Normal intraocular echo-biometric indices of adult dogs
Bibliographic record
Abstract
The purpose of this study was to describe the ultrasonographic appearance and to measure different intraocular echo-biometric indices in normal adult dogs. B-mode transcorneal ultrasonographic scanning of left and right eyes of six healthy adult dogs each from three different breeds viz. German shepherd, Labrador retriever and Indian mongrels were performed. Qualitative echo-biometric findings of the eyes were described and measurements of the intraocular structures were obtained. In the present transcorneal intraocular echobiometric study six parameter were measured, i.e., aqueous chamber depth (ACD), lens depth (LDe), lens diameter (LDi), vitreous depth (VD), sclero-retinal rim thickness (SRT), and globe axial length (GAL) by using high end ultrasound machine (Mylab30vet), with 2.5–7.5 MHz microconvex transducer and the depth of scanning was set at 5–9 cm with suitable gain without administration of any general/local anaesthetic. Nonsignificant difference (P>0.05) was observed in all parameters when compared between left and right eye of different breeds of animals. The average values of LDi and GAL of both eyes of German shepherd dog were significantly different from Labrador retriever and Indian mongrel dogs. The average value of SRT of both eyes of German shepherd and Labrador were significantly higher (P 0.05) among three breeds of dog.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".