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Record W1966982155 · doi:10.1186/1748-7161-5-s1-o35

Development of biomechanical measures to assist in the prediction of early progression in idiopathic scoliosis

2010· article· en· W1966982155 on OpenAlexaff
Karl Zabjek, Reinhard Zeller

Bibliographic record

VenueScoliosis · 2010
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePhysical medicine and rehabilitationScoliosisSpinal CurvaturesPelvisPhysical therapySurgery

Abstract

fetched live from OpenAlex

Idiopathic scoliosis (IS) is a class of paediatric spinal deformities that has historically posed a significant challenge to the orthopaedic and scientific community. Our understanding of the underlying mechanisms associated with the early progression to advanced stages that require surgical intervention is limited. Current clinical models of assessment provide limited insight into the biomechanical and neuromuscular factors that contribute to the alignment and stability of the spine. There is an emerging recognition that new insight into the factors that affect spinal stability and the progression of a spinal deformity may be gained by expanding current observational techniques beyond the clinic. Technological innovations and advancements in analytical techniques have provided a unique opportunity to develop measurements of neuromuscular function and spinal stability. The overall aim of our present work is to develop new biomechanical measures that will provide insight into the factors that contribute to the early progression of IS. The first specific aim of this pilot project is to further develop a technique that will provide a localized estimate of the asymmetric positioning of the Centre of Mass (COM) in relation to the underlying skeletal structures of the pelvis (sacrum) and spine (apex of spinal curvature). The second specific aim is to determine the association between these measures with persistent asymmetric posture and muscle activation patterns during the performance of dynamic activities that are typical of every day life. To achieve these objectives we are currently developing a mixed methods approach that includes the coupling of a radiological, biomechanical and ambulatory monitoring assessment. This includes a 3D assessment of the spine utilizing EOS to characterize the spinal deformity, and a dynamic assessment that is focused on characterizing the dynamic patterns of muscle activity and movement. This latter component of the project involves an in laboratory biomechanical assessment with a multiple camera Vicon and 16 channel EMG system, and an out of lab ambulatory monitoring assessment. This initial study will provide the foundation to conduct future work focused on identifying new biomechanical factors that are positively associated with the early progression of IS.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.046
GPT teacher head0.326
Teacher spread0.279 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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