Performance of assays for testing antibodies against porcine reproductive and respiratory syndrome virus in sera collected from swine farms in a region with an extreme virus heterogeneity
Bibliographic record
Abstract
Abstract Porcine reproductive and respiratory syndrome is the most economically important viral disease in the swine industry worldwide. Porcine reproductive and respiratory syndrome virus (PRRSV) strains are classified into two distinct genotypes, the European genotype and the North American genotype. The European PRRSV genotype has been divided into three subtypes: a pan-European subtype 1 and East European subtypes 2 and 3. The aim of this study was to evaluate the performance of commercial and homemade serological assays to test field sera from a geographical region with an extreme PRRSV heterogeneity. Belarus became the country of choice for sample collection because heterologous PRRSV strains of all known European subtypes circulate in this country. Sera from Belarusian swine farms were tested in immunoperoxidase monolayer assays based on pan-European subtype 1, East European subtype 3 and North American strains as antigens and commercial enzyme-linked immunosorbent assays (IDEXX and INGEZIM). The obtained results suggest that none of the serological tools for PRRSV diagnosis can guarantee a flawless detection of antibodies at the individual animal level. Considering heterogeneity of recently isolated European PRRSV strains the problem can be relevant in many countries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".