CANINE BREEDS PREDISPOSED TO DEVELOP DISKOSPONDYLITIS: A RETROSPECTIVE STUDY OF 181 CASES (2009-2018)
Bibliographic record
Abstract
A study to determine the prevalence and predisposition of dog breeds to develop diskospondylitis (DS) was carried out on a population of 5,497 animals submitted to computed tomography or digital radiography of the spine between 2009 and 2018. Variables such as breed, gender, age, vertebral segment and total number of vertebrae affected were collected and submitted to the prevalence tests, chi-square and odds ratio. A total of 181 dogs presented DS, a prevalence of 3.4%. Of these, 65% were males with a probability 1.6x greater than females (CI 1.17-2.17). Dogs more than 10 years old have a 1.5x higher probability (CI 1.10-2.05), while those between 2-5 years the probability decreases 51% (CI 0.34-0.77). Large dogs (>30 kg; 45%) showed a 3.8x greater chance to develop DS (CI 2.56-5.33) than small dogs (<15 kg; 28%), although the small dogs showed a 34% lower probability (CI 0.24-0.47). The Labrador Retriever breed was 3.7x more likely to develop DS than all the other breeds studied (CI 2.56-5.33) and the French Bulldog, among the small breeds, was 2.8x more susceptible (CI 1.51-5.06). In conclusion older dogs, large dogs, especially Labrador Retrievers, are more likely to develop DS. The French bulldog should be studied further.
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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 | 0.001 |
| 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".