Contribution of segmental kinetic energy to forward propulsion of the centre of mass: Analysis of sprint acceleration
Bibliographic record
Abstract
This study aimed to measure the contribution of each body segment to the production of total body kinetic energy (KE) during a 40-m sprint. Nine recreational sprinters performed two 40-m sprints wearing a MVN Biomech suit (Xsens). Data recorded were used to calculate total body KE, and the KE of each segment. The KE of each segment was then expressed as a percentage of the total body KE. We divided the sprint into three phases: 1 – start to maximal power (Pmax), 2 – Pmax to maximal velocity (Vmax), and 3 – Vmax to the end of the 40 m. Total body KE increased from the start to the end of the 40-m sprint (from 331.3 ± 68.4 J in phase 1 to 2378.8 ± 233.0 J in phase 3; p ≤ 0.001). The contribution of the head–trunk increased (from 39.5 ± 2.4% to 46.3 ± 1.1%; p ≤ 0.05). Contribution of the upper and lower limbs decreased over the three phases (respectively from 15.7 ± 2.5% to 10.6 ± 0.6% and from 44.8 ± 2.1% to 43.1 ± 1.5%; p ≤ 0.05). This study revealed the important contribution of the trunk to forward propulsion throughout the entire acceleration phase.
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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 | 0.001 | 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".