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Record W2294352953 · doi:10.1109/embc.2015.7319246

Simulation of high energy vertebral fractures on complete porcine specimens

2015· article· en· W2294352953 on OpenAlexaff
Yvan Petit, Dominic Boisclair, Stefan Parent, Jean‐Marc Mac‐Thiong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsUniversité de MontréalÉcole de Technologie Supérieure
Fundersnot available
KeywordsPelvisFracture (geology)Spinal canalBurst fractureLumbarLumbar vertebraeBiomechanicsComputed tomographyMaterials scienceSpinal fractureAnatomyOrthodonticsGeologyMedicineRadiologyComposite materialSpinal cord

Abstract

fetched live from OpenAlex

This work presents a novel method creating high energy vertebral fractures on complete swine specimens to investigate realistic vertebral fracture mechanisms. An apparatus was developed to maintain a porcine specimen in an upright position and apply a caudal impact simulating a fall. Five mature minipigs were impacted with varying impact magnitude. Computed tomography scans were used to assess the resulting fracture type, fracture level, spinal canal encroachment and fractures of adjacent bony structures. Lumbar fractures were produced on four specimens: three inferior endplate burst fractures (L2) and one superior endplate burst fracture (L5). One trial resulted in a hyperextension fracture between L2 and L3 vertebrae. Spinal canal encroachment was important for three specimens. No fracture was created on the pelvis or hind limbs. The proposed method developed and the resulting swine model of high energy vertebral fractures could be used to instigate novel biomechanical studies, to validate finite element models or to investigate surgical strategies.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.762

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)0.0010.000

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 head0.045
GPT teacher head0.326
Teacher spread0.281 · 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 designTheoretical or conceptual
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

Citations1
Published2015
Admission routes1
Has abstractyes

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