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Antigen and molecular testing using one swab: Lessons learned from a COVID-19 project

2025· article· en· W4416261219 on OpenAlexaff
Jodi Gilchrist, Nicole Smieja, Sarah Marttala, David Bulir, Mohammad R. Hasan, Marek Smieja

Bibliographic record

VenueDiagnostic Microbiology and Infectious Disease · 2025
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsMcMaster UniversityHamilton Health SciencesSt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsConcordanceLimitingAntigenAsymptomaticDiagnostic test

Abstract

fetched live from OpenAlex

• One swab used for both rapid antigen and RT-PCR testing improves efficiency. • Reflex RT-PCR testing of RAT swabs significantly increases SARS-CoV-2 detection. • RAT followed by PCR on the same swab showed 99.0 % concordance with standard PCR. • CT values from PCR tested RAT swabs are 2-5 cycles higher than direct PCR testing. • One-swab-two-test strategy reduces patient discomfort and resource burden. Rapid SARS-CoV-2 detection is essential in limiting transmission. We evaluated the performance of RT-PCR on the same nasopharyngeal swab used for Panbio antigen testing. High concordance with standard PCR and improved case detection—including asymptomatic infections—demonstrates this one-swab-two-test strategy enhances diagnostic yield while reducing patient discomfort and resource burden.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0040.003
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.005

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.

Opus teacher head0.076
GPT teacher head0.352
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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