Feasibility, Reproducibility and Cold-Induced Energy Expenditure using Whole-Room Calorimetry in Adults and Children
Bibliographic record
Abstract
Abstract Context To understand energy balance, whole-room indirect calorimetry (WRIC) allows for accurate measurement of energy expenditure (EE). Objectives To examine the relationship between cold-induced resting EE and brown adipose tissue (BAT) activity measured by MRI, evaluate WRICS performance and feasibility of use in children and adults. Methods The WRICS was equipped with a Promethion High-Definition Room Calorimetry system. Technical validation utilized N2 and CO2 gas infusions. Healthy adults and children (8 years and older) attended two 4-hour WRIC visits (one week apart) and one MRI visit. Resting EE at 25°C (REE 25 ) was compared between visits and to REE at 18°C (REE 18 ). Recruitment and completion rates were examined. BAT activity was assessed by MRI as the decline in supraclavicular proton density fat fraction during 18°C cold exposure. Results Gas infusion testing confirmed high accuracy (RER=0.99; 95% CI 0.991–0.996). Study completion rates were high (Adults: 20/21; Children: 18/18). REE 25 was consistent between visits (Adults: 1.59 vs 1.63 kcal/min, p=0.56; Children: 1.57 vs 1.56 kcal/min, p=0.76) with good reproducibility (ICC Adults: 0.766; Children: 0.887). Cold exposure increased REE by 0.23 kcal/min (adults) and 0.18 kcal/min (children). BAT activity correlated with REE 18 in both groups (Adults: r=0.51, p=0.03; Children: r=0.64, p=0.03). Conclusion WRICS use was feasible in adults and children. The WRICS measurement was accurate, measures of REE were reproducible and changes in EE during cold were measurable, and related to BAT activity, supporting the usefulness of this system in the assessment of EE in response to interventions in adults and children.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".