Influence of individual competition level on back kinematics of horses jumping a vertical fence
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: The costs and investments required for the purchase and training of showjumpers justify the need to find selection means for jumping horses. Use of objective kinematic criteria correlated to jumping ability could be helpful for this assessment. OBJECTIVES: To compare back kinematics between 2 groups of horses of different competition levels (Group 1, competing at high level; Group 2 competing at low level) while free jumping over a 1 m vertical fence. METHODS: Three-dimensional recordings were performed using 2 panning cameras. Kinematic parameters of the withers and tuber sacrale (vertical displacement, vertical and horizontal velocities), backline inclination and flexion-extension motion of the 3 main dorsal segments (thoracic, thoracolumbar and lumbosacral) were analysed. RESULTS: Group 2 horses had a lower displacement of their withers and tuber sacrale from the end of the last approach stride until the first departure stride (P<0.05). As a result, they increased the flexion of their thoracolumbar and lumbosacral junctions during the hindlimb swing phase before take-off (P<0.05). However, withers and tuber sacrale velocities were slightly modified. Group 1 horses pitched their backline less forward during the forelimb stance phase before take-off and straightened it more after landing (P<0.05), probably indicating a more efficient strutting action of their forelimbs. CONCLUSIONS AND POTENTIAL RELEVANCE: Because significant differences in back motion were found between good and poor jumpers when jumping a 1 m high fence, criteria based on certain back kinematics can be developed that may help in the selection of talented showjumpers.
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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 | 0.000 | 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) | 0.003 | 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".