Life history and environment predict variation in testosterone across vertebrates
Bibliographic record
Abstract
Endocrine systems act as key intermediaries between organisms and their environments. This interaction leads to high variability in hormone levels, but we know little about the ecological factors that influence this variation within and across major vertebrate groups. We study this topic by assessing how various social and environmental dynamics influence testosterone levels across the entire vertebrate tree of life. Our analyses show that breeding season length and mating system are the strongest predictors of average testosterone concentrations, whereas breeding season length, environmental temperature, and variability in precipitation are the strongest predictors of within-population variation in testosterone. Principles from small-scale comparative studies that stress the importance of mating opportunity and competition on the evolution of species differences in testosterone levels therefore likely apply to the entire vertebrate lineage. Meanwhile, climatic factors associated with rainfall and ambient temperature appear to influence variability in plasma testosterone, within a given species. These results therefore reveal how unique suites of ecological factors differentially explain scales of variation in circulating testosterone across mammals, birds, reptiles, amphibians, and fishes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.012 |
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".