Occurrence of Malassezia dermatitis in Dogs in and around Navsari (Gujarat)
Bibliographic record
Abstract
Malassezia dermatitis is a common clinical disorder in dogs caused by the yeast, Malassezia pachydermatis, clinically characterized by intense pruritus, alopecia, hyperpigmentation, lichenification, and visibly increased skin thickness. As Malassezia dermatitis mimics many other pruritic dermatoses, its diagnosis particularly the differential diagnosis of the disease is quite challenging. A total of 895 dogs presented to the Veterinary Clinical Complex and in and around Navsari during the period of six months, from February 2024 to July 2024 were screened for Malassezia dermatitis. Of these, 140 dogs (15.64%) demonstrated clinical signs indicative of dermatological disorders and were subjected to cytological examination for confirmation. Therefore, 40 dogs (28.57%) were found afflicted with Malassezia dermatitis. The overall occurrence of dermatological disorders in dogs in and around Navsari was 15.64 percent while, the overall occurrence of Malassezia dermatitis was 4.47 percent and among the suspected dogs, the occurrence was 28.57 percent. No significant variation between age, sex, breed, and month was observed for the occurrence of Malassezia dermatitis. However, dogs aged between 1-4 years, Labrador Retrievers and male dogs had higher occurrence of disease.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".