Associations between trunk muscle morphology, strength and function in older adults
Bibliographic record
Abstract
Skeletal muscle plays an important role in performing activities of daily living. While the importance of limb musculature in performing these tasks is well established, less research has focused on the muscles of the trunk. The purpose of the current study therefore, was to examine the associations between functional ability and trunk musculature in sixty-four community living males and females aged 60 years and older. Univariate and multivariate analyses of the a priori hypotheses were performed and reported with correlation coefficients and unstandardized beta coefficients (β) respectively. The univariate analysis revealed significant correlations between trunk muscle size and functional ability (rectus abdominis: six-minute walk performance, chair stand test, sitting and rising test; lumbar multifidus: timed up and go) as well as trunk muscle strength and functional ability (trunk composite strength: six-minute walk performance, chair stand test, Berg balance performance, sitting and rising test). After controlling for covariates (age and BMI) in the multivariate analysis, higher composite trunk strength (β = 0.34) and rectus abdominis size (β = 0.33) were associated with better performance in the sitting and rising test. The importance of incorporating trunk muscle training into programs aimed at improving balance and mobility in older adults merits further exploration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".