Immunity to equine influenza: relationship of vaccine‐induced antibody in young Thoroughbred racehorses to protection against field infection with influenza A/equine‐2 viruses (H3N8)
Bibliographic record
Abstract
Field outbreaks of influenza that occurred in vaccinated Thoroughbred racehorses in Newmarket in 1995 and 1996 were investigated by nucleoprotein ELISA and serology. Investigations showed that serum levels of vaccine-induced single radial haemolysis (SRH) antibody correlated closely with protective immunity against equine influenza and were consistent with observations made in previous experimental studies using nebulised aerosol challenge. In the second part of this study, antibody levels stimulated by vaccination were investigated to examine probable protection in high risk groups, such as yearlings and horses in training. Results for yearlings correlated closely with experimentally derived antibody profiles described for several equine influenza vaccines. The horses in training had levels of antibody immediately prior to revaccination, which were higher than those measured in the yearlings. In conclusion, SRH antibody, used in the investigation of outbreaks and surveillance of post vaccination responses, was shown to correlate with and validate experimental vaccination and challenge models currently used in ponies in the licensing of modern vaccines. There may be benefit from serological monitoring of horses following vaccination through identification of susceptible periods to infection and demonstration of poor vaccine responders. This would allow appropriate and timely amendment of vaccination strategies to maximise protective immunity against influenza.
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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 | 0.001 |
| 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) | 0.001 | 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".