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Record W4400729256 · doi:10.4103/hbc.hbc_1_23

The Fukuda stepping test is associated with various patterns of displacement

2024· article· en· W4400729256 on OpenAlexaff
Nicole Paquet, Lucas Michaud, Yves Lajoie

Bibliographic record

VenueHearing Balance and Communication · 2024
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTest (biology)Displacement (psychology)PsychologyPsychoanalysisGeology

Abstract

fetched live from OpenAlex

Abstract Objective: This study was to characterize individual path trajectories during the 50-step Fukuda stepping test (FST) and to determine the impact of step height on these trajectories. Methods: Kinematic data from the shoulders and feet were recorded in 12 young healthy adults while performing the FST at a comfortable step height (CoStep) and while stepping with lifting the knees high (HiStep). Path trajectories were depicted by step-by-step displacement of the right and left toes, and body rotation was obtained from the rotation of the shoulders. The effect of step height on the distance traveled and the final anteroposterior (AP) and mediolateral displacements and rotation were determined with paired t -tests. Results: Path trajectories were composed of various combinations of forward displacement, lateral deviation, and rotation to the left or right. In comparison with CoStep, the mean AP displacement and mean distance traveled were significantly shorter in HiStep ( P < 0.05) while the mean rotation was significantly larger in HiStep ( P < 0.05), but the displacement patterns were not modified. Conclusion: We found that the path trajectories vary greatly among participants, and that step height has a significant impact on the magnitude of displacements and rotation during the FST.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.143

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 head0.012
GPT teacher head0.233
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

Citations0
Published2024
Admission routes1
Has abstractyes

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