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Isolation of avian influenza virus from backyard poultry population of tehsil Abbottabad, Khyber Pakhtunkhwa, Pakistan

2024· article· en· W4398245442 on OpenAlexaff
Muqaddas Rasheed, Nayyer Yousaf, Naqash Khalid, Omer Dad

Bibliographic record

VenueZoo botanica. · 2024
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsKhyber pakhtunkhwaIsolation (microbiology)Virus isolationInfluenza A virus subtype H5N1Veterinary medicinePopulationNewcastle diseaseVirologyVirusGeographyBiologySocioeconomicsMedicineEnvironmental healthMicrobiologySociology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.051
GPT teacher head0.387
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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