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Record W3088387760 · doi:10.1139/facets-2020-0011

Ranaviruses in captive and wild Australian lizards

2020· article· en· W3088387760 on OpenAlexvenueno aff
Alicia Maclaine, Wytamma Wirth, Donald T. McKnight, Graham Burgess, Ellen Ariel

Bibliographic record

VenueFACETS · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
FundersJames Cook University
KeywordsRanavirusBiologyAmphibianIridovirusLizardZoologyEpizooticEcologyVirusVirology

Abstract

fetched live from OpenAlex

Ranaviral infections have been associated with mass mortality events in captive and wild amphibian, fish, and reptile populations globally. In Australia, two distinct types of ranaviruses have been isolated: epizootic haematopoietic necrosis virus in fish and a Frog virus 3-like ranavirus in amphibians. Experimental studies and serum surveys have demonstrated that several Australian native fish, amphibian, and reptile species are susceptible to infection and supported the theory that ranavirus is naturally circulating in Australian herpetofauna. However, ranaviral infections have not been detected in captive or wild lizards in Australia. Oral-cloacal swabs were collected from 42 wild lizards from northern Queensland and 83 captive lizards from private collections held across three states/territories. Samples were tested for ranaviral DNA using a quantitative PCR assay. This assay detected ranaviral DNA in 30/83 (36.1%) captive and 33/42 (78.6%) wild lizard samples. This is the first time molecular evidence of ranavirus has been reported in Australian lizards.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.242
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2020
Admission routes1
Has abstractyes

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