Exogenous Ketone Salt Supplementation and Whole-Body Cooling Do Not Improve Short-Term Physical Performance
Bibliographic record
Abstract
Exogenous ketone supplementation and whole-body cooling (WBC) have shown to independently influence exercise metabolism. Whether readily available ketone salts, with and without WBC, would provide similar metabolic benefits during steady-state aerobic and time-trial performances was investigated. Nine active males (VO2peak: 56.3 ± 2.2 mL·kg−1·min−1) completed three single-blind exercise sessions preceded by: (1) ingestion of placebo (CON), (2) ketone supplementation (0.3 g·kg−1 β-OHB) (KET), and (3) ketone supplementation with WBC (KETCO). Participants cycled in steady-state (SS, 60% Wmax) condition for 30-min, immediately followed by a 15-min time trial (TT). Skin and core temperature, cardio-metabolic, and respiratory measures were collected continuously, whereas venous blood samples were collected before and after supplementation, after SS and TT. Venous β-OHB was elevated, while blood glucose was lower, with supplementation vs. CON (p < 0.05). TT power output was not different between conditions (p = 0.112, CON: 190 ± 43.5 W, KET: 185 ± 40.4 W, KETCO: 211 ± 50.7 W). RER was higher during KETCO (0.97 ± 0.09) compared to both CON (0.88 ± 0.04, p = 0.012) and KET (0.88 ± 0.05, p = 0.014). Ketone salt supplementation and WBC prior to short-term exercise sufficiently increase blood β-OHB concentrations, but do not benefit metabolic shifts in fuel utilization or improve time trial performance.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".