Use of dual X-ray absorptiometry to measure body mass during short- to medium-term trials of nutrition and exercise interventions
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
Dual X-ray absorptiometry (DXA) has a range of clinical applications, from assessing associations between adipose or lean body mass and the risk of disease to measuring the effects of dietary interventions on adipose deposition and oxidation and/or muscle accumulation. Many lifestyle-related studies, however, are short- to medium-term interventions, and inter- or intradevice variation between DXA scanners can facilitate type I and type II errors during data analysis. Studies demonstrate that variation in body composition measurements exist not only between DXA instruments using fan-beam and pencil-beam technologies but also between DXA instruments produced by different manufacturers. Moreover, studies show inter- and intrainstrument variation between identical DXA instruments. Such inter- and intrascan variability between instruments can be compounded by the particular patient population being investigated. The objective of this review is to discuss inter- and intradevice variation of DXA instruments and to outline quality control procedures that should be implemented prior to initiating short-term single or multicenter clinical trials that use DXA to investigate the effects of an intervention on loss or accretion of lean or fat mass.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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