Simultaneous Detection and Differentiation between Wild-Type and Vaccine Measles Viruses by a Multiplex Real-Time Reverse Transcription-PCR Assay
Bibliographic record
Abstract
Measles is one of the most contagious viral respiratory infections and was declared to be eliminated from Canada in 1998; however, measles cases and outbreaks still occur every year through reintroduction from other parts of the world. Laboratory confirmation of measles virus (MV) RNA by real-time PCR provides a definitive diagnosis, and molecular analysis to determine the genotype is the only way to distinguish between wild-type and vaccine strains. This distinction is important since live attenuated vaccine strains are able to replicate in the patient and can be associated with rash and fever but are poorly transmissible, if at all. Prompt reporting of measles cases to local authorities, including differentiation between wild-type and vaccine strains, allows for optimal management and contact tracing. The development and validation of a multiplex real-time reverse transcription-PCR (rtRT-PCR) assay for the simultaneous detection and differentiation of the Moraten and Schwarz vaccine strains from presumptive wild-type MV in a format that can be easily implemented for high-throughput testing of patient samples are reported here. This assay is sensitive, specific, reproducible, and 100% accurate in comparison with the gold standard comparator assay.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".