Changes in kinematics and trunk electromyography during a 2000 m race simulation in elite female rowers
Bibliographic record
Abstract
Achieving excellence in rowing requires optimization of technique to maximize efficiency and force production. Investigation of the kinematics of the trunk, upper and lower extremity, together with muscle activity of the trunk, provides an insight into the motor control strategies utilized over a typical race. Nine elite female rowers performed a 2000 m race simulation. Kinematic data of the trunk and extremities, together with electromyography (EMG) activity of spinal and pelvic extensor and flexor muscles, were compared at 250 and 1500 m. At 1500 m, there was greater dissociation in the timing of leg extension and arm flexion and delayed trunk extension. Also at 1500 m, the spine demonstrated a delayed peak extension angular velocity of the T4-T7 and L3-S1 spinal segments in the early drive along with delayed and increased peak extension angular velocity of T10-L1 and L1-L3 spinal segments during the late drive. Trunk muscle fatigue was not evident; however, the abdominals demonstrated larger EMG burst areas at 1500 m. Alterations in trunk kinematics suggest that the trunk acts as a less stiff lever on which to transfer the forces of the legs to the arms and handle. Increased abdominal activity may reflect increased demand to control the trunk, given the altered coordination between the legs, trunk and arms.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.000 | 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".