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Record W4396775888 · doi:10.3389/fpubh.2024.1344295

Original article: novelty of Canadian manufacture nasopharyngeal swabs for collection of samples being tested for SARS-CoV-2 in a pandemic setting

2024· article· en· W4396775888 on OpenAlexafffundabout
Sandra Palomino-Padilla, Guillermo Caceres-Cardenas, Rodrigo Calderón, Alex C-T. Ko, Lauren Garnett, Kaylie Doan, Patrick Chong, Hammerly Lino, Tatiana Cáceres, Teodor Veres, Claúdia C. dos Santos, Birgit Nielsen, César Ugarte‐Gil

Bibliographic record

VenueFrontiers in Public Health · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsUniversity of TorontoPublic Health Agency of CanadaNational Research Council Canada
FundersStrongNational Research Council CanadaPublic Health Agency of Canada
KeywordsPandemicSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakNoveltyMedicineVirologyPathologyInfectious disease (medical specialty)DiseasePsychology

Abstract

fetched live from OpenAlex

Objectives: The COVID-19 pandemic caused a global shortage of nasopharyngeal (NP) swabs, required for RT-PCR testing. Canadian manufacturers were contacted to share NP swab innovations. The primary objective was to determine whether novel NP test swabs were comparable to commercially available swabs regarding user characteristics, ability to collect a specimen, and diagnostic performance using RT-PCR testing. Methods: Participants were randomized by swab (test/control) and nostril (left/right). A calculated positive percent agreement ≥90% was considered successful. Mean Ct values of viral genes and housekeeping gene (RNase P) were considered similar if a Ct difference ≤ 2 between control and test group was obtained. There also was a qualitative assessment of swabs usability. Results: 647 participants were enrolled from Huaycan Hospital in Lima, Peru, distributed over 8 NP swabs brands. Seven brands agreed to share their results. There were no statistically significant differences between the test swabs of these 7 brands and control swabs. Conclusion: All the seven brands are comparable to the commercially available flocked swabs used for SARS-CoV-2 regarding test results agreement, ability to collect a specimen, and user characteristics.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.345
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes3
Has abstractyes

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