Understanding and measuring powered wheelchair mobility and manoeuvrability. Part I. Reach in confined spaces
Bibliographic record
Abstract
PURPOSE: To determine: (1) what wheelchair manoeuvrability factors are important and (2) the effects of powered wheelchair design on the ability to reach in a confined space. METHOD: The relative importance of five aspects of wheelchair manoeuvrability was determined through a survey of users of wheelchairs (N = 52) and health care professionals and others (N = 89). A single young, non-disabled subject undertook repeated trials of reach distance on to a counter at the end of a corridor whose width could be adjusted by moving Styrofoam walls. RESULTS: Reaching, moving in confined spaces and avoiding collisions were more important than speed and avoiding the need to drive backwards. The rear wheel drive powered wheelchair was found to allow the greatest reach when driving backwards into the space and the wheelchair which moved in a sideways direction allowed greatest reach in the narrowest corridor. CONCLUSIONS: The survey concluded that manoeuvring in small spaces and reaching without collisions were important. The powered wheelchair with sideways capability afforded the greatest reach in confined spaces except when the rear wheel drive chair was driven in backwards. The survey respondents did not place a high priority on avoiding backwards driving but some people find this difficult to do safely.
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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 | 0.010 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".