Porcine epidemic diarrhea virus: An emerging and re-emerging epizootic swine virus
Bibliographic record
Abstract
The enteric disease of swine recognized in the early 1970s in Europe was initially described as "epidemic viral diarrhea" and is now termed "porcine epidemic diarrhea (PED)". The coronavirus referred to as PED virus (PEDV) was determined to be the etiologic agent of this disease in the late 1970s. Since then the disease has been reported in Europe and Asia, but the most severe outbreaks have occurred predominantly in Asian swine-producing countries. Most recently, PED first emerged in early 2013 in the United States that caused high morbidity and mortality associated with PED, remarkably affecting US pig production, and spread further to Canada and Mexico. Soon thereafter, large-scale PED epidemics recurred through the pork industry in South Korea, Japan, and Taiwan. These recent outbreaks and global re-emergence of PED require urgent attention and deeper understanding of PEDV biology and pathogenic mechanisms. This paper highlights the current knowledge of molecular epidemiology, diagnosis, and pathogenesis of PEDV, as well as prevention and control measures against PEDV infection. More information about the virus and the disease is still necessary for the development of effective vaccines and control strategies. It is hoped that this review will stimulate further basic and applied studies and encourage collaboration among producers, researchers, and swine veterinarians to provide answers that improve our understanding of PEDV and PED in an effort to eliminate this economically significant viral disease, which emerged or re-emerged worldwide.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".