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Record W2254188759 · doi:10.1152/jappl.2001.91.3.1307

Muscle activity in the leg is tuned in response to ground reaction forces

2001· article· en· W2254188759 on OpenAlex
James M. Wakeling, Vinzenz von Tscharner, Benno M. Nigg, Pro Stergiou

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.

Bibliographic record

VenueJournal of Applied Physiology · 2001
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBicepsVastus medialisGround reaction forceElectromyographyPhysical medicine and rehabilitationMedicineAnatomyPhysicsKinematics

Abstract

fetched live from OpenAlex

During walking and running, the human body reacts to its external environment. One such response is to the impact forces that occur at heel strike. This study tested previous speculation that the levels of muscle activity in the lower extremities are adjusted in response to the loading rate of the impact forces. A pendulum apparatus was used to deliver repetitive impacts to the heels of 20 subjects. Impact forces were of similar magnitude to those experienced during running, but the loading rate was varied by 13% using different materials in the subjects' shoes. Myoelectric patterns were measured in the tibialis anterior, medial gastrocnemius, vastus medialis, and biceps femoris muscles. Wavelet analysis was used to resolve intensity of the myoelectric patterns into time and frequency space. Substantial and significant differences in the myoelectric activity occurred between the impact conditions for the 50 ms before and the 50 ms after impact, reaching 3 ms in timing, 16% in wavelet number, and 154% in the intensity of the muscle activity.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.258

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)0.0000.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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