Multiple propane gas burn rates procedure to determine accuracy and linearity of indirect calorimetry systems: an experimental assessment of a method
Bibliographic record
Abstract
Objective Indirect calorimetry (IC) systems measure the fractions of expired carbon dioxide (F e CO 2 ), and oxygen (F e O 2 ) recorded at the mouth to estimate whole-body energy production. The fundamental principle of IC relates to the catabolism of high-energy substrates such as carbohydrates and lipids to meet the body’s energy needs through the oxidative process, which are reflected in the measured oxygen uptake rates (V̇O 2 ) and carbon dioxide production rates (V̇CO 2 ). Accordingly, it is important to know the accuracy and validity of V̇O 2 and V̇CO 2 measurements when estimating energy production and substrate partitioning for research and clinical purposes. Although several techniques are readily available to assess the accuracy of IC systems at a single point for V̇CO 2 and V̇O 2 , the validity of such procedures is limited when used in testing protocols that incorporate a wide range of energy production ( e.g. , basal metabolic rate and maximal exercise testing). Accordingly, we built an apparatus that allowed us to manipulate propane burn rates in such a way as to assess the linearity of IC systems. This technical report aimed to assess the accuracy and linearity of three IC systems using our in-house built validation procedure. Approach A series of trials at different propane burn rates (PBR) ( i.e. , 200, 300, 400, 500, and 600 mL min −1 ) were run on three IC systems: Sable, Moxus, and Oxycon Pro. The experimental values for V̇O 2 and V̇CO 2 measured on the three IC systems were compared to theoretical stoichiometry values. Results A linear relationship was observed between increasing PBR and measured values for V̇O 2 and V̇CO 2 (99.6%, 99.2%, 94.8% for the Sable, Moxus, and Jaeger IC systems, respectively). In terms of system error, the Jaeger system had significantly ( p < 0.001) greater V̇O 2 (mean difference ( M) = −0.057, standard error ( SE) = 0.004), and V̇CO 2 ( M = −0.048, SE = 0.002) error compared to either the Sable (V̇O 2 , M = 0.044, SE = 0.004; V̇CO 2 , M = 0.024, SE = 0.002) or the Moxus (V̇O2, M = 0.046, SE = 0.004; V̇CO 2 , M = 0.025, SE = 0.002) IC systems. There were no significant differences between the Sable or Moxus IC systems. Conclusion The multiple PBR approach permitted the assessment of linearity of IC systems in addition to determining the accuracy of fractions of expired gases.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".