Neuromuscular and Lower Limb Biomechanical Differences Exist between Male and Female Elite Adolescent Soccer Players during an Unanticipated Side-cut Maneuver
Bibliographic record
Abstract
BACKGROUND: Female athletes are 2 to 8 times more likely than male athletes to injure the anterior cruciate ligament during a non-contact athletic maneuver. Identifying anterior cruciate ligament injury risk factors in female athletes may help with the development of preventive training programs aimed at reducing injury rates. HYPOTHESIS: Differences between genders in lower limb kinematics, kinetics, and neuromuscular patterns will be identified in an adolescent soccer population during an unanticipated side-cut maneuver. STUDY DESIGN: Controlled laboratory study. METHODS: Forty-two elite adolescent soccer players (21 male and 21 female) performed an unanticipated side-cut maneuver, with the 3-dimensional kinematic, kinetic, and electromyographic lower limb data being analyzed using principal component analysis. RESULTS: The female athletes had higher gastrocnemius activity, normalized to maximal voluntary isometric contractions, and a mediolateral gastrocnemius activation imbalance that was not present in the male athletes during early stance to midstance of the side-cut. Female athletes demonstrated greater rectus femoris muscle activity throughout stance, and the only hamstring difference identified was a mediolateral activation imbalance in male athletes only. Female athletes performed the side-cut with less hip flexion and more hip external rotation and also generated a smaller hip flexion moment compared with the male athletes. CONCLUSION: This is the first study to identify gender-related differences in gastrocnemius muscle activity during an unanticipated cutting maneuver. CLINICAL RELEVANCE: The increased and imbalanced gastrocnemius muscle activity, combined with increased rectus femoris muscle activity and reduced hip flexion angles and moments in female subjects, may all have important contributing roles in the higher noncontact ACL injury rates observed in female athletes.
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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) | 0.002 | 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".