Non-breeding feather concentrations of testosterone, corticosterone and cortisol are associated with subsequent survival in wild house sparrows
Bibliographic record
Abstract
Potential mechanistic mediators of Darwinian fitness, such as stress hormones or sex hormones, have been the focus of many studies. An inverse relationship between fitness and stress or sex hormone concentrations has been widely assumed, although empirical evidence is scarce. Feathers gradually accumulate hormones during their growth and provide a novel way to measure hormone concentrations integrated over time. Using liquid chromatography-tandem mass spectrometry, we measured testosterone, corticosterone and cortisol in the feathers of house sparrows (Passer domesticus) in a wild population which is the subject of a long-term study. Although corticosterone is considered the dominant avian glucocorticoid, we unambiguously identified cortisol in feathers. In addition, we found that feathers grown during the post-nuptial moult in autumn contained testosterone, corticosterone and cortisol levels that were significantly higher in birds that subsequently died over the following winter than in birds that survived. Thus, feather steroids are candidate prospective biomarkers to predict the future survival of individuals in the wild.
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 | 0.000 | 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".