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Record W3093301400 · doi:10.1139/facets-2020-0024

Lack of molecular detection of frog virus 3-like ranavirus (FV3) in mosquitoes during natural outbreak and nonoutbreak conditions

2020· article· en· W3093301400 on OpenAlexvenueno aff
Nicole A. Lopez Vargas, Laura Adamovicz, Brittany Willeford, Brian F. Allan, Matthew C. Allender

Bibliographic record

VenueFACETS · 2020
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsnot available
Fundersnot available
KeywordsRanavirusOutbreakBiologyAedes albopictusZoologyCulexAedesVirologyEcologyAmphibianLarvaAedes aegypti

Abstract

fetched live from OpenAlex

Ranaviruses are worldwide pathogens of ectothermic vertebrates that can threaten herptile conservation efforts. Identifying transmission routes is critical for understanding disease ecology and promoting species conservation. Frog virus 3 (FV3) DNA was detected in mosquitoes during a ranavirus outbreak in semicaptive box turtles, but the role that insect vectors play under natural conditions is unknown. To address this knowledge gap, we collected mosquito species known to take blood meals from reptiles and amphibians ( Aedes canadensis, Culex erraticus, Culex territans, and Uranotaenia sapphirina) from mid-May to early August, 2014, at four study sites in Vermilion County, Illinois, two of which had historic or ongoing FV3 outbreaks in box turtles and amphibians. Mosquitoes were batched by date and species, DNA was extracted, and quantitative polymerase chain reaction was performed for detection of FV3. FV3 was not detected despite one of the sites having an active FV3 outbreak during the study period. Our findings indicate that FV3 detection is uncommon in mosquitoes during outbreak and nonoutbreak conditions at these sites in Illinois. Thus, we cannot establish that mosquitoes contribute to transmission during natural mortality events without performing further studies.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

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

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 head0.295
Teacher spread0.271 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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