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Record W2075175603 · doi:10.1115/imece2003-43246

On the Stability Analysis of the Human Spine

2003· article· en· W2075175603 on OpenAlexafffund
A. Shirazi‐Adl

Bibliographic record

VenueAdvances in Bioengineering · 2003
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsPolytechnique Montréal
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsCompression (physics)KinematicsStability (learning theory)StiffnessInstabilityLumbar spineMathematicsGait cycleWork (physics)InfillComputer scienceStructural engineeringEngineeringMedicinePhysicsMechanicsMechanical engineeringSurgery

Abstract

fetched live from OpenAlex

The stability of the human spine in compression has attracted a considerable amount of attention in recent years. The passive ligamentous thoracolumbar and lumbar spines are known to exhibit large displacements or hypermobility (i.e., instability in an imperfect column) under compression loads <100N. Since such compression loads are only a small fraction of those supported by the spine even in regular daily activities, let aside the manual material handling tasks, the question arises as to how the spine is stablized in vivo? Various stabilizing mechanisms have been proposed and investigated; wrapping loading [Shirazi-Adl and Parnianpour, 2000], postural adaptations [Shirazi-Adl and parnianpor, 1999], intra-abdominal pressure [Cholewicki et al, 1999] and muscle activation/coactivation [Bergmark, 1989; Crisco and Panjabi, 1991]. In this work, a novel kinematics-based methad [Shirazi-Adl et al., 2002] is first applied to compute muscle forces and internal loads in standing postures under gravity with or without 200N loads held either on sides or close to the body in front. The stability of the system under given loads and prescribed postures is sudsequently examined using both linear bucking analysis based on the deformed configurations and nonlinear analysis while employing a liner stiffness-force relationship for muscules [Bergmark, 1989; Crico and Panjabi, 1991]. The relative accuracy of foregoing methods in stability analysis of some sample structures is also investigated. Moreover, the effect of co-activity on stability of the spine in neutral postures is studied.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.128

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.283
Teacher spread0.272 · 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
Published2003
Admission routes2
Has abstractyes

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