Distribution of multifragmental diaphyseal fractures of femur and tibia in dogs
Bibliographic record
Abstract
The study included in 21 dogs suffering from multifragmental long bone fractures involving femur and tibia. Multifragmental diaphyseal fractures were more in male animals (76.19%) than in females (23.80%). Highest number of fractures was recorded in dogs aged up to 12 months (52.38%). Medium weight dogs of 20–30 kg were most commonly affected (71.42%) followed by light (10–12 kg) and heavy dogs (>30 kg). Among the different breeds, German shepherds were the most commonly involved (28.57%), followed by Rottweiler and Labrador Retriever (19.05% each). Automobile accident was the major etiology of fractures (76.19%). Among the long bones, femur was most commonly involved (80.95%), followed by tibia (19.05%). In femur, the left side and in tibia right side was more commonly involved. Wedge fractures were more common (76.19%) than complex fractures (23.81%); and femur showed highest number of 32B3 type fractures and tibia showed highest number of 42C3 type fractures.
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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 | 0.001 |
| 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".