Evaluation of Diagnostic Accuracy of Eight Commercial Assays for the Detection of Measles Virus-Specific IgM Antibodies
Bibliographic record
Abstract
= 187) were collected from individuals presenting with other fever and rash illnesses. A total of 7 ELISA kits (Euroimmun native antigens and recombinant nucleoprotein, IBL, Clin-Tech Microimmune, NovaTec NovaLisa, Serion, and Siemens Enzygnost) and one CLIA method (DiaSorin LIAISON XL) were evaluated. The ELISA kits included two IgM capture methods and five indirect methods. Calculated sensitivities and specificities ranged from 75.0% to 98.1% and 86.6% to 99.5%, respectively. The parvovirus B19 IgM positive sera were noted to cause false-positive results, particularly for the ELISA kits from Serion and NovaLisa; specificities for this subset of samples ranged from 51.4% to 100.0%. The capture IgM ELISA methods provided the best combination of sensitivity and specificity.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".