Postural Control Follows a Bi-Phasic Alteration Pattern During Mountain Ultra-Marathon
Bibliographic record
Abstract
It is well knows that postural control (PC) is deteriorated with neuromuscular fatigue, altitude or sleep deprivation induced by a mountain ultra-marathon (MUM). Several regulatory mechanisms have also been reported during this type of event and the changes in PC at different points of MUM remain unknown. The purpose of this study was to investigate the time course of PC during an extreme MUM. We tested the hypothesis that PC alteration would not increase linearly. Method: 16 participants (age 45.1±9.6 yr) were tested bipedaly on a posturographic platform for 51.2s with eyes open every ~50 km. Both traditional and stabilogramm diffusion analyses (SDA) were performed. A visual analog scale (VAS) was used for a subjective evaluation of global fatigue, sleep feeling and pain. Results: The main parameters (center of pressure trajectory analysis) increased significantly (p<0.001, d= 1.56, very large) until km 100. This was confirmed by SDA in the antero-posterior plane. Short term effective diffusion coefficient significantly increased (p<0.001, d=1.07, very large) as critical point (p<0.01, d=1.57, very large). From km 100 to 200, a different response was observed with a continuous decrease in most of the PC parameters. This was confirmed by SDA in the antero-posterior plane. Short term effective diffusion coefficient significantly increased (p<0.001, d=1.39, very large) as critical point (p<0.01, d=1.51, very large). Conclusion: Posture alteration is progressively increased until 100 km. After this point, compensatory mechanisms appear to limit the posture degradation. This bi-phasic response is of interest for better understanding the coping with extreme fatigue.
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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 | 0.001 |
| 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) | 0.001 | 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".