The Influence of Acute Back Muscle Fatigue and Fatigue Recovery on Trunk Sensorimotor Control
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate trunk repositioning sense after an acute muscle fatigue protocol and during a 30-minute recovery period. METHODS: Twenty healthy participants were asked to reproduce a 20° and 30° angle in trunk extension. Participants were tested before and after a Biering-Sorensen fatigue protocol was performed. Movement time, peak angle variable error, constant error and absolute error in peak angle were calculated and compared between 4 temporal conditions in both 20° and 30° extensions. RESULTS: The statistical analysis revealed a main effect of angle between 20° and 30° extension condition for variable error, absolute error, and movement time. A main effect of time was also found and was characterized by a significant increase in variable error between the prefatigue condition and the first postfatigue condition. During recovery, a significant decrease in variable error was observed between the first postfatigue condition and the 30-minute postfatigue condition, indicating that the variable mean scores were similar to initial values. CONCLUSION: Lower back muscle fatigue induced changes in trunk repositioning sense indicators immediately after the fatigue protocol. However, the observed changes did not last for more than a few minutes.
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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 | 0.001 | 0.003 |
| 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 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".