Relationship between postabsorptive respiratory exchange ratio and plasma free fatty acid concentrations
Bibliographic record
Abstract
The relationship between overnight postabsorptive (fasting) respiratory exchange ratio (RER) and plasma FFA concentrations was addressed using data from three separate protocols, each of which involved careful control of the antecedent diet. Protocol 1 examined the relationship between fasting RER and the previous daytime RER. In Protocol 2 fasting, RER and plasma palmitate concentrations were measured in 29 women and 31 men (body mass index <30 kg.m(-2)). Protocol 3 analyzed data from Nielsen et al. (Nielsen, S., Z. K. Guo, J. B. Albu, S. Klein, P. C. O'Brien, M. D. Jensen. 2003. Energy expenditure, sex and endogenous fuel availability in humans. J. Clin. Invest. 111: 981-988.) to understand how fasting RER and palmitate concentrations relate within individuals during four consecutive measurements. The results were as follows: 1) Fasting RER was correlated (r = 0.74, P < 0.001) with the previous day's average RER, and less so with RER variability. 2) Fasting RER was correlated (r = -0.39, P = 0.007) with fasting plasma palmitate concentrations. 3) The pattern of the RER/palmitate relationship was similar within individuals and between individuals; a negative slope was observed significantly more often than a positive slope (chi(2) test; P < 0.001). Our findings suggest that, despite a fixed food quotient, the slight departures from energy equilibrium in a controlled General Clinical Research Center environment can effect plasma FFA concentrations. We suggest that including indirect calorimetry as part of FFA metabolism studies may aid in data interpretation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| 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".