Effects of 20‐day bed rest with and without strength training on postural sway during quiet standing
Bibliographic record
Abstract
AIM: To examine the effect of unweighting as a possible contributory factor to a reduced calf muscle volume on postural sway during quiet standing, changes in postural sway following bed rest with or without strength training were investigated. METHODS: Twelve young men participated in a 20-day bed-rest study. Subjects were divided into a non-training group (BR-Con) and a strength training group (BR-Tr). For the BR-Tr group, training was comprised of dynamic calf-raise and leg-press exercises to maintain the muscle volume of the plantar flexors. Before and after bed rest, subjects maintained quiet standing in a barefoot position on a force platform with their eyes open or closed. During the quiet stance, foot centre-of-pressure (CoP) and the mean velocity of CoP was calculated. Muscle volume of the plantar flexors was computed using axial magnetic resonance images of the leg. RESULTS: After the bed-rest period, the muscle volume decreased in the BR-Con group but not in the BR-Tr group. The mean velocity of CoP as an assessment of postural sway, however, increased in both groups. These results indicate that the strength training during bed rest cannot counteract the increase in postural sway. CONCLUSION: We concluded that postural sway increases following 20 days of bed rest despite maintenance of the muscle volume of plantar flexors as the main working muscles for the human postural standing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".