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
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".