STUDY ON THE INCIDENCE OF CANINE PYODERMA IN NAGPUR
Bibliographic record
Abstract
Canine pyoderma significantly impacts affected animals, causing discomfort and a notable decline in their overall quality of life.The study was carried out in the Department of Veterinary Clinical Medicine, Ethics & Jurisprudence, Nagpur Veterinary College, Nagpur from June 2023 to December 2023.The comparative therapeutic efficacy of systemic, topical and mixed therapy was evaluated.The primary diagnosis of canine pyoderma was done using skin cytology and further confirmed by bacterial culture.Out of total 11657 dogs examined,1287 (11.04%) dogs that were found positive for skin diseases.Out of these, 223 (17.32%) dogs were found affected with pyoderma.The highest incidence of canine pyoderma was observed in dogs aged between 1 to 2 years.Males were found most susceptible.Labrador Retriever was found predominantly affected..The common clinical signs recorded were erythema, alopecia, pruritus, papules, and pustules.spp.was found to be the most common bacteria (96.77%), followed by E.coli (3.22%).Clindamycin and doxycycline demonstrated the highest level of antibiotic sensitivity when tested on Staphylococciisolates (n=30), while enrofloxacin demonstrated the highest level when tested on E.Coli isolates (n=1).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".