Advances in Vaccine Development of the Emerging Novel Genotype Fowl Adenovirus 4
Bibliographic record
Abstract
Fowl adenovirus (FAdV) was first reported in Angara Goth, Pakistan, in 1987. For this reason, it is also known as "Angara disease." It was later reported in China, Japan, South Korea, India, the United States, Canada, and other countries and regions, causing huge economic losses in the poultry industry worldwide. Notably, since June 2015, a natural outbreak of severe hydropericardium hepatitis syndrome (HHS), associated with a hypervirulent novel genotype FAdV-4 infection, has emerged in most provinces of China. The novel virus FAdV-4 spread rapidly and induced a 30-100% mortality rate, causing huge economic losses and threatening the green and healthy poultry breeding industry. Vaccines against FAdV-4, especially the emerging novel genotype, play a critical role and will be the most efficient tool for preventing and controlling HHS. Various types of FAdV-4 vaccines have been developed and evaluated, such as inactivated, live-attenuated, subunit, and combined vaccines. They have made great contributions to the control of HHS, but the details of cross-protection within FAdVs and the immunogenicity of different vaccines require further investigation. This review highlights the recent advances in developing the FAdV-4 vaccine and promising new vaccines for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".