Protocol to longitudinally quantify SARS-CoV-2 RNA in wastewater using RT-qPCR and pepper mild mottle virus normalization
Bibliographic record
Abstract
Wastewater surveillance allows severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection levels to be tracked in a community. Here, we present a protocol to longitudinally quantify SARS-CoV-2 RNA in wastewater using quantitative reverse-transcription PCR (RT-qPCR) and pepper mild mottle virus (PMMoV) normalization. We describe steps for the pasteurization of wastewater samples, solids separation, supernatant filtration, viral precipitation and concentration, and RNA extraction. We then detail procedures for RT-qPCR, viral concentration extrapolation, PMMoV normalization, and longitudinal analysis. This protocol has the potential to be used for surveillance of other microorganisms. For complete details on the use and execution of this protocol, please refer to Sanchez Jimenez et al.1
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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 | 0.001 |
| 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".