Natal nutrition and the habitat distributions of male and female black-capped chickadees
Bibliographic record
Abstract
In nonmigratory passerines, dispersing juveniles may compete to settle in suitable habitat patches, leading to phenotypic assortment across habitat types. We compared the past natal nutrition of 1st year black-capped chickadees (Poecile atricapillus (L., 1766)) that settled in two adjacent patches known to differ in suitability as breeding habitat: a mature mixed forest (good habitat) versus a young regenerating forest dominated by conifers (poor habitat). The past natal nutrition of recruits was estimated by measuring growth bars on their tail feathers grown as nestlings; growth bars were positively associated with body condition of birds at the time of capture, suggesting this measure may accurately reflect individual condition. Males that settled in either habitat had similar growth bar size; however, females that settled in the mature habitat had slightly larger growth bars than those in poor habitat. Individuals occupying the disturbed site were of similar size and in similar body condition compared with those that settled in the mature forest. These findings suggest that females may be more discriminating of habitat quality than males during natal dispersal, matching what is known about chickadee dispersal behaviour. We suggest that males are distributed with a non-ideal despotic distribution, whereas females are distributed with an ideal despotic distribution.
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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 | 0.000 | 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) | 0.001 | 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".