Towards the validation of endogenous steroid testing in wildlife hair
Bibliographic record
Abstract
Abstract Hair analysis is emerging as a popular tool to examine stress and reproduction hormone levels in wild mammals. The reliability of this approach, however, depends on an understanding of steroid hormone incorporation into hair as well as appropriate validations. We reviewed studies that have examined steroid hormones in wildlife hair with the goal of summarizing the analytical, physiological, and biological evidence that this approach is meaningful. Accordingly, we differentiated among validations aimed at evaluating the reliability of the analytical method versus those designed to assess whether hormone levels in hair reflect physiologically meaningful processes in the target species. Our literature survey revealed that endogenous steroids have been examined in hair from 40 species of nonhuman animals across seven mammalian classes. Although the majority (85%) of 72 studies reported analytical validations of the method, physiological validations have only been reported for five species. Moreover, results of physiological validations were inconsistent among studies. This highlights the need for further research, carefully designed to differentiate between the multiple purported models of steroid incorporation into hair in species with different types of hair and different hair growth patterns. To complement our review of published studies, we present new data supporting a positive relationship between levels of the steroid, cortisol, in hair and blood across eight mammalian species. In addition, we present novel results from a laboratory‐based study showing variable hair growth in genetically identical laboratory mice that were kept under controlled conditions. Synthesis and applications . Collectively, this Review reveals substantial progress towards the validation of stress hormone assays in hair from a variety of wildlife species. Further validations of reproductive steroids, combined with appropriate physiological validations, would expand the potential applications of hair analyses in wildlife research. As a key example, physiological data can provide mechanistic insights into species’ responses to change and may therefore contribute to conservation planning.
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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 | 0.001 | 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) | 0.000 | 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".