Development of Methods for Detection and Quantification of Avian Influenza and Newcastle Disease Viruses in Compost by Real-Time Reverse Transcription Polymerase Chain Reaction and Virus Isolation
Bibliographic record
Abstract
Composting has been used for disposal of poultry carcasses and manure following outbreaks caused by avian influenza virus (AIV) and Newcastle disease virus (NDV), but methods are needed to test for survival of the viruses in compost to ensure biosecurity. Methods developed in the present study include extracting viruses from compost and purifying viral RNA. The extracted viruses were detected by virus isolation using embryonated chicken eggs, and the purified RNA was detected by real-time reverse transcription PCR (RRT-PCR). The virus isolation and the RRT-PCR methods were evaluated with 3 compost preparations that were produced from chicken manure mixed with corn silage, wood shavings, or wheat straw. The detection limits of both methods were 1,700 and 1,000 embryo lethal doses of AIV and NDV per gram of compost, respectively. The copy number of viral RNA quantified by RRT-PCR was highly correlated with the amount of virus in compost. The results suggested that the RRT-PCR method may be used as an alternative to the virus isolation method for rapid detection and accurate quantification of AIV and NDV in compost.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".