Liver size reveals social status in the African cichlid <i>Neolamprologus pulcher</i>
Bibliographic record
Abstract
Wild groups (n = 167) of the cooperatively breeding Lake Tanganyika cichlid, Neolamprologus pulcher, were used to investigate how social status and sex influence liver investment. In contrast to expectations, males and females (controlling for body size) had similar liver investment and subordinates (both sexes) had relatively larger livers compared with dominants. Three hypotheses were considered for why social status results in liver size disparity: liver mass might reflect status-dependent differences in (1) energy expenditure, (2) energy storage and (3) energy acquisition. First, dominants performed more energetically costly behaviours (e.g. social policing and care) compared with subordinates, supporting the notion that energy expenditure drives liver investment. Moreover, dominants in large groups (with many subordinates to monitor) and those holding multiple territories (with large areas to patrol), tended to have smaller livers. Second, subordinates did not appear to use the liver as a strategic energy storage organ. In laboratory and field experiments, subordinates ascending in rank had similar or larger livers during periods of rapid growth compared with non-ascending controls. Third, although subordinates fed more frequently than dominants, a negative relationship was found between feeding rates and liver size. Hence, these results contrast with previous liver studies and suggest that liver investment patterns were linked to status-driven differences in energy expenditure but not to energy intake or storage in N. pulcher.
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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 | 0.001 | 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) | 0.001 | 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".