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Record W2128813204 · doi:10.1177/0954411915597258

Braided tubular superelastic cables provide improved spinal stability compared to multifilament sublaminar cables

2015· article· en· W2128813204 on OpenAlexaff
Jaëlle Tremblay, Jean‐Marc Mac‐Thiong, Vladimir Braïlovski, Yvan Petit

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsÉcole de Technologie SupérieureHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMaterials scienceFixation (population genetics)Structural engineeringMedicineEngineering

Abstract

fetched live from OpenAlex

This study investigates the use of braided tubular superelastic cables, previously used for sternum closure following sternotomy, as sublaminar fixation method. It compares the biomechanical performance of spinal instrumentation fixation systems with regular sublaminar cables and proprietary superelastic cables. A hybrid experimental protocol was applied to six porcine L1-L4 spinal segments to compare multifilament sublaminar cables (Atlas, Medtronic Sofamor Danek, Memphis, TN) with proprietary superelastic cables. First, intact total range of motion was determined for all specimens using pure moment loading. Second, pure moments were imposed to the instrumented specimens until these intact total ranges of motion were reproduced. Compared to the intact specimens, the use of superelastic cables resulted in stiffer instrumented specimens than the use of multifilament cables for all the loading modes except axial torsion. Consequently, the superelastic cables limited the instrumented segments mobility more than the multifilament cables. Spinal instrumentation fixation systems using superelastic cables could be a good alternative to conventional sublaminar cables as it maintains a constant stabilization of the spine during loading.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
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 integrity0.0000.001
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 head0.036
GPT teacher head0.280
Teacher spread0.244 · 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 designBench or experimental
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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in MedicineSame topicSpinal Fractures and Fixation TechniquesFrench-language works237,207