Multiple propane gas flow 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 in order to estimate whole body energy production (EP). The fundamental principal of IC relates to oxidative mechanisms, expressed as rate of oxygen uptake (V̇O 2 ) and carbon dioxide production (V̇CO 2 ). From these volumes we calculate energy production and respiratory exchange ratio which is used to estimate substrate utilization rates. The accuracy of IC systems is critical to detect small changes in respiratory gas exchanges. The aim of this technical report was to assess the accuracy and linearity of IC systems using multiple propane gas flow rates procedure. Approach: A series of propane gas with different flow rates and ventilation rates were run on three different IC systems. The actual experimental V̇O 2 and V̇CO 2 were calculated and compared to stoichiometry theoretical values. Results: showed a linear relationship between gas volumes (V̇O 2 and V̇CO 2 ) and propane gas flows (99.6%, 99.2%, 94.8% for the Sable, Moxus, and Jaeger metabolic carts, respectively). In terms of system error, Jaeger system had significantly ( p < 0.001) greater V̇O 2 ( M = -0.057, 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) metabolic carts. There were no significant differences between the Sable or Moxus metabolic carts. Conclusion: The multiple flow rates 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 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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".