Should I brood or should I hunt: a female barn owl's dilemma
Bibliographic record
Abstract
While brooding, many female raptors rely exclusively on food provisioning from males. Thus, they may forego hunting until young are about half grown before exiting the nest to undertake a first foraging trip. To investigate the mechanisms that trigger this first foraging exit, we analysed nest food provisioning, female body mass change, and nestling and female food requirements in regard to exit date in five pairs of barn owls, Tyto alba (Scopoli, 1769), nesting in eastern France. Adult mass and behaviour were monitored using an automated weighing system and a video camera. Our results indicate that the first foraging exit of the female occurs about 15 days after the hatching of the first egg. This reinitiation of foraging occurs at about the same time that male food provisioning no longer matches nestling food requirements — about 17 days after the hatching of the first egg. Thus the timing of the female's first hunting trip may be primarily adjusted to a discrepancy between brood food requirements and available food supply. Additionally, we found that females started to lose mass, on average, 6 days before their first hunting trip through a reduction of food intake, and we discuss the potential mechanisms and implications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".