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Prevalence of hemorrhagic gastroenteritis in canine population of Garividi region of Andhra Pradesh

2024· article· en· W4405257491 on OpenAlexaboutno aff
G.S. Haritha, N. Praharshini, Pooja Reddi, P Ramesh

Bibliographic record

VenueJournal of Krishi Vigyan · 2024
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsVeterinary medicineMedicinePopulationGeographyTraditional medicineSocioeconomicsEnvironmental healthSociology

Abstract

fetched live from OpenAlex

The present study was taken from March 2023 to February 2024 to determine the prevalence of hemorrhagic gastroenteritis (HGE) in dogs that were presented to Veterinary Clinical Complex, College of Veterinary Science, Garividi with the purpose to determine the prevalence and associated etiologies causing hemorrhagic gastroenteritis in the area. A total of 1292 dogs were presented to the VCC with the history of anorexia, dullness, vomiting, hematemesis, blood tinged/ brownish colored diarrhea and putrid odour feces. The overall prevalence of HGE was 19.2 per cent among the presented cases. The prevalence in young ones (< 6 months) was higher than the adult dogs (above 3 years) with prevalence ranging from 62.1 to 2.4 per cent, respectively. The prevalence was higher in male (75.8%) than female (24.2%) dogs. Mongrel breed of dogs showed high prevalence of 40.72 per cent followed by Spitz, Labrador, German shepherd and lowest in Pug, Husky and Terrier breeds of dogs with 1.21 per cent. HGE due to Canine Parvovirus infection (45.2%) followed by intestinal parasitic infestation (27.8%), combined infection of parvovirus and intestinal parasites (12.5%), other conditions (9.7%) and Isosporiosis (4.8%) were the etiologies that resulted in HGE in dogs.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.025
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.325
Teacher spread0.301 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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