West Nile Virus Infection Rates in Pooled and Individual Mosquito Samples
Bibliographic record
Abstract
The detection of West Nile virus (WNV) in mosquitoes by real-time RT-PCR provides valuable information on the epidemiology of the virus and identifies mosquito species that are potential vectors. Testing sets of pooled mosquitoes of the same species is logistically the easiest and most cost-effective approach for WNV testing; however, little information is available on how the results of small pooled sets relate to those of testing individual mosquitoes. During the 2002 outbreak, we compared pooled and individual samples of two mosquito species (Culex pipiens and Culex restuans) collected from three Health Unit regions in Ontario, Canada. Significantly more Cx. restuans were infected with WNV compared to Cx. pipiens. We show that with pool sizes of five individuals both MIR (minimum infection rates) and MLE (maximum likelihood estimation) values were acceptable in estimating infection rates.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".