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Record W2138728261 · doi:10.1080/10255841003630652

The relationship between trunk muscle activation and trunk stiffness: examining a non-constant stiffness gain

2010· article· en· W2138728261 on OpenAlex

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 · 2010
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Waterloo
FundersMcGill University
KeywordsStiffnessTorsoMuscle stiffnessDimensionless quantityTrunkInstabilityMechanicsControl theory (sociology)MathematicsMaterials scienceStructural engineeringPhysicsComputer scienceAnatomyMedicineControl (management)EngineeringBiology

Abstract

fetched live from OpenAlex

The relationship between muscle activation, force and stiffness needs to be known to interpret the stability state of the spine. To test the relationship between these variables, a quick release approach was used to match quantified torso stiffness with an EMG activation-based estimate of individual muscle stiffnesses. The relationship between activation, force and stiffness was modelled as k = q x F/l, where k, F and l are muscle stiffness, force and length, respectively, and q is the dimensionless stiffness gain relating these variables. Under the tested experimental scenario, the 'stiffness gain', q, which linked activation with stiffness, demonstrated a decreasing trend with increasing levels of torso muscle activation. This highlights the likelihood that the choice of a single q value may be over simplistic to relate force to stiffness in muscles that control the spine. This has implications for understanding the potential for spine instability in situations requiring high muscular demand.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.031
GPT teacher head0.296
Teacher spread0.265 · 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