Parasite load, rather than parasite presence, decreases upstream movement in Trinidadian guppies <i>Poecilia reticulata</i>
Bibliographic record
Abstract
Several factors influence whether an organism remains in its local habitat. Parasites can, for example, influence host movement by impacting their behavior, physiology, and morphology. In rivers, fish that swim efficiently against the current are able to maintain their position without being displaced downstream, a behavior referred to as positive rheotaxis. We hypothesized that both the presence and number of ectoparasites on a host would affect the ability of fish to avoid downstream displacement and thus prevent them from remaining in their habitat. We used the guppy-Gyrodactylus host-ectoparasite model to test whether parasite presence and parasite load had an effect on fish rheotaxis. We quantified rheotaxis of sham-infected and parasite-infected fish in a circular flow tank in the laboratory prior to infection and 5-6 days postinfection. Both parasite-infected and sham-infected individuals expressed similar levels of positive rheotaxis prior to infection and after infection. However, with increasing parasite numbers, guppies covered less distance in the upstream direction and spent more time in slower flow zones. These results suggest that higher numbers of Gyrodactylus ectoparasites negatively influence rheotactic movements. Further research is needed to understand the ecological and evolutionary implications of this ectoparasite on fish movement.
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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 | 0.000 |
| 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".