Non-invasive measurement of tibialis anterior muscle temperature during rest, cycling exercise and post-exercise recovery
Bibliographic record
Abstract
We introduce a non-invasive and accurate method to assess tibialis anterior muscle temperature (Tm) during rest, cycling exercise, and post-exercise recovery using the insulation disk (INDISK) technique. Twenty-six healthy males (23.6 ± 6.2 years; 24.1 ± 3.1 body mass index) were randomly allocated into the 'model' (n = 16) and the 'validation' (n = 10) groups. Participants underwent 20 min supine rest, 20 min cycling exercise at 60% of age-predicted maximum heart rate, and 20 min supine post-exercise recovery. In the model group, Tm (34.55 ± 1.02 °C) was greater than INDISK temperature (Tid; 32.44 ± 1.23 °C; p < 0.001) and skin surface temperature (Tsk; 29.84 ± 1.47 °C; p < 0.001) throughout the experimental protocol. The strongest prediction model (R(2) = 0.646) incorporated Tid and the difference between the current Tid temperature and that recorded four minutes before. No mean difference (p > 0.05) and a strong correlation (r = 0.804; p < 0.001) were observed between Tm and predicted Tm (predTm) in the model group. Cross-validation analyses in the validation group demonstrated no mean difference (p > 0.05), a strong correlation (r = 0.644; p < 0.001), narrow 95% limits of agreement (-0.06 ± 1.51), and low percent coefficient of variation (2.24%) between Tm (34.39 ± 1.00 °C) and predTm (34.45 ± 0.73 °C). We conclude that the novel technique accurately predicts Tm during rest, cycling exercise, and post-exercise recovery, providing a valid and cost-efficient alternative when direct Tm measurement is not feasible.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".