APPLES TO APPLES? DISCORDANT DEFINITIONS STILL HINDER EVIDENCE-BASED TREATMENTS FOR SARCOPENIA
Bibliographic record
Abstract
Abstract The definition of sarcopenia continues to evolve, creating difficulty in determining the diagnosis and prognosis of the newly classified disease. The most common definitions include a combination of (a) muscle mass [measured using proxies of muscle mass—appendicular lean soft tissue via dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA)]; (b) muscle strength (often measured using hand grip strength); and (c) physical function (measured using gait speed). However, each consensus definition uses different combinations of muscle mass, strength and physical function to operationalize the definition of sarcopenia. Additionally, each group recommends various measures and cutoff points to capture these outcomes. For example, the European Working Group on Sarcopenia in Older People (EWGSOP) recommends appendicular lean mass for muscle mass, grip strength or chair stand for muscle strength, and gait speed, short performance physical battery, timed up and go, or 400-m walk test for physical function. The Asian Working Group for Sarcopenia (AWGS) uses DXA or BIA, grip strength and 6-m gait speed for muscle, strength and function, respectively. Using different consensus group definitions results in differences in the prevalence of sarcopenia, and there would be, at best, a modest agreement between the various definitions, which would be attributed to the lack of criterion standards.
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.
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 | 0.122 | 0.252 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".