Streptococcus canis prevalence on the normal and abnormal ocular surface of dogs referred for ophthalmic disease in Canada
Bibliographic record
Abstract
Streptococcus canis is a beta-haemolytic, Gram-positive cocci commonly identified on the canine ocular surface under both healthy and diseased conditions. The objective of the study was to determine the prevalence of S. canis on the normal and abnormal ocular surface of a canine ophthalmology referral population in Canada, and to investigate potential clinical aspects that may be associated with its presence. Included were 59 dogs (118 eyes) with unilateral or bilateral ocular disease diagnosed at the time of conjunctival sampling. A real-time PCR specific for S. canis was standardized for use with conjunctival swabs. Total DNA was extracted from 118 samples and used as template for the diagnostic assay. Samples were considered positive if amplification was detected and dissociation temperature matched a positive control. Signalment and other clinical data were also collected at the time of sampling. Of the 118 eyes sampled, 8 tested positive for S. canis (6.8%). No association between the detection of S. canis and breed, cephalic conformation, sex, age, use of ophthalmic antibiotics or other topical medications, ophthalmic diagnosis, use of systemic antibiotics or other systemic medications, or systemic diagnosis was identified. In conclusion, S. canis may be present on the ocular surface of dogs at a higher rate than previously reported. It is suggested that this may be linked to the use of PCR for pathogen detection instead of culture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".