Lack of molecular detection of frog virus 3-like ranavirus (FV3) in mosquitoes during natural outbreak and nonoutbreak conditions
Bibliographic record
Abstract
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.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".