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Record W4407986863 · doi:10.1080/10255842.2025.2470796

Biomechanical modeling and assessment of patient positioning to facilitate spinal deformity instrumentation

2025· article· en· W4407986863 on OpenAlex
Xiaoyu Wang, Guillaume Imbleau-Chagnon, Christiane Caouette, A. Noelle Larson, Carl‐Éric Aubin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2025
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsPolytechnique MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInstrumentation (computer programming)KyphosisLumbarMedicineLumbar lordosisReduction (mathematics)OrthodonticsBiomechanicsCobb angleSpinal deformityFinite element methodDeformityDisplacement (psychology)SurgeryScoliosisComputer scienceRadiographyEngineeringAnatomyStructural engineeringMathematics

Abstract

fetched live from OpenAlex

Finite element models (FEM) were built based on clinical documentation of five AIS surgical cases to simulate patient positioning and spinal instrumentation. Various patient positioning and instrumentation configurations were simulated, and the associated corrections and screw pull-out forces were analyzed. Patient prone-positioning resulted in Cobb angle reduction of over 5°. Vertical, caudal, and cephalad displacement of thoracic cushions had significant impact on thoracic kyphosis. Pelvic rotation through lower-limb extension/flexion had significant effect on lumbar lordosis. The validated FEM enabled simulations of patient positioning and spinal instrumentation. Patient positioning configurations had significant effects on deformity correction and screw pull-out forces.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.046
GPT teacher head0.388
Teacher spread0.342 · 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