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Record W3047169130 · doi:10.1139/facets-2020-0007

Amphibian ranaviruses in Europe: important directions for future research

2020· article· en· W3047169130 on OpenAlexvenueno aff
Lewis J. Campbell, Alice H. Pawlik, Xavier A. Harrison

Bibliographic record

VenueFACETS · 2020
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsnot available
Fundersnot available
KeywordsRanavirusAmphibianBiologyHost (biology)MicrobiomeEcologyZoologyBioinformatics

Abstract

fetched live from OpenAlex

Ranaviruses are an emerging group of pathogens capable of infecting all cold-blooded vertebrates. In Europe, ranaviruses pose a particularly potent threat to wild amphibian populations. Since the 1980s research on amphibian-infecting ranaviruses in Europe has been growing. The wide distribution of amphibian populations in Europe, the ease with which many are monitored, and the tractable nature of counterpart ex situ experimental systems have provided researchers with a unique opportunity to study many aspects of host–ranavirus interactions in the wild. These characteristics of European amphibian populations will also enable researchers to lead the way as the field of host–ranavirus interactions progresses. In this review, we provide a summary of the current key knowledge regarding amphibian infecting ranaviruses throughout Europe. We then outline important areas of further research and suggest practical ways each could be pursued. We address the study of potential interactions between the amphibian microbiome and ranaviruses, how pollution may exacerbate ranaviral disease either as direct stressors of amphibians or indirect modification of the amphibian microbiome. Finally, we discuss the need for continued surveillance of ranaviral emergence in the face of climate change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.170
GPT teacher head0.422
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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