Data for: Parasite prevalence depends on female preference: Integrating parasite-mediated sexual selection and infectious disease dynamics
Bibliographic record
Abstract
If ornament quality advertises heritable resistance to a directly transmitted parasite, female preference for males with higher quality ornaments could reduce parasite prevalence via two pathways. Preference for, and thus more contact with, resistant males should: 1) change parasite transmission opportunities; and 2) increase offspring parasite resistance. Here, we used data and parameterized a SIR model to test the hypothesis that, across populations of guppies (Poecilia reticulata), the strength of female preference negatively correlates with the prevalence of directly transmitted gyrodactylids. Female guppies exhibit between-population variation in preference for males with larger orange ornaments that are heritable and forecast resistance. Using 89 prevalence estimates from 10 populations, and controlling for ecological covariates, we found that populations with significant female preference had lower prevalence than those without. Our theoretical model inferred that preference affects prevalence largely by affecting offspring parasite resistance. Female preference can thus drive the dynamics of ordinary infectious diseases.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.065 | 0.007 |
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".