Territorial behaviour and conflict management in a semi-social cichlid fish, Neolamprologus caudopunctatus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Conflict solving strategies can prevent fights from escalating and reduce the costs of aggressive encounters. Having the capacity to efficiently assess an opponent’s fighting abilities before fully committing to a fight is a useful social skill. Here, we conducted two experiments to investigate how a colony living, cichlid species, Neolamprologus caudopunctatus , changes its aggressive behaviour when faced with familiar vs unfamiliar opponents. First, we staged size matched, same-sex, dyadic resource contests and found that fights were always of low-intensity with neither familiarity nor sex influencing how quickly the conflict ended. Second, we explored the dual defence of mated territorial pairs together defending their territory boundaries against other pairs, either familiar or unfamiliar ones, and discovered that fights between two pairs were more vigorous, and that unfamiliar neighbouring pairs were attacked significantly more often than familiar pairs. We also observed that dark bars sometimes appeared on the sides of contestant’s bodies, and that these bars were far more common in winners than in losers, suggesting that these might be visual signals of dominance. However, conflicts where contestants displayed bars were of longer duration than those without. Taken together, our results further advance our understanding of territoriality and conflict resolution strategies and set the stage for future studies focusing on how animals manage to co-exist in closely aggregated breeding territories and to form colonies.
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.
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 | 0.000 |
| 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 it