Effect of sleep restriction on somatosensory sensitivity in the oro‐facial area: An experimental controlled study
Bibliographic record
Abstract
BACKGROUND: No studies have addressed the effect of SR on somatosensory function in the oro-facial area. OBJECTIVES: The aim of this study was to investigate the effect of sleep restriction (SR) on the somatosensory perception of the tip of the tongue. MATERIALS AND METHODS: Using a crossover study design, 13 healthy participants took part in a random order, to a two arms experiments: the SR and control/no SR-arms. For all participants, the Epworth Sleepiness Scale (ESS) was used to assess sleepiness and mechanical sensitivity, and pain detection threshold was estimated at the tongue tip and right thumb (as a body area control site). In the SR-arm of the study, on day one, we estimated sensory baseline perception and repeated tests on day two, after a night of voluntary SR, and on day 3, after a recovery night. In the second arm, same sensory tests were done but no SR was requested. RESULTS: Significantly more sleepiness was observed after SR in comparison with baseline and recovery testing days (P < 0.05). After SR, mechanical pain threshold on the tip of the tongue was significantly lower on day after SR (day 2) and a rebound, higher values, were observed on the third day (P < 0.05); no difference on thumb site. In the control arm, no SR and no significant differences between days were observed for all the variables of interest. CONCLUSIONS: The present results suggest that SR may affect somatosensory perception in the oro-facial area.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".