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Record W1994097308 · doi:10.1152/jn.00511.2005

A Role for Hip Position in Initiating the Swing-to-Stance Transition in Walking Cats

2005· article· en· W1994097308 on OpenAlexaff
David A. McVea, J. Maxwell Donelan, Atsumichi Tachibana, K. G. Pearson

Bibliographic record

VenueJournal of Neurophysiology · 2005
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSwingAnklePhysical medicine and rehabilitationHip flexionMedicinePsychologyAnatomyPhysical therapyRange of motionPhysics

Abstract

fetched live from OpenAlex

In this investigation, we obtained data that support the hypothesis that afferent signals associated with hip flexion play a role in initiating the swing-to-stance transition of the hind legs in walking cats. Direct evidence came from observations in walking decerebrate cats. Assisting the flexion of the hip joint during swing advanced the onset of activity in ankle extensor muscles, and this advance was strongly correlated with a reduction in the duration of hip flexor muscle activity. The hip angle at the time of onset of the flexion to extension transition was similar during assisted and unassisted steps. Additional evidence for the hypothesis that sensory signals related to hip flexion are important in regulating the swing-to-stance transition came from four normal animals trained to walk in a variety of situations designed to alter the coordination of movements at the hip, knee, and ankle joints during the swing phase. Although there were exceptions in some tasks and preparations, the angle of the hip joint at the time of onset of extensor activity was generally less variable than that of the knee and ankle joints. We also found no clear relationships between the angle of the limb and body axes, or the length of the limb axis, and the time of onset of extensor activity. Finally, there were no indications that the stretching of ankle extensor muscles during swing was a factor in regulating the transition from swing-to-stance.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.208

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations86
Published2005
Admission routes1
Has abstractyes

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