Dynamic postural control and associated attentional demands in contemporary dancers versus non-dancers
Bibliographic record
Abstract
Postural control is not a fully automatic process, but requires a certain level of attention, particularly as the difficulty of the postural task increases. This study aimed at testing whether experienced contemporary dancers, because of their specialized training involving the control of posture/balance, would present with a dual-task performance suggesting lesser attentional demands associated with dynamic postural control compared with non-dancers. Twenty dancers and 16 non-dancers performed a dynamic postural tracking task in both antero-posterior and side-to-side directions, while standing on a force platform. The postural task was performed, in turn, 1) as a stand-alone task, and concurrently with both 2) a simple reaction time task and 3) a choice reaction time task. Postural control performance was estimated through variables calculated from centre of pressure movements. Although no overall group difference was found in reaction time values, we found a better ability to control the side to side movements of the centre of pressure during the tracking task in dancers compared with non-dancers, which was dependent on the secondary task. This suggests that such increased ability is influenced by available attentional resources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".