Causes and consequences of individual variation in the extent of post-juvenile moult in the blue tit<i>Cyanistes caeruleus</i>(Passeriformes: Paridae)
Bibliographic record
Abstract
Moult, comprising the growth or replacement of feathers in birds, is an energetically demanding process. As a \nresult, in many species, the extent of the post-juvenile moult can vary substantially. However, the reasons \nunderlying this variation remain poorly understood, and the potential life-history consequences of variation in \nmoult extent are even less clear. In the present study, we aimed to use individual-specific data to identify factors \naffecting the extent of the post-juvenile moult in a population of over 2500 blue tits Cyanistes caeruleus Linnaeus \n1758, and to assess the consequences of individual variation in moult extent on reproduction in the first year of \nlife. There was a substantial sex difference in post-juvenile moult extent, with males moulting more extensively \nthan females. Putative immigrant birds had moulted on average less than those born locally. However, there was \nlittle evidence of carry-over effects of the natal environment on moult extent because we found no relationship \nbetween moult extent and fledging date or nestling mass. Evidence that moult extent, and hence feather \nbrightness, affected subsequent reproductive success was limited. Moult extent had no effect on recruitment in \nmales, although female recruits had moulted significantly less than nonbreeders. Because it was not influenced \nby features of the natal environment, moult extent may not be an honest signal of individual quality in \nC. caeruleus. As a result, the potential consequences of variation in moult extent for fitness are likely to be \nsmall. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 116, 341–351.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".