Population Differences in Postural Response Strategy Associated with Exposure to a Novel Continuous Perturbation Stimuli: Would Dancers Have Better Balance on a Boat?
Bibliographic record
Abstract
Central or postural set theory suggests that the central nervous system uses short term, trial to trial adaptation associated with repeated exposure to a perturbation in order to improve postural responses and stability. It is not known if longer-term prior experiences requiring challenging balance control carryover as long-term adaptations that influence ability to react in response to novel stimuli. The purpose of this study was to determine if individuals who had long-term exposure to balance instability, such as those who train on specific skills that demand balance control, will have improved ability to adapt to complex continuous multidirectional perturbations. Healthy adults from three groups: 1) experienced maritime workers (n = 14), 2) novice individuals with no experience working in maritime environments (n = 12) and 3) individuals with training in dance (n = 13) participated in the study. All participants performed a stationary standing task while being exposed to five 6 degree of freedom motions designed to mimic the motions of a ship at sea. The balance reactions (change-in-support (CS) event occurrences and characteristics) were compared between groups. Results indicate dancers demonstrated significantly fewer CS events than novices during the first trial, but did not perform as well as those with offshore experience. Linear trend analyses revealed that short-term adaptation across all five trials was dependent on the nature of participant experience, with dancers achieving postural stability earlier than novices, but later than those with offshore experience. These results suggest that long term previous experiences also have a significant influence on the neural control of posture and balance in the development of compensatory responses.
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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) | 0.002 | 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".