Detection of influenza <scp>C</scp> virus by a real‐time <scp>RT</scp>‐<scp>PCR</scp> assay
Bibliographic record
Abstract
BACKGROUND: Influenza C virus can cause both upper and lower respiratory tract infections and has been reported to be prevalent in children. However, these infections have been under-diagnosed, and epidemiological data available are limited due to the lack of convenient detection assays. OBJECTIVE: Design and validate a real-time reverse-transcriptase PCR (rt RT-PCR) assay for the detection of influenza C. STUDY DESIGN: Respiratory samples from two primary settings, namely, children who were hospitalized or seen in the emergency department, and respiratory outbreaks for which no other viral etiology was found were used for the detection of influenza C. RESULTS AND CONCLUSIONS: The assay was sensitive and specific for the detection of influenza C. Eleven of 474 (2·32%) patients, all less than 10 years of age, were positive for influenza C. The strains clustered into two lineages, namely C/Kanagawa and C/Sao Paulo, based upon sequencing of the hemagglutinin-esterase gene. Epidemiological data showed that a higher proportion of influenza C infections occur in younger children and during the winter months. This is the first report of the detection of influenza C in Alberta, Canada, and suggests that the detection of this virus should be included in respiratory virus testing panels.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".