Egg size predicts motor performance and postnatal weight gain of Australian Brush-turkey (<i>Alectura lathami</i>) hatchlings
Bibliographic record
Abstract
Birds usually influence offspring survival through the amount of parental care they provide. Megapodes have evolved a different life history. Eggs are incubated by external heat sources, and chicks dig themselves out of their underground nest and live independently of their parents. Egg size is one of the few means by which females can influence chick survival. We found that in the Australian Brush-turkey, Alectura lathami Gray, 1831, eggs and hatchlings varied considerably in size, with a ratio of 1.62 between the largest and the smallest egg. Egg size was positively correlated with hatchling body mass and tarsus length. It also significantly predicted the chicks' motor performance: chicks from larger eggs dug their way out of their underground nest faster and were more active when kept in a resting box and monitored by motion detection software. The main advantage of reaching the surface more quickly is likely that such chicks will have more time to find suitable food, refuge, and a tree for roosting at night while still feeding on their internal yolk reserves. Egg size also interacted significantly with body mass during the first 10 months of life. A size advantage at hatching thus seems to have an immediate effect on motor performance and a longer term effect on the ability to gain mass.
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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) | 0.002 | 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".