Toward a sex‐specific relationship between muscle strength and appendicular lean body mass index?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In spite of some dissociation between muscle mass and strength, muscle strength is often used as a proxy to identify individuals with low muscle mass (sarcopenia). Thus, the aim of the present study was to investigate the relationship between muscle strength and the appendicular lean body mass index (app LBMI). METHODS: One hundred and five individuals were recruited. Knee extension and handgrip strength were measured. Body composition was assessed by DXA. App LBMI was calculated as appendicular lean body mass divided by height squared. RESULTS: At le level of the entire cohort, both handgrip (r = 0.73; p < 0.001) and knee extension strength (r = 0.57; p < 0.001) were associated with app LBMI. However, in women, knee extension strength (r = 0.32; p < 0.05) but not handgrip strength (r = 0.14; p = 0.35) was associated with app LBMI; while in men, handgrip strength (r = 0.43; p < 0.01) but not knee extension strength (r = 0.27; p = 0.09) was associated with app LBMI. CONCLUSIONS: Muscle strength appears to be associated with lean body mass; however, handgrip strength may be preferentially used in men and knee extension strength in women to detect sarcopenic individuals. Future larger studies are now needed to confirm our findings and their clinical relevance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 it