Postural stability
Bibliographic record
Abstract
Purpose: Dizziness is the most common complaint of patients over 65 years consulting a physician. Presbyacusis affects 65% of Canadians aging 70–79. The inner ear is responsible for both hearing and postural stability. However, the interactions between auditory information and the maintenance of postural balance have not been widely studied. The aim of this study is to evaluate and compare the effect of auditory input on postural stability for normal hearing subjects versus hearing-aid users. Methods: The effect of auditory input on postural stability was assessed with and without earplugs in normal subjects, and in adult hearing users with and without hearing aids. Balance tests (Romberg on foam and Tandem stance) were performed in the presence of a point-source of noise in both groups. Results: Normal individuals’ balance performance was not affected by the absence of auditory input. However, hearing aid users had significantly better balance with hearing aids on for the Romberg test ( v = 36, p = .014), and for the Tandem test ( v = 44, p = .012). Conclusion: Auditory input does not seem to have an effect on postural stability in normal hearing individuals. However, hearing aid users had a significant improvement in the presence of an auditory input.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".