The role of multiple stressors in ranavirus-caused amphibian mortalities in Acadia National Park wetlands
Bibliographic record
Abstract
Recent studies suggest that multiple sublethal stressors compromise amphibian immune systems and increase susceptibility to disease. We examined two aspects of multiple stressors and incidence of ranavirus-caused amphibian mortalities in free-living amphibian populations: (1) among-pond differences in physical, chemical, and biological stressors that may exacerbate mortality events, and (2) temporal changes in within-pond stressors that coincide with mortality events. At the among-pond scale, we used principal components analysis and logistic regression followed by Akaike’s information criterion (QAICc) to identify stressors associated with disease incidence. Of the stressors we investigated, aluminum, temperature, and conductivity were most correlated with outbreaks, but it was unclear whether they increased ranavirus-caused mortality events. Sublethal stressors were difficult to isolate in the field and few were significantly associated with ranavirus across all breeding ponds. Our results suggest that each wetland, because of varied physical, biological, and chemical settings, will have its own suite of stressors that sublethally affect amphibians.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".