Original article: novelty of Canadian manufacture nasopharyngeal swabs for collection of samples being tested for SARS-CoV-2 in a pandemic setting
Bibliographic record
Abstract
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.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".