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Record W1542968084 · doi:10.1002/mus.24309

Effects of changes in muscle activation level and spine and hip posture on erector spinae fiber orientation

2014· article· en· W1542968084 on OpenAlexafffund
Alexandra Harriss, Stephen H.M. Brown

Bibliographic record

VenueMuscle & Nerve · 2014
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineAnatomyLumbarSittingErector spinae musclesElectromyographyLumbar spineOrientation (vector space)Physical medicine and rehabilitationSurgeryGeometryMathematics

Abstract

fetched live from OpenAlex

INTRODUCTION: During lumbar flexion, the fiber orientation of the lumbar erector spinae (LES) muscle becomes oriented more along the spine compressive axis. It is unknown how changes in LES activation effect fiber orientation. METHODS: Ultrasound images of LES were collected during 2 sets of experimental conditions: (1) varying levels of LES activation while lying prone; and (2) varying spine and hip angles while seated. Electromyographic activity and lumbar spine and hip angles were also recorded. RESULTS: As LES activation increased, increases in fiber orientation (signifying increased orientation along the posterior shear axis) were found (P<0.001). Compared with the relaxed sitting posture, decreases in fiber orientation were found with full spine flexion and combined spine and hip flexion (P<0.001), but there were no changes with full hip flexion alone. CONCLUSIONS: Activation magnitude and spine posture both affect LES fiber orientation, thus modifying its ability to protect the spine against anterior shear 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2014
Admission routes2
Has abstractyes

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