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Record W2416998787 · doi:10.3233/978-1-60750-932-5-218

Brace Monitoring System for the Treatment of Scoliosis

2002· article· en· W2416998787 on OpenAlexaff
E. Lou, James Raso, Douglas L. Hill, N.G. Durdle, James Mahood, Marc Moreau

Bibliographic record

VenueStudies in health technology and informatics · 2002
Typearticle
Languageen
FieldEngineering
TopicMedical Imaging and Analysis
Canadian institutionsCapital District Health Authority
Fundersnot available
KeywordsBraceScoliosisComputer scienceMedicineEngineeringSurgeryStructural engineering

Abstract

fetched live from OpenAlex

Determining the efficacy of brace treatment for AIS has been hampered by poor data on the wear pattern of those children prescribed this treatment. Although there is some information on brace compliance, there is very little on how well the brace is secured and the resulting loads imposed on the trunk. The purpose of this study was to determine the daily brace wear pattern of adolescents prescribed Boston braces. The brace monitoring system consists of a force transducer and a microcomputer unit. A force transducer was placed in the lining of the Boston brace. The microcomputer unit was carried while the brace was worn. The force imposed by the brace pad during daily activity was recorded at 1 minute intervals over a period of 3 to 14 days. The samples were stored by the microcomputer. Five subjects (3F;2M; age: 14+/-2 years) who were to wear the brace full time were studied. The subjects adjusted their braces to a prescribed level of tightness as indicated by a light on the microcomputer. Overall compliance, compliance during school days, and forces imposed by the brace were analysed. The force provided by the Boston brace varies considerably during daily activity. Overall brace compliance was lower than expected, with 2 of 5 subjects wearing their brace infrequently. The compliance rate during school time was not different than during the rest of the study period. Peer pressure at school did not appear to affect brace compliance.

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.

How this classification was reachedexpand

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.159

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 head0.055
GPT teacher head0.330
Teacher spread0.275 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2002
Admission routes1
Has abstractyes

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