Bayesian Evaluation of Solana HSV 1+2/VZV Assay Compared to Viral Culture and Commercial PCR Assay for Cutaneous or Mucocutaneous Specimens
Bibliographic record
Abstract
Results from the Solana HSV 1+2/VZV assay for the detection of herpes simplex virus 1 (HSV-1), HSV-2, and varicella-zoster virus (VZV) in cutaneous or mucocutaneous specimens were compared with that of viral culture and a commercial PCR assay (RealStar alpha herpesvirus PCR kit). Three hundred two mucocutaneous specimens, for which HSV-1, HSV-2, or VZV viral culture or PCR detection have been requested, were randomly selected and prospectively processed on the Solana assay and viral culture or the RealStar assay. Discordant results between culture and the Solana assay were further analyzed using the RealStar assay. A Bayesian latent class model was developed to estimate the performance of each method. Viral culture detected 123 positive specimens (85 HSV-1, 36 HSV-2, and 2 VZV), while the Solana assay detected 27 additional positive specimens (4 HSV-1, 11 HSV-2, and 12 VZV), in agreement with the RealStar PCR assay. The estimated sensitivity of the Solana assay according to our model was 92.7% to 98.7%, 87.1% to 97.8%, and 94.9% to 98.8% (95% confidence interval [CI]) for HSV-1 HSV-2, and VZV, respectively, while the estimated sensitivity of viral culture was 85.2% to 95.0%, 73.6% to 89.6%, and 30.9% to 45.8% (95% CI), respectively. A nonsignificant tendency toward increased sensitivity was noted for the Solana assay compared with culture for HSV-1 and HSV-2, and the Solana assay was significantly more sensitive than culture for the detection of VZV. The Solana assay performed comparably to the RealStar assay. Processing time was reduced with the Solana assay compared with viral culture.
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 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 | 0.033 | 0.080 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".