Whole-body hypothermia has central and peripheral influences on elbow flexor performance
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Bibliographic record
Abstract
The superimposed twitch technique was used to study the effect of whole-body hypothermia on maximal voluntary activation of elbow flexors. Seven subjects [26.4 ± 4 years old (mean ± SD)] were exposed to 60 min of either immersion in 8°C water (hypothermia) or sitting in 22°C air (control). Voluntary activation was assessed during brief (3 s) maximal voluntary contractions (MVCs) and then during a 2 min fatiguing sustained MVC. Hypothermia (core temperature 34.8 ± 0.9°C) decreased maximal voluntary torque from 98.2 ± 1.0 to 82.8 ± 5.8% MVC (P < 0.001) and increased central conduction time from 7.9 ± 0.4 to 9.1 ± 0.7 ms (P < 0.05). Hypothermia also decreased maximal resting twitch amplitude from 17.6 ± 4.0 to 10.0 ± 1.7% MVC (P < 0.005) and increased the time-to-peak twitch tension from 55.4 ± 4.0 to 79.0 ± 11.7 ms (P < 0.001). During the 2 min contraction, hypothermia decreased initial torque (P < 0.01) but attenuated the subsequent rate of torque decline (control from 95.5 ± 4 to 29.4 ± 8% MVC; and hypothermia from 85.3 ± 8 to 37.3 ± 5% MVC; P < 0.01). Cortical superimposed twitches increased as fatigue developed but were always lower in the hypothermic conditions. Cortical superimposed twitches increased from a value of 0.4 ± 0.3% MVC prefatigue to 3.9 ± 1.4% MVC postfatigue (P < 0.001) in the hypothermic conditions and from 1.7 ± 0.9 to 5.5 ± 2.3% MVC in control conditions. Our results suggest that hypothermia decreases MVCs primarily via peripheral mechanisms and attenuates the rate of fatigue development by reducing central fatigue.
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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) | 0.002 | 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 it