Comparison of 2 Accelerometers for Assessing Daily Energy Expenditure in Adults
Bibliographic record
Abstract
Background: Daily energy expenditure (EE) assessment plays an important role in clinical strategies for lifestyle-related diseases. The purpose of this study was to compare the performance of 2 activity monitors from different manufacturers to estimate total energy expenditure (TEE) and physical activity related-energy expenditure (PAEE) in daily living conditions. Methods: Sixteen adults stayed in a respiratory chamber for 24 h. The subjects wore 2 accelerometers based on uniaxial (Lifecorder; UNI) and triaxial accelerometry (Tritrac-R3D; TRI). Results: A highly significant correlation was observed between measured TEE and estimated values (r=0.868 in UNI and r=0.819 in TRI; P<0.001). However, TEE and PAEE were significantly underestimated: TEEUNI by -9% and TEETRI by -12%; PAEEUNI by -10% and PAEETRI by -55%. Conclusions: The EE of structured activity was adequately estimated by both accelerometers, whereas the EE of the non-structured activities involved much more errors. The results also suggest that the algorithm for EE calculation may be more important than the number of planes used for detecting acceleration.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".