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Record W4311550117 · doi:10.3390/vibration5040051

Seat-to-Head Transmissibility Responses of Seated Human Body Coupled with Visco-Elastic Seats

2022· article· en· W4311550117 on OpenAlexaff
K.N. Dewangan, Yumeng Yao, Subhash Rakheja

Bibliographic record

VenueVibration · 2022
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsConcordia University
FundersNational Natural Science Foundation of China
KeywordsTransmissibility (structural dynamics)SittingVibrationHead (geology)Resonance (particle physics)ExcitationWhole body vibrationCoupling (piping)Materials scienceStructural engineeringPhysicsAcousticsAtomic physicsMedicineComposite materialEngineeringGeologyVibration isolation

Abstract

fetched live from OpenAlex

This study investigated the seat-to-head vibration transmissibility (STHT) responses of 58 subjects (31 males and 27 females) seated on three different elastic seats with (WB) and without back support (NB) and under three levels of vertical vibration (0.25, 0.50 and 0.75 m/s2 RMS) in the 0.50–20 Hz range. The STHT responses with elastic seats were significantly different from the widely reported responses with rigid seats, irrespective of sitting and excitation conditions. The peak STHT magnitudes with elastic seats were relatively higher than those obtained with a rigid seat. Moreover, the transmission of seat vibration showed a strong dependence on the elastic properties of the body-seat coupling. The primary resonance frequencies were also significantly different among the elastic seats. Compared to NB conditions, the peak STHT magnitudes and the primary resonance frequencies obtained with WB conditions were significantly lower. An increase in excitation magnitude resulted in a statistically significant (p < 0.001) decrease in the primary resonance frequency.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.000

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 head0.028
GPT teacher head0.347
Teacher spread0.320 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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