Chicks of cavity-nesting birds do not ‘exercise’ prior to fledging
Bibliographic record
Abstract
Fledging represents a key life-history transition involving a rapid increase in workload associated with a rapid transition from sedentary nestling to volant, active fledgling. Here, we tested the idea that chicks might prepare for fledging through increased voluntary activity (‘exercise’) and whether this would impact somatic and physiological development. European starling ( Sturnus vulgaris ) chicks, in cavity nests, increased levels of putative exercise (wing flapping), and more general active behaviours (e.g. perching, standing) in the five days up to fledging. However, facultative mass loss and wing growth between days 15 and 20 were independent of time spent wing flapping, standing or perching and, counterintuitively, we found a weak negative relationship between haematocrit (a measure of aerobic capacity) and time spent wing flapping or standing. Thus, although exercise is commonly associated with an increase in haematocrit in other species, this does not appear to be a mechanism for increasing pre-fledging haematocrit in chicks. Despite widespread anecdotal observations of flight preparation (e.g. wing flapping) in larger seabirds and raptors, our data suggest that exercise, or increased activity in general, does not contribute to improved development just prior to fledging: starling chicks do not ‘exercise’ enough to show somatic or physiological effects.
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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) | 0.002 | 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".