On senecavirus transmission pathways and mechanism
Bibliographic record
Abstract
Senecavirus infection is manifested by vesicular lesions of the skin of the distal parts of the limbs, patch and mammary gland in adult pigs and epizootic transient neonatal disease of newborn piglets. According to clinical signs and pathological changes, vesicular senecavirus infection in fattening pigs and adult pigs is indistinguishable from foot and mouth disease, porcine vesicular disease, porcine vesicular exanthema and vesicular stomatitis. The causative agent of senecavirus infection is a small, non-enveloped virus containing RNA coated with a protein capsid. Возбудитель относится к семейству Picornaviridae, роду Senecavirus. According to the data of 2019 senecavirus infection has been reported in the United States, Canada, Brazil, Colombia, China, Thailand, and Vietnam. There is a tendency to widespread senecavirus. A number of researchers believe that in the US, senecavirus infection has become endemic. Outbreaks of senecavirus infection in the Heilujiang province of China represent the greatest threat to pig breeding in the Russian Federation, since this province borders with Primorsky, Khabarovsk, the Jewish Autonomous and Amur regions. Experimentally proved the possibility of infection of pigs with senecavirus by alimentary route. It has been established that certain food ingredients are risk factors for the movement of viruses, including senecavirus, across the country and around the world. These results indicate a great risk of introducing senecavirus into Russia with feed ingredients. Isolation of senecavirus from samples of the lungs of sick pigs indicates a possible infection of animals by an aerogenous route. Senecavirus is excreted from the mouth out of the body of pigs, as well as with feces within 28 days.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".