Effects of hoof shape, body mass and velocity on surface strain in the wall of the unshod forehoof of Standardbreds trotting on a treadmill
Bibliographic record
Abstract
Abstract The purpose of this work is to investigate the effects of body mass (BM), velocity ( V ), and hoof shape on compressive surface strains in the wall of the front hoof at the trot. Toe angle (TA), heel angle (HA), toe length (TL), medial and lateral wall length (MWL, LWL) and BM were measured for nine adult, unshod Standardbreds. Five rosette gauges were glued around the circumference of the left forehoof of each animal which was then trotted on a treadmill at a set range of velocities from 3.5 to 7.5 m s −1 . Analysis of variance (ANOVA) of principal compressive strains ɛ 2 at midstance identified that all primary variables (BM, V , TA, HA, etc.) had a significant effect as did the interactions of TA×HA and BM×TA. These significant variables explained over 96% of the variation in ɛ 2 . Multiple regression of ɛ 2 on these variables gave equations which accurately predicted ɛ 2 within 3%, but the individual coefficients did not accurately describe how each variable affected ɛ 2 . Further tests using bivariate regression gave equations that enabled ɛ 2 data to be standardized for BM and V at the gauge locations used here. Strain ɛ 2 increased linearly with mass and curvilinearly with velocity ( ɛ 2 ∝ V + V 2 ), and both caused redistribution of strain to the dorsum and lateral quarter. Variation in each shape variable caused redistribution rather than simple increase or decrease in strains. The primary conclusion with regard to hoof shape is that the effects of change in any one measurement on strain magnitudes are affected by the values of all other measurements. Resolving the interplay among measurements in their effects on ɛ 2 will need a considerably larger sample size than that used here.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".