Official Position of the Brazilian Association of Bone Assessment and Metabolism (ABRASSO) on the evaluation of body composition by densitometry—part II (clinical aspects): interpretation, reporting, and special situations
Bibliographic record
Abstract
OBJECTIVE: To present an updated and evidence-based guideline for the use of dual-energy x-ray absorptiometry (DXA) to assess body composition in clinical practice. MATERIALS AND METHODS: This Official Position was developed by the Scientific Committee of the Brazilian Association of Bone Assessment and Metabolism (Associação Brasileira de Avaliação Óssea e Osteometabolismo, ABRASSO) and experts in the field who were invited to contribute to the preparation of this document. The authors searched current databases for relevant publications in the area of body composition assessment. In this second part of the Official Position, the authors discuss the interpretation and reporting of body composition parameters assessed by DXA and the use of DXA for body composition evaluation in special situations, including evaluation of children, persons with HIV, and animals. CONCLUSION: This document offers recommendations for the use of DXA in body composition evaluation, including indications, interpretation, and applications, to serve as a guiding tool in clinical practice and research for health care professionals in Brazil.
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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 | 0.024 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".