A Comprehensive Epidemiological Study on Dermatophytosis in Dogs in Jabalpur, India
Bibliographic record
Abstract
Dermatophytosis is a contagious fungal infection of keratinized tissue. The disease is of significant veterinary and public health importance due to its zoonotic potential, posing risks to both animals and humans. The present study was undertaken to investigate occurrence of dermatophytosis in dogs. During the study period, from May to October 2024, a total of 2468 dogs were screened which were presented at Veterinary Clinical Complex, College of Veterinary Science and Animal Husbandry, Jabalpur (M.P.). Among them, 225 dogs were suspected for dermatological disorders and 43 dogs were found to be positive for dermatophytosis. The occurrence of different dermatological disorders was recorded highest in Pyoderma (20.89%), followed by dermatophytosis (19.11%), others (18.67%), Malassezia dermatitis (15.11%), mange in (13.78%) and tick and flea infestation (12.44%). The overall occurrence of dermatophytosis in dogs was recorded as 1.74% and among the suspected dogs, the occurrence was 19.11%. Age wise occurrence was significantly higher in 0-1 years of age (38.10%). Gender wise occurrence was observed significantly higher in males (25.93%). The breed wise highest occurrence of dermatophytosis was recorded in the Labrador breed of dogs (24.39%). The most prevalent clinical signs observed in canine dermatophytosis were alopecia (86.00%), scales (74.40%), crusts (74.40%), circular lesions (72.10%), pruritis (58.10%), erythema (51.20%), hyperpigmentation (46.50) and pustules and papules (34.90%). The lesions were predominantly seen on hind limbs (69.77%) followed by forelimbs (67.44%), dorsum (65.12%), face, head and neck (62.79%), paws (55.81%), interdigital space (48.84%), tail (41.86%) and abdomen (13.95%).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".