Positive association between experimental cortisol increases and cage-measures of feeding behavior in wild-caught gerbils
Bibliographic record
Abstract
Abstract Glucocorticoid hormone levels vary within a forager based upon environmental stressors such as illumination and riskier habitats, and a forager’s response to environmental variables depends upon its glucocorticoid levels. Here, we report on a laboratory experiment in which we manipulated cortisol in Allenbyi’s gerbils ( Gerbillus andersoni allenbyi ) to test the relationship between cortisol and behavior. We then quantified the resulting blood cortisol levels and feeding behavior in gerbils. Thirty gerbils were injected with 21-day slow-release cortisol pellets drawn from 5 different dosages. We quantified the physiological response to pellet implantation in gerbils by measuring cortisol level in blood serum using ELISA (Enzyme Linked Immunosorbent Assay). We fed gerbils daily by mixing millet seeds into the sand inside rodent cages and measured the remaining seeds the following day to quantify feeding efforts. Some evidence supports that subcutaneous supplementation of glucocorticoids (GCs) in the gerbils led to higher blood serum levels. Cortisol levels varied according to time period of measurement. Gerbils that received lower dosages consumed most of the food presented to them when compared to those receiving the highest doses. In this manner, we delineate a pattern on cortisol hormone level variation over time following dosing and consequences in feeding behavior.
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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 | 0.001 |
| 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".