Body condition reveals hidden correlations between co-infection and behavior in sunfish
Bibliographic record
Abstract
Abstract The role of parasites in maintaining consistent inter-individual differences in behavior (ie personality) is the subject of increasing study and debate. While behavioral differences may expose individuals differently to parasites, parasite infection can itself change host behavior, sometimes favoring the parasite’s own transmission. Furthermore, parasites can alter the functioning of energetically costly organs like the brain, thus affecting cognitive performance. However, relationships among infection, cognition, and behavior can be complex and difficult to interpret, especially in wild populations where individual health status is unknown. The inclusion of body condition as a fitness proxy may help reveal relationships between parasites and host traits that are otherwise masked. We examined relationships among host body condition, personality (ie exploration, boldness), cognition (ie aversive learning) and parasite density in wild-caught pumpkinseed sunfish (Lepomis gibbosus) naturally infected with endoparasites. Exploration in an open field test was repeatable in sunfish. Boldness, assessed using a shelter test, was not repeatable, but was correlated with exploration. Host exploration decreased with both increasing parasite density and decreasing body condition. Only individuals in relatively lower body condition displayed a negative relationship between parasite density and exploration, suggesting a pathologic effect of the parasites on the sunfish. Aversive learning was not influenced by co-infection. Our results show that body condition is important to consider when studying wild populations as some patterns observed between parasite density and host behavior were only revealed when body condition was taken into consideration.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".