Evaluation of Spleen Swabs for Sensitive and High-Throughput Detection of Classical Swine Fever Virus
Bibliographic record
Abstract
Despite intensive eradication efforts, classical swine fever (CSF) remains endemic across South America, Europe, Asia, and the Caribbean, highlighting the need for more effective surveillance and detection methods. Reverse-transcription real-time polymerase chain reaction (RRT-PCR) is the fastest, and most sensitive assay for detecting CSF virus (CSFV) genomic material. Previously, we demonstrated that spleen swabs outperformed spleen homogenates for the detection of ASFV genomic material by RRT-PCR. In this study, we compared CSFV genome detection in paired spleen homogenates and spleen swabs generated using 49 frozen and 33 fresh spleen samples collected from experimentally inoculated pigs with acute infection. The results show that the CSFV genome detection in spleen swabs is comparable to that in spleen homogenates. The study also demonstrated that the CSFV genomic material can be detected in spleen swabs during early CSFV infections, and the viruses can be successfully isolated from the swabs. The use of spleen swabs instead of spleen tissue homogenates for CSF detection will reduce labor, decrease costs associated with reporting, and increase the diagnostic throughput.
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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 | 0.000 |
| 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".