Macroevolutionary Patterning in Glucocorticoids Suggests Different Selective Pressures Shape Baseline and Stress-Induced Levels
Bibliographic record
Abstract
Glucocorticoid (GC) hormones are important phenotypic mediators across vertebrates, but their circulating concentrations can vary markedly. Here we investigate macroevolutionary patterning in GC levels across tetrapods by testing seven specific hypotheses about GC variation and evaluating whether the supported hypotheses reveal consistent patterns in GC evolution. If selection generally favors the "supportive" role of GCs in responding effectively to challenges, then baseline and/or stress-induced GCs may be higher in challenging contexts. Alternatively, if selection generally favors "protection" from GC-induced costs, GCs may be lower in environments where challenges are more common or severe. The predictors of baseline GCs were all consistent with supportive effects: levels were higher in smaller organisms and in those inhabiting more energetically demanding environments. During breeding, baseline GCs were also higher in populations and species with fewer lifetime opportunities to reproduce. The predictors of stress-induced GCs were instead more consistent with the protection hypothesis: during breeding, levels were lower in organisms with fewer lifetime reproductive opportunities. Overall, these patterns indicate a surprising degree of consistency in how some selective pressures shape GCs across broad taxonomic scales; at the same time, in challenging environments selection appears to operate on baseline and stress-induced GCs in distinct ways.
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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 | 0.001 | 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) | 0.001 | 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".