Vocal performance varies with habitat quality in black-capped chickadees (Poecile atricapillus)
Bibliographic record
Abstract
Abstract In vocal learners, such as songbirds, the ability to maintain an internal acoustic structure between songs during a chorus seems to be positively correlated with the singer’s condition and may, therefore, represent a reliable measure of the singer’s condition. For instance, some internal ratios in the black-capped chickadee ( Poecile atricapillus) fee-beesong are more stable in the song of dominant males than in the song of subordinate males, suggesting that dominant birds are better at maintaining the internal song structure than subordinate males. Habitat quality is also known to affect the behaviour of this species. Birds settling in young forest have a lower song output and lower reproductive success than birds occupying mature forests, and it is suggested that those differences arise from differential food availability across habitats. As recent studies suggest that song performance can be altered by food limitation at the time of song learning, we explore whether habitat quality has a similar effect on the ability to maintain internal song structure as does social rank. We paired males by similar social rank, but who occupied different habitat types, and compared the consistency of male song within his dawn chorus. The ability to maintain an internal song structure of birds occupying young forests was consistently lower than birds occupying mature forests. Our results demonstrate that the same difference that exist in song structure between male differing in social rank also exist between males differing in the habitat in which they sing.
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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 | 0.001 | 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) | 0.001 | 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".