Male and female cooperatively breeding fish provide support for the “Challenge Hypothesis”
Bibliographic record
Abstract
The idea that territorial aggression is regulated by androgens and that aggression itself can modulate androgen levels is well established in males. In many species, females also display aggressive behavior, yet little work has been conducted on the effects of female aggression on hormone levels. In this study, we compared the effects of a simulated territory intrusion (a method for testing the Challenge Hypothesis) on males and females of the fish, Neolamprologus pulcher. This cichlid fish from Lake Tanganyika is a particularly useful species to examine sex differences in the behavioral mediation of hormones as breeding pairs remain in a territory year round and both sexes defend this territory against conspecific and heterospecific intruders. In our study, both sexes indeed aggressively defended their territory against a simulated territory intruder. In response to intruders, both males and females displayed elevated levels of circulating 11-ketotestosterone, but only females exhibited increases in testosterone. Neither aggressing male nor female fish showed changes in estradiol levels compared to control (nonaggressing) fish. Residents were more aggressive than the intruders and won most of the interactions. However, residents (or winners) did not show higher hormone levels than intruders (or losers). We suggest that aggression commonly modulates androgen levels in both male and female teleost fish.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".