Isolation of avian influenza virus from backyard poultry population of tehsil Abbottabad, Khyber Pakhtunkhwa, Pakistan
Bibliographic record
Abstract
The avian influenza virus is a highly contagious viral disease that predominantly impacts avian species, especially domestic birds like chickens, ducks, and turkeys. The study was conducted to isolate the avian influenza virus from domestic poultry breeds (Desi, Aseel, Fayoumi, and Golden) from backyard poultry population of the Tehsil Abbottabad from January to June 2023. A cross-sectional study was conducted in three rural and five urban areas of Tehsil Abbottabad Using sterile cotton swabs, 128 (tracheal and cloacal) swab samples were collected. The samples were labelled and stored in a brain-heart infusion medium, then transported to the National Reference Laboratory for Poultry Diseases in Islamabad using a thermostat shipment box. The samples were processed using a real-time reverse transcription polymerase chain reaction for avian influenza virus detection. This study concludes with a significant 9.38% prevalence percentage of avian influenza virus in Tehsil Abbottabad backyard poultry. The prevalence percentage of H9 was 83.33%, and that of H5 was 16.66%. The findings reveal the importance of implementing preventative measures to curb avian influenza outbreaks within the poultry population of the district. This study offers vital data for AIV research in 2023, guiding enhanced containment and prevention in backyard poultry to control avian influenza.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".