Development of a rapid, internally controlled, two target, real-time RT-PCR for detection of rubella virus
Bibliographic record
Abstract
Rubella surveillance in elimination setting relies on rapid molecular detection of the virus. In this study a multiplex real-time RT-PCR assay for the detection of rubella virus was validated. The assay includes three independent probes with unique reporter dyes for the simultaneous detection of the rubella viral coding regions for envelope glycoprotein E1 and non-structural p150 protein, and an endogenous control (human RNaseP). Using dilution series of synthetic RNAs, the limits of detection were determined to be at least 50 copies of rubella RNA. The assay is reproducible with low intra-assay and inter-assay coefficients of variation for both the E1 and the p150 targets. After testing 62 confirmed rubella positive and 165 rubella negative archival clinical samples, the sensitivity and specificity of the multiplex assay were 98.4 and 100 %, respectively. No cross reactivity was identified with clinical specimens positive for eleven other viruses. This multiplex assay successfully detected nine viral genotypes including the predominant genotypes 1E, 1G, 1J, and 2B as well as the 1a vaccine genotype.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 0.001 |
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".