Development and Evaluation of a Multitarget Real-Time Taqman Reverse Transcription-PCR Assay for Detection of the Severe Acute Respiratory Syndrome-Associated Coronavirus and Surveillance for an Apparently Related Coronavirus Found in Masked Palm Civets
Bibliographic record
Abstract
Severe acute respiratory syndrome (SARS)-associated coronavirus (SARS-CoV) is the etiological agent of SARS. It is believed that SARS-CoV originates from wild animals. We have developed a multitarget real-time Taqman reverse transcription-PCR (RT-PCR) assay for the quantitative detection of SARS-CoV. The sequences of the Taqman probes with a minor groove binder and the corresponding primers were based on the sequences of the N gene, open reading frame (ORF) 3, and ORF 8. The overall linear range of this assay was from at least 10(1) to 10(6) copies per reaction, and the detection limit could reach less than 10 copies per reaction. The quantification results for SARS-CoV from cell culture correlated well with those of the RT-PCR by using any two of the three sets of primer and probe used in this assay. However, the results of quantification of SARS-CoV obtained by using a few available throat swab specimens from SARS patients and the N gene as the target were almost 10 times higher than those obtained by using ORF 3 and ORF 8. Using this assay, we also detected an apparently SARS-CoV-related coronavirus in the throat swab specimens from masked palm civets in the west part of Hubei Province, People's Republic of China.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".