Evaluation of a Commercial Culture-Free Neutralization Antibody Detection Kit for Severe Acute Respiratory Syndrome-Related Coronavirus-2 and Comparison With an Antireceptor-Binding Domain Enzyme-Linked Immunosorbent Assay
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Bibliographic record
Abstract
Abstract Background Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) surrogate neutralization assays that obviate the need for viral culture offer substantial advantages regarding throughput and cost. The cPass SARS-CoV-2 Neutralization Antibody Detection Kit (GenScript) is the first such commercially available assay that detects antibodies that block receptor-binding domain (RBD)/angiotensin-converting enzyme (ACE)-2 interaction. We aimed to evaluate cPass to inform its use and assess its added value compared with anti-RBD enzyme-linked immunosorbent assays (ELISAs). Methods Serum reference panels comprising 205 specimens were used to compare cPass to plaque-reduction neutralization test (PRNT) and a pseudotyped lentiviral neutralization (PLV) assay for detection of neutralizing antibodies. We assessed the correlation of cPass with an ELISA detecting anti-RBD immunoglobulin (Ig)G, IgM, and IgA antibodies at a single timepoint and across intervals from onset of symptoms of SARS-CoV-2 infection. Results Compared with PRNT-50, cPass sensitivity ranged from 77% to 100% and specificity was 95% to 100%. Sensitivity was also high compared with the pseudotyped lentiviral neutralization assay (93%; 95% confidence interval [CI], 85–97), but specificity was lower (58%; 95% CI, 48–67). Highest agreement between cPass and ELISA was for anti-RBD IgG (r = 0.823). Against the pseudotyped lentiviral neutralization assay, anti-RBD IgG sensitivity (99%; 95% CI, 94–100) was very similar to that of cPass, but overall specificity was lower (37%; 95% CI, 28–47). Against PRNT-50, results of cPass and anti-RBD IgG were nearly identical. Conclusions The added value of cPass compared with an IgG anti-RBD ELISA was modest.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it