Characterization and Prevalence of a New Porcine Calicivirus in Swine, United States
Bibliographic record
Abstract
Real-time reverse transcription PCR revealed that new St-Valerien-like porcine caliciviruses are prevalent (2.6%-80%; 23.8% overall) in fi nisher pigs in North Carolina.One strain, NC-WGP93C, shares 89.3%-89.7%genomic nucleotide identity with Canadian strains.Whether these viruses cause disease in pigs or humans or are of food safety concern requires further investigation.V iruses in the family Caliciviridae are nonenveloped, polyadenylated, single-stranded, positive-sense RNA viruses (1).They have been classifi ed into 5 genera (Norovirus, Sapovirus, Vesivirus, Lagovirus, and Nebovirus) since 2009 (www.ictvonline.org).Later, the nonhuman primate Tulane virus (2) and the porcine St-Valerien-like viruses (3) were characterized as potential new genera in the Caliciviridae family. The StudyRecently, we identifi ed a St-Valerien-like virus, NC-WGP93C strain, from a healthy fi nisher pig in the United States by reverse transcription PCR (RT-PCR) with calicivirus universal primers p290/110 (4,5), followed by direct sequencing and nucleotide BLAST search (www. ncbi.nlm.nih.gov).We further sequenced the genome of NC-WGP93C strain by using primer walking, 3′ and 5′ rapid amplifi cation of cDNA ends (RACE) methods (3,6,7).The NC-WGP93C strain was closely related genetically to the Canadian St-Valerien-like viruses, AB90, AB104, and F15-10 strains (3), sharing 89.3%-89.7%nt identity, without insertions or deletions, and similar genomic organization.Complete genomes of strains representing different Caliciviridae genera were selected for a phylogenetic tree (Figure 1).The NC-WGP93C strain
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".