Effect of hoof orientation and ballast on acceleration and vibration in the hoof and distal forelimb following simulated impacts <i>ex vivo</i>
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: We wished to add to the existing baseline data on impact loading of the distal limb as a precursor to assessing the potential role of impact in injury and joint disease. OBJECTIVES: To examine the effect of 3 hoof-strike conditions (toe first, flat and heel first) and 2 specimen masses (with and without a ballast of ∼2% body mass) on impact deceleration and vibration frequencies and energies at the hoof, first phalanx and third metacarpal. STUDY DESIGN: Biomechanical experiments in cadaver material. METHODS: Eight cadaver limbs were subjected to randomised, repeated controlled trials, in which the hoof was struck by a pendulum impact-testing machine (impact velocity, 3.55 m/s) in the 3 strike and 2 mass conditions. Data from triaxial accelerometers on the hoof, first phalanx and third metacarpal quantified, for all trials, the peak impact acceleration, frequencies in the first 6.4 ms following impact, the frequency with the most energy, 95% of the total energy and the frequency at 95% cumulative energy. The effects of the strike and mass conditions on each variable were statistically tested using repeated-measures ANOVA (α = 0.05). RESULTS: Signal energy reaching the third metacarpal was 6-31% of that at the hoof. A heel-first strike produced the largest peak accelerations and highest frequencies among all strike conditions, and changing the mass had no effect regardless of strike condition. CONCLUSIONS: Large accelerations that occur upon impact of the hoof with the ground are attenuated by the distal structures of the equine limb, but still carry considerable energy within the signal that could be damaging to tissue and are dependent on hoof-strike condition but not ballast. Our results suggest that impact loading on the hoof could be a factor in contributing to bone injury and joint disease in the distal limb.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".