Muscular Lower Leg Asymmetry in Middle-Aged People
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to determine whether muscular asymmetries were present in the lower legs of recreationally active middle-aged people grouped by leg dominance. METHODS: Twelve healthy middle-aged subjects were analyzed bilaterally. The clinical variables included leg dominance, sports level, range of motion, lower leg alignment, calf circumference, and AOFAS (American Orthopaedic Foot and Ankle Society) ankle score. The biomechanical variables included maximal voluntary isometric ankle joint torque and surface electromyography (EMG) with determination of mean EMG frequency and intensity of four lower leg muscles: anterior tibial (AT), medial gastrocnemius (MG), soleus (SO), and peroneus longus (PL). RESULTS: The mean EMG frequency was significantly lower in the dominant leg for the AT (dominant, 148.6 Hz; nondominant, 157.8 Hz) and MG muscles (dominant, 183.9 Hz; nondominant, 196.8 Hz). A significantly higher plantarflexion torque was found in the dominant leg (27.1 Nm) compared to the nondominant leg (22.9 Nm). Higher (not significant) dorsiflexion torque was found in the dominant leg (dominant, 27.3 Nm; nondominant, 24.8 Nm). The calf circumference was marginally significantly higher (p =0.039) in the dominant leg (34.2 cm; nondominant leg, 33.8 cm). The dominant leg had a higher but not significantly different mean EMG intensity for all four muscles. CONCLUSIONS AND CLINICAL RELEVANCE: Differences in muscle EMG and torque were found between the dominant and nondominant lower leg. These results might be applicable to treatment, rehabilitation, and future research of lower leg and foot and ankle disorders.
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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) | 0.003 | 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".