Increased detection of rotavirus using a real time reverse transcription‐polymerase chain reaction (RT‐PCR) assay in stool specimens from children with diarrhea
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Six-hundred and twenty-six stool specimens collected from children with diarrhea over a 12-month period were tested for rotavirus using a real time reverse transcription-polymerase chain reaction (RT-PCR) assay, a conventional nested PCR assay and by electron microscopy (EM). A fragment of 87 bp in a highly-conserved region of non-structural protein 3 (NSP3) in rotavirus genome was amplified by a single-step RT-PCR protocol in a closed-tube system. Rotavirus was detected in 123 samples (20%) with the real time RT-PCR assay, 113 samples (18%) with the nested-PCR assay, and 79 samples (13%) with EM. Using serial diluted nucleic acid extract, we compared the sensitivity of real time RT-PCR with conventional RT-PCR and conventional nested PCR assays. Real time RT-PCR was two to four logs more sensitive than the conventional assays. The reaction time required for the RT-PCR assay is about half the time required for the conventional nested-PCR. The real time RT-PCR assay is both simple and rapid with advantages including enhanced sensitivity and a lower risk for cross-contamination making it a useful tool for the detection of rotavirus in various situations including sporadic gastroenteritis, outbreaks, and environmental investigations. G(1) was the predominant type (89%), followed by G(2) (10%), and G(4) (1%). No rotavirus of G(3), G(8), and G(9) types were found. The peak season for rotavirus infection was January to May in northern Alberta.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it