Benefit of "rysis" : A Wheelchair Seated Posture Measurement Based on ISO 16840-1
Bibliographic record
Abstract
This article is of a measurement method of wheelchair seated posture. First, we have reported a brief outline of ISO 16840-1 world standard regarding posture while seated in a wheelchair; the standard specifies a global coordinate system. We also introduced measurement tools based on ISO 16840 and the current Japanese clinical works using the tools. Secondly, we have reported how to use "rysis", the ISO standard-based wheelchair seated posture measurement (WSPM) software, which was invented by one of the authors Takashi Handa innovated in 2008. Since 2009, we have been promoting clinical application of "rysis". As of June 2014, the number of distribution facilities of the "rysis" was over 300 in the world. Thirdly, we have reported how to conduct a survey using "rysis" and have stated the results of the research. We have presented our research booth during the Barrie Free Trade Show (BF), which has annually held with almost one hundred thousand visitors at Intec Osaka, Osaka, Japan. From BF visitors in the past six years, a total of 266 daily wheelchair users participated in the research. Our measurement results can directly visualize their wheelchair seated posture. We have been developing skills and knowledge for clinical application and improving the software usability, Finally, we concluded the benefit of "rysis" that include empowerment of people with disability and the educational impact on both consumers and students.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".