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Record W3162664258 · doi:10.6084/m9.figshare.8288858

Standing centre of pressure alters the vibration transmissibility response of the foot

2019· dataset· en· W3162664258 on OpenAlexaff
Katie Goggins, Marco Tarabini, Brent Lievers, Tammy Eger

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsLaurentian University
Fundersnot available
KeywordsTransmissibility (structural dynamics)VibrationHeelFoot (prosody)Foot pressureStructural engineeringCentre of pressureAcousticsPhysical medicine and rehabilitationPosition (finance)MedicineEngineeringPhysicsVibration isolationPressure sensorMechanical engineering

Abstract

fetched live from OpenAlex

Vibration-white foot as an occupational disease has underscored the need to better understand the vibration response of the foot. While vibration transmissibility data exist for a natural standing position, it is anticipated that weight distribution will affect the response. The purpose of this study was to determine the effects of changes in centre of pressure (COP) on the foot’s biomechanical response. Twenty-one participants were exposed to vertical vibration of 30 mm/s, with a sine sweep from 10–200 Hz. <i>Z</i>-axis (vertical) vibration was measured at 24 locations on the right foot, with the COP shifted forward or toward the heel. A mixed model analysis at each location revealed significant differences (<i>p</i> <b>Practitioner Summary</b>: Altering the centre of pressure location resulted in changes in the transmission of vibration through the foot. The forward lean position was associated with the greatest amplitude of vibration transmissibility at the toes. This information is relevant for clinicians studying vibration-induced white-foot and engineers designing protective equipment.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.035
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
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)0.0360.000

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 head0.050
GPT teacher head0.334
Teacher spread0.284 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations2
Published2019
Admission routes1
Has abstractyes

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