Intelligent Brace System for the Treatment of Scoliosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Measurement of the biomechanical effectiveness of a brace for the treatment of scoliosis has been hampered by the lack of compressive information about wear characteristics. Orthotists and orthopaedic surgeons believe that the effectiveness of bracing is correlated with the strap tensions. If the strap tensions can be maintained at the optimal level while patients wear their braces, a better treatment outcome may be obtained. However, strap tensions vary significantly during different activities. An intelligent brace system has been developed to control the strap tension so that the optimal prescribed level is maintained at all time. This system consists of an innovative strap tension transducer, a microcomputer unit and a motorized unit. The strap transducer has been developed with an accuracy +/- 1.0N in the range of 0 to 100N. An instrumented Boston brace was built to test the concept. When the strap tension was below 80% of the prescribed level for a 15 minutes interval, the microcomputer unit signaled the motor to tighten the strap. While the strap tension level was above 120% of the prescribed level for a 15 minutes interval, the motor reversed the direction. Laboratory testing results showed that the strap tension could be maintained at the optimal prescribed level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it