Evolutionary Endocrinology: Hormones as Mediators of Evolutionary Phenomena: An Introduction to the Symposium
Bibliographic record
Abstract
Hormones are agents of biological coordination that circulate systemically to signal diverse cells and tissues, thereby influencing nearly all aspects of the phenotype, including behavior, morphology, physiology, and life history. Hormonal phenotypes can be both heritable and subject to natural selection ( Bonier et al. 2009 ; McGlothlin et al. 2010 ; Ouyang et al. 2011 ; Pavitt et al. 2014 ; Cox et al. 2016 , this issue), yet hormones and endocrine pathways have rarely been integrated into evolutionary models and analyses. As Garland et al. (2016 , this issue) note this issue, “the seminal papers in modern evolutionary physiology scarcely mentioned the endocrine system.” Nevertheless, over the past two decades, the field of evolutionary endocrinology ( Zera et al. 2007 ; Nepomnaschy et al. 2009 ) has emerged not only as a means of understanding the evolution of the endocrine system itself ( Denver et al. 2009 ), but also as a framework for exploring the roles of hormones in shaping other evolutionary phenomena ( Ketterson and Nolan 1999 ; Adkins-Regan 2008 ; Husak et al. 2009 ; Williams 2012 ). Originally centered on classic quantitative genetic approaches to the study of hormonal phenotypes themselves ( Zera and Zhang 1995 ; Zera and Huang 1999 ), this field has expanded to include new ideas about the diverse roles of hormones as mediators of a variety of fundamental evolutionary phenomena. This theme of “hormones as mediators of evolutionary phenomena” serves as the organizing concept for this issue and can be illustrated by several examples drawn from the papers that follow.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".