The association between the signalment, common causes of canine otitis externa and pathogens
Bibliographic record
Abstract
OBJECTIVE: To determine whether associations exist between pathogens, allergies, conformational abnormalities, endocrinopathies and signalment in canine otitis externa (OE). METHODS: Medical records of 149 dogs which met predetermined inclusion criteria were evaluated retrospectively. Correlations between pathogens and the presence of allergy, endocrinopathy, conformational abnormalities and signalment were evaluated statistically. RESULTS: The shar-pei, German shepherd and cocker spaniel breeds were over-represented compared with the hospital's breed distribution (P<0·001). German shepherd dogs and cocker spaniels were statistically more prone to infection with rod-shaped organisms and Labrador retrievers less than other breeds (P=0·034). Almost all dogs that were older than five years when diagnosed with OE had cocci (P=0·01) and also had higher levels of rods (P=0·028). The incidence of rods was higher in endocrinopathies (P=0·004), while that of Malassezia spp. tended to be higher in allergies (P=0·098). There were no statistically significant differences among the groups for all the other parameters examined. CLINICAL SIGNIFICANCE: OE infection is usually not influenced by primary causes or predisposing factors. Endocrinopathies may be followed by a more severe otitis, however. OE may be more severe when it affects older dogs.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".