Development and Validation of Reverse Transcription Loop- Mediated Isothermal Amplification (RT-LAMP) for Rapid Detection of SARS-CoV-2 in Human Samples
Bibliographic record
Abstract
Introduction: Coronavirus disease 2019 (COVID-19) known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly in the world and was declared a pandemic by the World Health Organization (WHO). COVID-19 displays a variety of symptoms, from mild flu to life-threatening conditions. Early detection of an infected person with rapid and sensitive tests is one of the crucial points to control the pandemic. Reverse transcriptase reaction followed by quantitative polymerase chain reaction (RT-qPCR) from nasopharyngeal swabs is the gold standard for molecular diagnosis of SARS-CoV-2. However, the technique has several limitations for application in point-of-care (POC) diagnostics.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".