Ranavirus infection in northern leopard frogs: the timing and number of exposures matter
Bibliographic record
Abstract
Abstract Transmission is a central feature of pathogen fitness and influences host population dynamics. The form and magnitude of transmission rates determine whether a pathogen establishes itself in a host population and the proportion of a population that becomes infected. While the effects of environmental variation on pathogen transmission dynamics have received substantial attention, the time and number of pathogen exposure in relation to host ontogeny has been relatively less investigated. Such understanding is particularly important in host species exhibiting distinct life‐history stages such as amphibians as this temporal variation in infection modulates transmission trends at the population level. We investigated the role of the timing and number of ranavirus (FV3) exposures on infection rate and mortality patterns inLithobates pipienstadpoles in a two‐step laboratory experiment with four treatments: individuals exposed as hatchlings but not as tadpoles, individuals not exposed as hatchlings but exposed as tadpoles, individuals exposed both as hatchlings and tadpoles and individuals that were never exposed. Our results indicate that individuals exposed twice presented higher infection and mortality rates over individuals exposed only once (infection: 40 vs. 16%; mortality: 16.8 vs. 8.1%, respectively). Among individuals exposed only once, but at different time, no difference in mortality was observed; yet, dissimilar infection rates indicate a differential capacity to carry and transmit virions among various developmental stages suggesting distinct epidemiological roles. Our results stress the importance of considering stage‐dependent host susceptibility to better understand infection patterns and transmission dynamics and advocate its incorporation in models and field study designs.
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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".