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Record W4407386896 · doi:10.9734/jabb/2025/v28i21979

Epidemiological Studies on Staphylococcal Otitis in Dogs at Jabalpur, India

2025· article· en· W4407386896 on OpenAlexaboutno aff
Chetanya Walia, Ranbir Singh Jatav, Shashi Pradhan, Apoorva Mishra, Aditya Pratap, Sanjay K. Shukla, Kshemankar Shrman, Diva Dhingra, Dushyant Kumar

Bibliographic record

VenueJournal of Advances in Biology & Biotechnology · 2025
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsnot available
Fundersnot available
KeywordsOtitisEpidemiologyMedicinePathologySurgery

Abstract

fetched live from OpenAlex

Ear affections are one of the most common conditions prevalent in canine practice and have a worldwide distribution. Inflammation of external, middle and inner ear are referred as otitis externa, otitis media and otitis interna, respectively and is reported to be the most frequent canine infectious disease over the past decades. The present study was undertaken to investigate the epidemiological study of Staphylococcal otitis in dogs. A total of 2420 dogs from May to October-2024 were screened for the study. Among them, 106 dogs suspected to have otitis were screened, out of which 89 dogs were confirmed for otitis and subjected to indirect smear examination and isolation of Staphylococcal species. Among which, 68 dogs were found to be suffering from Staphylococcal otitis resulting in overall occurrence of 2.8 per cent. Higher occurrence was observed in dogs of 3-5 years of age followed by dogs of age group more than 6 years. Amongst different breeds, notably higher occurrence was observed in Labrador Retrievers followed by German Shepherd. Sex wise occurrence was seen higher in males as compared to females. The percentage of dogs with bilateral ear infection was more pronounced as compared to unilateral ear infection. Mostly, dogs had a duration of illness for less than 1 week. Amongst different types of exudate, yellowish exudate was presented more. Cytological examination revealed that mixed infection (bacteria + Malassezia) was the commonest cause for otitis.

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)0.004
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 score0.152
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.372
Teacher spread0.353 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

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