The influence of status and the social environment on energy stores in a social fish
Bibliographic record
Abstract
This study explores how muscle and liver energy stores are linked with social status and the social environment in Neolamprologus pulcher, a cooperatively breeding fish that lives in colonies comprised of up to 200 distinct social groups. Subordinate muscle energy stores were positively correlated with the number of neighbouring social groups in the colony, but this pattern was not observed in dominant N. pulcher. Furthermore, liver energy stores were smaller in dominants living at the edge of the colony compared with those living in the colony centre, with no differences among subordinates in liver energy stores. Subordinate N. pulcher may build up large energy stores in the muscles to fuel rapid growth after dispersal, which could occur more frequently in high-density environments. Dominant N. pulcher may use the more easily mobilized energy stores in the liver to fuel daily activities, which could be more energetically demanding on the edge of the colony as a result of the increased predation defence needed on the edge. Overall, this study demonstrates that both subordinate and dominant physiology in N. pulcher varies with characteristics of the social environment. Furthermore, dominant and subordinate energy storage strategies appear to differ due to status-dependent variation in daily activities and variation in the need to prepare for future reproductive or dispersal opportunities.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".