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Record W2397852956 · doi:10.3233/978-1-61499-067-3-338

Smart Brace versus Standard Rigid Brace for the Treatment of Scoliosis: A Pilot Study

2012· article· en· W2397852956 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in health technology and informatics · 2012
Typearticle
Languageen
FieldEngineering
TopicMedical Imaging and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBraceScoliosisMedicineIdiopathic scoliosisPhysical medicine and rehabilitationPhysical therapyOrthodonticsComputer scienceSurgeryEngineeringStructural engineering

Abstract

fetched live from OpenAlex

The outcomes of brace treatment for scoliosis depend on how the brace is used. Simply prescribing a brace does not mean it will be worn properly. A smart brace has been developed to control the brace wear tightness with the expectation that appropriately worn braces will improve outcomes. Twelve brace candidates (10F; 2M) agreed to participate into this study and were randomly divided into 2 groups. The smart brace group used the smart brace for the first year, and then wore the standard brace for the following year. The standard rigid brace group wore their TLSO for 2 years. Both groups were followed for 3 years after they finished the brace treatment. The smart brace group showed better quality of brace wear, wearing their brace at the prescribed tightness level a higher proportion of time than the standard brace group. All subjects in the smart brace group had successful outcomes, Cobb angle changed less than 5°, whereas 2/6 subjects in the standard brace group had unsuccessful bracing. One had 7° increment and 1 underwent surgery. The smart brace group also reported that the smart brace was more comfortable to wear than the standard rigid brace.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.375
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it