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Demographic study of staphylococcal pododermatitis in Jabalpur

2025· article· en· W4408566353 on OpenAlexaboutno aff
Patil Ankita Vijay, Ranbir Singh Jatav, Brejesh Singh, Vidhi Gautam, Sanjay K. Shukla, Chetanya Walia

Bibliographic record

VenueInternational Journal of Advanced Biochemistry Research · 2025
Typearticle
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiology

Abstract

fetched live from OpenAlex

A study was undertaken to determine the prevalence of Staphylococcal pododermatitis amongst different dermatological conditions. During the study period, a total of 2475 dogs presented to VCC, College of Veterinary Science and Animal Husbandry, Jabalpur (M.P.) were screened over six months period from May to October 2024. Out of which, 248 dogs showed clinical signs pertaining to pododermatitis, the overall occurrence of pododermatitis was 3.27% although the occurrence of Staphylococcal pododermatitis was 1.29%. Higher occurrence was observed in male dogs (43.18%) in comparison to females. Dogs in the age group of 1-3 years were mostly susceptible (50%) to Staphylococcal pododermatitis and the least susceptible were below 1 year of age. Results revealed that Labrador (44.44%) were more predisposed followed by non-descript (41.67%) and the least predisposed breed was found to be Pug (30.77%). The most common clinical signs of pododermatitis observed were licking (53.13%), erythema (43.75%) with limping and bleeding the least presented clinic signs (6.25% each). The clinical signs were more prominent in all four paws.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.430
Teacher spread0.399 · 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 source (direct Gemma or distilled Codex), 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

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