Multi-tool diagnosis of an outbreak of ranavirosis in amphibian tadpoles in the Canadian boreal forest
Bibliographic record
Abstract
Investigation of mortalities in isolated wild amphibian populations presents diagnostic difficulties that can hinder reaching a definitive diagnosis for the cause of death. Disease can only be diagnosed when pathogen presence (e.g. detection by PCR) is linked to tissue lesions (histopathology) in the host. We report a 2-site outbreak of ranavirosis in wild anuran tadpoles in the boreal forest of Wood Buffalo National Park, Canada, diagnosed by histologic and molecular techniques. Mortalities occurred in wood frog Rana sylvatica tadpoles and boreal chorus frog Pseudacris maculata tadpoles. Lack of mortality in sympatric Canadian toad Bufo (Anaxyrus) hemiophrys tadpoles suggested lower disease susceptibility in this species. In the former 2 species, ranavirosis was diagnosed based on consistent histopathology, immunohistochemistry (IHC), in situ hybridization (ISH), and quantitative PCR results. The most common histopathologic lesion present in wood and boreal chorus frog tadpoles was necrosis of the skin, oral mucosa, renal tubular epithelium, renal hematopoietic tissue, and branchial epithelium. Mild hepatic and pancreatic necrosis and rare intracytoplasmic inclusion bodies in hepatocytes were less common. Skeletal and connective tissues in budding limbs often had multifocal to coalescing necrosis and were intensely positive for ranavirus, with IHC staining even in areas where no obvious necrosis could be observed. Abundant IHC and ISH staining in actively growing tissues support a link between disease emergence and amphibian developmental stage. Our findings provide a definitive diagnosis of ranavirosis in free-living amphibians and highlight the effectiveness of multi-tool approaches to mortality investigation and elucidation of pathogenesis of ranavirosis in wild 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".