Effects of weather and social factors on hormone levels in the European badger (Meles meles)
Bibliographic record
Abstract
Animals in the wild continually experience changes in environmental and social conditions, which they respond to with behavioural, physiological and morphological adaptations related to individual phenotypic quality. During unfavourable environmental conditions, reproduction can be traded-off against self-maintenance, mediated through changes in reproductive hormone levels. Using the European badger (Meles meles) as a model species, we examine how testosterone in males and oestrogens in females respond to marked deviations in weather from the long-term mean (rainfall and temperature, where badger earthworm food supply is weather dependent), and to social factors (number of adult males and females per social group and total adults in the population), in relation to age, weight and head-body length. Across seasons, testosterone levels correlated postively with body weight and rainfall variability, whereas oestrone correlated positively with population density, but negatively with temperature variability. Restricting analyses to the mating season (spring), heavier males had higher testosterone levels and longer females had higher oestradiol levels. Spring oestrone levels were lower when temperatures were above normal. That we see these effects for this generally adaptive species with a broad bioclimatic niche serves to highlight that climatic effects (especially with the threat of anthropogenic climate change) on reproductive physiology warrant careful attention in a conservation context.
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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 | 0.000 |
| 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".