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Record W2289738973 · doi:10.1186/1748-7161-10-s1-o38

Ultrasound-assisted brace casting for adolescent idiopathic scoliosis

2015· article· en· W2289738973 on OpenAlexaff
Edmond Lou, Amanda CY Chan, Andreas Donauer, Melissa Tilburn, Doug Hill

Bibliographic record

VenueScoliosis · 2015
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsAlberta HealthUniversity of AlbertaAlberta Health Services
Fundersnot available
KeywordsMedicineIdiopathic scoliosisBraceUltrasoundOrthopedic surgeryScoliosisPathologyMedical physicsOrthodonticsRadiologySurgeryEngineering

Abstract

fetched live from OpenAlex

Objectives There is a short period during rapid growth when a scoliosis brace is most effective. In standard practice, the inbrace correction is not measured during brace casting. The first assessment of the in-brace correction in the follow-up clinic may trigger brace adjustment for improved spinal alignment resulting in delay of effective treatment and increased number of radiographs. The objective was to investigate if real-time ultrasound (US) can aid orthotists in determining the pad pressure level and location resulting in optimal in-brace correction of the spine.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.110
GPT teacher head0.341
Teacher spread0.231 · 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.

Study designObservational
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

Citations7
Published2015
Admission routes1
Has abstractyes

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