Evaluation of Ortho VITROS and Roche Elecsys S and NC Immunoassays for SARS-CoV-2 Serosurveillance Applications
Bibliographic record
Abstract
Seroprevalence studies like the U.S. Nationwide Blood Donor Seroprevalence Study (NBDS) have been critical in monitoring SARS-CoV-2 epidemic activity. These studies rely on serological assays to detect antibodies indicating prior infection. It is critical that the assays and testing algorithms used in seroprevalence studies have adequate performance (high sensitivity, high specificity, ability to discriminate vaccine-induced and infection-induced antibodies, etc.), as well as appropriate characteristics to support large-scale studies, such as high throughput and low cost. In this study we evaluated the performance of Ortho's anti-nucleocapsid assay as a replacement for the Roche anti-nucleocapsid assay and compared performance of parallel anti-spike and anti-nucleocapsid testing on both platforms. These data demonstrate similar performance of the Ortho and Roche anti-nucleocapsid assays and that parallel anti-spike and anti-nucleocapsid testing on either platform could be used for serosurveillance applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".