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Record W2408778168 · doi:10.1080/00222895.2015.1134433

Estimating Gait Stability: Asymmetrical Loading Effects Measured Using Margin of Stability and Local Dynamic Stability

2016· article· en· W2408778168 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

VenueJournal of Motor Behavior · 2016
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStability (learning theory)WeightingGaitMargin (machine learning)MathematicsPhysical medicine and rehabilitationControl theory (sociology)Computer scienceArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

Changes to intersegmental locomotor control patterns may affect body stability. Our study aimed to (a) characterize upper body dynamic stability in response to the unilateral addition of mass to the lower extremity and (b) evaluate the efficacy of 2 different stability measures commonly used in the literature to detect resulting symmetrical step pattern modifications across the weighted segments (spatial) and between epochs of the gait cycle (temporal). Young adults walked on a treadmill while unloaded or with weights applied unilaterally to their foot, shank, or thigh. Both margin of stability and local dynamic stability (LDS) estimates detected similar trends of distal segment weighting resulting in more unstable upper body movement compared to proximal weighting; however only LDS detected anteroposterior changes in upper body stability over time.

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)0.005
metaresearch head score (Gemma)0.002
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 score0.549
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.055
GPT teacher head0.368
Teacher spread0.312 · 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