Use of a Standardized Bovine Serum Panel To Evaluate a Multiplexed Nonstructural Protein Antibody Assay for Serological Surveillance of Foot-and-Mouth Disease
Bibliographic record
Abstract
Liquid array technology has previously been used to show proof of principle of a multiplexed nonstructural protein serological assay to differentiate foot-and-mouth disease virus-infected and vaccinated animals. The current multiplexed assay consists of synthetically produced peptide signatures 3A, 3B, and 3D and the recombinant protein signature 3ABC in combination with four controls. To determine the diagnostic specificity of each signature in the multiplex, the assay was evaluated against a naive population (n = 104) and a vaccinated population (n = 94). Subsequently, the multiplexed assay was assessed by using a panel of bovine sera generated by the World Reference Laboratory for foot-and-mouth disease in Pirbright, United Kingdom. This serum panel has been used to assess the performance of other singleplex enzyme-linked immunosorbent assay (ELISA)-based nonstructural protein antibody assays. The 3ABC signature in the multiplexed assay showed performance comparable to that of a commercially available nonstructural protein 3ABC ELISA (Cedi test), and additional information pertaining to the relative diagnostic sensitivity of each signature in the multiplex was acquired in one experiment. The encouraging results of the evaluation of the multiplexed assay against a panel of diagnostically relevant samples promote further assay development and optimization to generate an assay for routine use in foot-and-mouth disease serological surveillance.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".