Detection of antibodies to structural proteins of foot-and-mouth disease virus in swine meat juice.
Bibliographic record
Abstract
Established test methods for detecting foot-and-mouth disease virus (FMDV) rely on sample collection from live animals. However, circumstances exist in which it is not possible to collect the desired samples. Meat juice has been explored as an alternative for the detection of FMDV and has previously proven successful by real-time reverse transcription polymerase chain reaction and lateral flow strip test. Meat juice has not yet been assessed for the detection of antibodies to FMDV. This study, therefore, evaluated meat juice for the detection of antibodies to structural proteins by existing serotype-specific solid phase competitive enzyme-linked immunosorbent assays. Antibodies to FMDV structural proteins were detected in meat juice from experimentally infected pigs beginning 6- or 7-days post-infection (DPI) and continued until 21 to 28 DPI. Sera were tested in tandem and followed similar antibody detection patterns. The results show that meat juice can be used for detection of anti- FMDV structural protein antibodies.
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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 | 0.000 | 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 | 0.001 | 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".