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Record W3200268031 · doi:10.3390/vibration4040041

Effect of the Shoe Sole on the Vibration Transmitted from the Supporting Surface to the Feet

2021· article· en· W3200268031 on OpenAlexaff
Marco Tarabini, Tammy Eger, Katie Goggins, Alex P. Moorhead, Filippo Goi

Bibliographic record

VenueVibration · 2021
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsLaurentian University
FundersRegione Lombardia
KeywordsTransmissibility (structural dynamics)VibrationHeelFoot (prosody)Structural engineeringAcousticsEnvironmental scienceEngineeringVibration isolationPhysics

Abstract

fetched live from OpenAlex

Vibration transmitted through the foot can lead to vibration white feet, resulting in blanching of the toes and the disruption of blood circulation. Controlled studies identifying industrial boot characteristics effective at attenuating vibration exposure are lacking. This work focused on the evaluation of vibration transmissibility of boot midsole materials and insoles across the range 10–200 Hz at different foot locations. Questionnaires were used to evaluate the comfort of each material. The materials were less effective at attenuating vibration transmitted to the toe region of the foot than the heel. Between 10 and 20 Hz, all midsole materials reduced the average vibration transmitted to the foot. The average transmissibility at the toes above 100 Hz was larger than 1, evidencing that none of the tested material protects the worker from vibration-related risks. There was a poor correlation between the vibration transmissibility and the subjective evaluation of comfort. Future research is needed to identify materials effective for protecting both the toe and the heel regions of the foot. Specific standards for shoe testing are required as well.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0050.000

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 head0.014
GPT teacher head0.305
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2021
Admission routes1
Has abstractyes

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