Prevalence of developmental skeletal abnormalities in the dog in Bulgaria: a 6-year survey.
Bibliographic record
Abstract
A 6-year survey (1 October 2006 – 1 October 2012) on the prevalence of developmental skeletal abnormalities in dogs was performed based on patients’ records of the Small Animal Clinic to the Faculty of Veterinary Medicine – Stara Zagora, Bulgaria. From the total number of 6,097 dogs with surgical disorders, developmental skeletal disorders were diagnosed in 230 dogs (3.78%). The incidence of diagnoses was as followed: hip dysplasia (64.35%), panosteitis (16.96%), elbow dysplasia (12.61%), hypertrophic osteodystrophy (3.48%), osteochondrosis (2.62%). The most commonly affected breeds were German shepherd (33.4%), Central Asian Shepherd (7.83%), Golden Retriever and Rottweiler (6.52%), Labrador Retriever (4.78%), and the least frequently – small canine breeds and hunting dogs. Male dogs were more frequently affected. Most of the patients were under 3-years old (91.30%) and all recorded panosteitis cases were in dogs younger than 3 years of age.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".