Community-Based Performance of a Pelvic Stabilization Device for Children With Spasticity
Bibliographic record
Abstract
We developed a new type of pelvic stabilization device designed to help children be better positioned in their wheelchairs. The device replaces a wheelchair lap belt by providing firm anterior pelvic support for the seated user. We developed, tested, and evaluated instructions for installing, fitting, and using the device to study its performance in "typical" community settings in Toronto, Canada. Each of four therapists worked with a local rehabilitation technology supplier to install and fit the device onto an adaptive wheelchair seating system for a young child between 5 and 10 years of age. Therapists assessed the system's positioning effects, and children used the system for 12-14 days. Following the trials, therapists, parents, and children reported their levels of satisfaction with the performance of the device as compared with the children's existing lap belts. Participating therapists confirmed that the device provided better anterior pelvic stability for their clients. Parents felt that their children were generally better positioned in their seats and thought that the device was easy to use. Children had similar perspectives. Suppliers were confident that they could readily install the devices following the instructions provided. Based on the opinions of participants and our inspection of the installed devices, we proposed that minor modifications be made to the product design and instructions for installation, fitting, and use.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".