Assessing multiplex tiling PCR sequencing approaches for detecting genomic variants of SARS-CoV-2 in municipal wastewater v1
Bibliographic record
Abstract
In this work, we aim to access the performance of three different multiplex primer schemes, i.e. Swift amplicon SARS-CoV-2 panel (150bp amplicons), ARTIC V3 panel (400bp amplicons), and SARS-CoV-2 midnight panel (1200bp amplicons), for metatranscriptomic sequencing of SARS-CoV-2 for influent wastewater and primary sludge. This protocol is adapted from the Swift amplicon™ SARS-COV-2 protocol (150bp amplicon), ARTIC V3 protocol (400bp amplicon), and "midnight" protocol (1200bp amplicon). Sequencing libraries are prepared with 1) Oxford Nanopore Ligation Sequencing Kit (SQK-LSK109) with Native Barcoding kit (EXP-NEB104 and EXP-NEB114), or 2) NEBNext® Ultra™ II DNA Library Prep Kit for Illumina® with NEBNext® Multiplex Oligos for Illumina®. Links to the protocols are: Swift amplicon protocol (150bp): https://swiftbiosci.com/swift-amplicon-sars-cov-2-panel/ ARTIC V3 protocol (400bp): https://www.protocols.io/view/ncov-2019-sequencing-protocol-v3-locost-bh42j8ye?version_warning=no "midnight" protocol V4 (1200bp): dx.doi.org/10.17504/protocols.io.bh7hj9j6
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".