Pan-Piscine Orthoreovirus (PRV) Detection Using Reverse Transcription Quantitative PCR
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Piscine orthoreovirus (PRV) infects farmed and wild salmon and trout species in North America, South America, Europe, and East Asia. PRV groups into three distinct genotypes (PRV-1, PRV-2, and PRV-3) that can vary in distribution, host specificity, and/or disease potential. Detection of the virus is currently restricted to genotype specific assays such that surveillance programs require the use of three assays to ensure universal detection of PRV. Consequently, herein, we developed, optimized, and validated a real-time reverse transcription quantitative PCR assay (RT-qPCR) that can detect all known PRV genotypes with high sensitivity and specificity. Targeting a conserved region at the 5' terminus of the M2 segment, the pan-PRV assay reliably detected all PRV genotypes with as few as five copies of RNA. The assay exclusively amplifies PRV and does not cross-react with other salmonid viruses or salmonid host genomes and can be performed as either a one- or two-step RT-qPCR. The assay is highly reproducible and robust, showing 100% agreement in test results from an inter-laboratory comparison between two laboratories in two countries. Overall, as the assay provides a single test to achieve highly sensitive pan-specific PRV detection, it is suitable for research, diagnostic, and surveillance purposes.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 it