A wireless personal wearable network system to understand the biomechanics of orthotic for the treatment of scoliosis
Bibliographic record
Abstract
The wear tightness of an orthosis for the treatment of scoliosis varies greatly during daily activities. Currently, there is no commercially available product that can monitor force distribution inside the brace and the time that the othosis is worn during daily activities. Subjective feeling is the most commonly used method. To provide an objective measure, a battery-powered wireless personal wearable network system is developed. This system consists of up to 16 wireless force loggers and a USB ZigBee dongle. Each logger contains a force sensor and a wireless unit. The whole system records how much time the orthosis has been used and how loads distribute inside the orthoses. Laboratory tests have been performed; the maximum force measurement error is +/-0.02N and the resolution is 0.1N. The average power consumption of the system is 0.3mW/h and thus a single AAA-sized alkaline battery is able to support the power for 6 months.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 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".