Fuel selection during intense shivering in humans: EMG pattern reflects carbohydrate oxidation
Bibliographic record
Abstract
The thermogenic response of humans depends critically on the coordination of muscle fibre recruitment and oxidative fuel metabolism. The primary goal of this study was to determine whether the electromyographic (EMG) pattern of muscle recruitment could provide metabolic information on oxidative fuel selection during high-intensity shivering. EMG activity (of 8 large muscles) and fuel metabolism were monitored simultaneously in non-acclimatized adult men during high-intensity shivering. Even though acute cold exposure elicited similar changes in metabolic rate among subjects, lipid and carbohydrate use was very different. Depending on the subject, the cold-induced increase in carbohydrate (CHO) oxidation ranged between 2- and 8-fold, with CHO accounting for 33-78% of total heat production, and lipids for 14-60%. This high variability in fuel selection was primarily explained by differences in 'burst shivering' rate, indicating that the recruitment of type II fibres plays a key role in orchestrating fuel selection. This study is the first to show that the pattern of muscle recruitment can provide quantitative information on energy metabolism. Future work should focus on the study of shivering bursts that may provide essential clues on what limits human survival in the cold.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".