Epidemiological Studies on Staphylococcal Otitis in Dogs at Jabalpur, India
Bibliographic record
Abstract
Ear affections are one of the most common conditions prevalent in canine practice and have a worldwide distribution. Inflammation of external, middle and inner ear are referred as otitis externa, otitis media and otitis interna, respectively and is reported to be the most frequent canine infectious disease over the past decades. The present study was undertaken to investigate the epidemiological study of Staphylococcal otitis in dogs. A total of 2420 dogs from May to October-2024 were screened for the study. Among them, 106 dogs suspected to have otitis were screened, out of which 89 dogs were confirmed for otitis and subjected to indirect smear examination and isolation of Staphylococcal species. Among which, 68 dogs were found to be suffering from Staphylococcal otitis resulting in overall occurrence of 2.8 per cent. Higher occurrence was observed in dogs of 3-5 years of age followed by dogs of age group more than 6 years. Amongst different breeds, notably higher occurrence was observed in Labrador Retrievers followed by German Shepherd. Sex wise occurrence was seen higher in males as compared to females. The percentage of dogs with bilateral ear infection was more pronounced as compared to unilateral ear infection. Mostly, dogs had a duration of illness for less than 1 week. Amongst different types of exudate, yellowish exudate was presented more. Cytological examination revealed that mixed infection (bacteria + Malassezia) was the commonest cause for otitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".