Seasonal changes in sexual size dimorphism in northern chamois
Bibliographic record
Abstract
In many polygynous mammals, sexual size dimorphism (SSD) is thought to have evolved through sexual selection, because larger males prevail in male–male combat and secure access to estrous females. SSD is often correlated with higher age-specific mortality of males than of females, possibly because males have higher nutritional requirements and riskier growth and reproductive tactics. In adult chamois Rupicapra rupicapra, sexual dimorphism in skeletal size was about 5%, but dimorphism in body mass was highly seasonal. Males were about 40% heavier than females in autumn but only 4% heavier in spring. For a given skeletal size, males were heavier than females only in autumn. Chamois sexual dimorphism appears mainly due to greater summer accumulation of fat and muscle mass by males than by females. Male mass declines rapidly during the rut. Limited dimorphism in skeletal size combined with substantial but seasonal dimorphism in mass has not been reported in other sexually dimorphic ungulates. Seasonal changes in mass allow males to achieve large size for the rut by accumulating body resources during summer. The use of these resources over the rut may reduce mortality associated with sustaining a large size over the winter.
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 | 0.000 |
| 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) | 0.003 | 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".