Can changes in provisioning by parent birds account for seasonally declining patterns of offspring recruitment?
Bibliographic record
Abstract
Declining reproductive success among individuals that breed later in the season occurs in numerous taxa and is particularly well-documented in birds. Principal ideas advanced to explain this pattern, the date and parental quality hypotheses, consider the ultimate causes of this phenomenon and have received much attention; however, proximate mechanisms have not been clearly elucidated. Parental provisioning could mediate a seasonal decline in nestling fitness. We delayed hatch dates and manipulated brood sizes of Tree Swallows ( Tachycineta bicolor (Vieillot, 1808)) to assess the ability of parents to compensate for deteriorating environmental conditions and increased demands of more chicks. We measured provisioning rates using audio recordings of nestlings begging. Brood size was the best predictor of provisioning frequency, with parents feeding larger broods more frequently than smaller ones. Delayed hatching did not reduce provisioning rate despite declining food abundance. Date and food abundance were unrelated to provisioning rate, suggesting no seasonal change in the quantity of food nestlings receive. However, provisioning frequency was informative about life-history strategies of Tree Swallows, showing that late breeders incurred the costs of deteriorating environmental conditions rather than passing these costs on to their offspring.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".