Goniometric Assessment in French Bulldogs
Bibliographic record
Abstract
Goniometry is a low-cost, user-friendly and widely available technique used by different veterinary medicine professionals to estimate joint range of motion (ROM). Studies providing breed-specific reference ranges for goniometric measurements are scarce and there is a lack of information regarding joint angles in French Bulldogs. This prospective study set out to determine normal ROM for the carpus, elbow, shoulder, tarsus, stifle and hip joints in healthy, adult French Bulldogs using goniometry. We hypothesized ROM would be similar in this and other dog breeds. Twenty dogs met the inclusion criteria. Sample size was calculated using power analysis based on previous studies. Goniometric measurements were made by a single examiner. Limbs were measured in random order and three measurements made per joint. Dogs were not sedated. Joint angles measured in French Bulldogs in this study were similar to those reported in Labrador Retrievers (shoulder, carpal, and tarsal flexion), Rottweilers (shoulder, carpus, and hip flexion), and Dachshunds (hip, stifle, and tarsal flexion). Similar flexion angles and ROM were detected in right and left limb joints. Findings of this study suggest similar ROM in French Bulldogs and other dog breeds. Lack of radiographic assessment and the fact that goniometric measurements were made by a single examiner were the major limitations of this study.
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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 | 0.001 | 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".