DEVELOPMENT OF A ONE-STEP DUPLEX RT-qPCR FOR THE QUANTIFICATION OF PHOCINE DISTEMPER VIRUS
Bibliographic record
Abstract
Worldwide, stranded marine mammals and the network personnel who respond to marine mammal mortality have provided much of the information regarding marine morbillivirus infections. An assay to determine the amount of virus present in tissue samples would be useful to assist in routine surveying of animal health and for monitoring large-scale die-off events. False negatives from poor-quality samples prevent determination of the true extent of infection, while only small amounts of tissue samples or archived RNA may be available at the time of collection for future retrospective analysis. We developed a one-step duplex real-time reverse transcriptase-quantitative-PCR assay (RT-qPCR) based on Taqman probe technology to quantify phocine distemper virus (PDV) isolated from an outbreak in harbor (Phoca vitulina concolor) and gray seals (Halichoerus grypus) along the northeast US coast in 2006. The glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) gene was selected to assess RNA quality. This duplex assay is specific for PDV and sensitive through a range of 10(0) to 10(9) copies ds-plasmid DNA. For the GAPDH target, the reaction in duplex amplified 10(0) to 10(9) copies of ds-plasmid DNA and was detectable in multiple seal species. This assay reduced the likelihood of false negative results due to degradation of tissues and well-to-well variability while providing sensitive and specific detection of PDV, which would be applicable in molecular epidemiologic studies and pathogen detection in field and laboratory investigations involving a variety of seal species.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".