Specialized morphology for a generalist diet: evidence for Liem's Paradox in a cichlid fish
Bibliographic record
Abstract
The stable isotope ratio and seasonal changes in diet of Alluaud's haplo Astatoreochromis alluaudi, a cichlid fish with massive pharyngeal jaws well known for its ability to process hard-bodied prey, are described. The diet of A. alluaudi was quantified in Lake Saka, Uganda, over a period of 30 months. Variation in physico-chemical variables (mean monthly rainfall, water temperature, turbidity and dissolved oxygen), as well as potential competitor density and food abundance, was measured throughout the second half of the study (14 months). Stomach contents and isotope analysis revealed a diet comprised mainly of fishes and insects, with a low contribution of molluscs (0-33%) in any given month. No correlation was detected between diet and either macroinvertebrate abundance or competitor abundance. The running average rainfall was positively related to the percentage of fish consumed per month. Although A. alluaudi exhibits an apparent molluscivorous trophic morphology in Lake Saka, molluscs did not appear to compose a major portion of its diet. Gradients of rainfall seemed to be the most important environmental predictor of diet choice in Lake Saka. These results are discussed with reference to Liem's Paradox that apparently morphologically specialized fishes often function as generalist feeders in the wild.
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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 | 0.001 |
| 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 | 0.001 |
| 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".