Perception of Weight-Bearing Distribution during Sit-to-Stand Task in Healthy Young and Elderly Individuals
Bibliographic record
Abstract
The first objective was to assess whether healthy individuals could accurately estimate their weight-bearing distribution in sit-to-stand transfers. The second was to evaluate the effect of age on weight-bearing perception. 16 young participants (11 women, 5 men; M age 29 yr., SD = 8.7) and 15 elderly participants (7 women, 8 men; M age 65 yr., SD = 3.8) were recruited. Verbal instructions and visual feedback referring to different percentages of weight-bearing distribution to execute were used to quantify weight-bearing perception in sit-to-stand tasks. For the feedback approach, the perception was assessed with a visual analog scale. For the verbal task, the weight-bearing distribution produced was assessed with force plates. Both young and elderly participants had good perception of weight-bearing distribution, with mean absolute errors of 6.4%. Moreover, their perceived and real weight-bearing distribution showed good agreement (ICC > or = .79).
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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) | 0.001 | 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".