Studies on <i>Malassezia</i> Infection in Otitis External of Dogs
Bibliographic record
Abstract
The present study was aimed to investigate the prevalence of Malassezia in common ear affections of dogs. A total of 115 dogs with ear affections were evaluated between March 2014 and May 2015. Otoscopic examination and microbiological isolation was done for diagnosis. Case prevalence of Malassezia infection in otitis externa was 19.1%. Relatively higher proportion of Malassezia was found in males 68.2% (n=15) as compared to females 31.8% (n =7). The yeast was more prevalent in adult dogs (1–3 years old). Labrador, Beagle and Cocker Spanial were breeds more commonly predisposed to otitis externa. The prevalence was relatively higher in rainy season (July-August) 63.6% (n=14) followed by summer (April-June) 18.2% (n=4), winter (December-March) 13.6% (n=3) and autumn (September-November) 4.6% (n=1). Head shaking, frequent itching and malodour were the common presenting signs. It can be concluded that Malassezia infection is quite common in otitis externa, and can be diagnosed using otoscopy and microbiological isolation.
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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 | 0.001 | 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 | 0.001 |
| 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".