Furthermore, clutch size decreased between 3‐ and 6‐months of age in birds bred first on the high‐quality diet and then on the low‐quality diet. Age did not affect egg mass but older birds had shorter laying intervals. Reproductive performance did not differ between females breeding at 6‐months of age for the first or second time: the effects of age were not due to ‘training’ effects or experience specific to breeding (e.g. undergoing the physiological process of egg formation). In conclusion, nutritional condition (diet) emerged as a central component of state that could strongly influence, and even reverse, any age‐dependent increase in primary reproductive performance.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".