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Record W4387624544 · doi:10.2316/j.2023.201-0390

NOVEL CHAIR DESIGN TO MANAGE PRESSURE DISTRIBUTION, 1-10.

2023· article· en· W4387624544 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMechatronic systems and control · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicOperations Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsDistribution (mathematics)EngineeringComputer scienceMathematics

Abstract

fetched live from OpenAlex

Sitting pressure distribution is closely related to sitting comfort, health, and chair ergonomics.This study describes the development of a novel chair that can monitor and adjust seat pressure with the aim of relieving seat pressure.A mat device was developed to collect pressure distribution data from the seat surface.Electric extension/retraction mechanisms were designed from the base of the seat to redistribute seat pressure.Evaluations are presented for monitoring the pressure distributions of three different seat materials when a person was in four different postures, demonstrating that the performance of the pressure sensing mats was satisfactory.In an evaluation of the efficacy of the electric extenders' mechatronics features, the retraction function is viable for decreasing surface pressure.We expect that this study will contribute to novel chair design, and successful engineering development could contribute to the prevention of pressure ulcers by adjusting seat pressure for people in prolonged sitting positions.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.070
GPT teacher head0.331
Teacher spread0.261 · 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