Aggression and plasma testosterone in male golden hamsters (<i>Mesocricetus</i> <i>auratus</i>) in response to encounters with receptive vs. nonreceptive females
Bibliographic record
Abstract
Exposure to sexual stimuli can lead to increased aggression in male mammals, but it is unclear whether the aggression is related to the receptiveness of the females. Interactions with receptive females elicit testosterone (T) pulses that are important for sexual behaviors. We investigated the effects of male–female interactions on subsequent aggressive behaviors and T responses in the golden hamster (Mesocricetus auratus (Waterhouse, 1839)). Three groups (n = 18, 17, and 18) of males were exposed to receptive females, nonreceptive females, and blank (control), respectively. Then, we randomly chose eight animals from each group and measured their aggression toward an unfamiliar male conspecific; the remaining 29 males were used for a T assay (to avoid effects of aggression on T levels). The results show that interactions with females led to significantly higher male aggression and T levels than were found in control males. The increased aggression was not related to the receptiveness of the females, but receptive females elicited higher levels of T in males than nonreceptive females. Our findings suggest that the elevated aggression following the sexual encounter may serve to defend the female, by enhancing the ability of males to exclude other males from the vicinity of females, whereas the post-encounter T release may serve to assist mating behaviors and reproductive success.
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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".