Bibliographic record
Abstract
Inflammation of the external ear in dogs is a widespread pathology in 20 % of sick animals that come to veterinary medicine clinics. The purpose of the work was to monitor the spread of otitis in dogs for 2021 in Odesa. To solve this goal, several tasks were set: to study the spread of otitis among dogs by breed, age, and sex; to study the spread of Malassezia otitis among dogs; to determine the seasonality of otitis in dogs. The data from the journal of registration of sick animals of the veterinary clinic of Odessa (VetKOiN) served as the material. Data concerning sick animals from the logbook were entered into tables, and statistical analysis was carried out. Dogs of Pugs and Mestizo made up the most significant number of sick animals with otitis (10.4 % each); the French Bulldog breed accounts for 9.1 %, the Pekinese and Labrador breeds – 6.5 % each, the Clamber Spaniel breed – 5.2 %. Such dog breeds as Jack Russell Terrier, Chihuahua, Spitz, German Shepherd, and Cane Corso account for 3.9 %; Bull Terrier, East European Shepherd, and Retriever – 2.6 % each; Grünendal, Husky, Samoyed, Kangal, Dachshund, Scottish Shepherd, Shar-Pei, Bolonka, Beagle, American Cocker Spaniel, Shih-Tzu, Laika, Fox Terrier, Staffordshire Terrier, Pit Bull Terrier, American Bully, Breton, Bernese Mountain Dog, English Bulldog breeds – 1.3 % each. Animals between the ages of 1 and 5 years suffer mostly from canine otitis (64 %) and animals under the age of 1 year suffer less(10 %). Animals older than five years make up 26 %. The gender of dogs is not important in otitis spreading: females account for 49 % of sick animals, and males – 51 %. Malassezia otitis in dogs occurred in 38 % of cases. Dogs of Pug breeds comprised the largest percentage of sick animals (13.8 %), French bulldog and Pekingese breeds – (10.3 % each). The Bull Terrier, Jack Russell Terrier, and Chihuahua breed each account for 6.9 %. Otitis was registered every month during the year. An increase in the incidence was observed in April (9.1 %), May (13.0 %), June (7.8 %), July (15.6 %), August (13.0 %), September (10.4 % ) and November (10.4 %). So otitis was more often registered in dogs in the warm season. In the future, the spread, etiology, and most effective treatment regimens of various forms of otitis in dogs will be studied.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".