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Record W1987460976 · doi:10.1504/ijvd.2014.063829

Distributed occupant-seat interactions as an objective measure of seating comfort

2014· article· en· W1987460976 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Vehicle Design · 2014
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsConcordia University
Fundersnot available
KeywordsEngineeringAnalytic hierarchy processAutomotive industryMeasure (data warehouse)SimulationAutomotive engineeringComputer scienceOperations research

Abstract

fetched live from OpenAlex

An automotive seat must provide the occupant with a comfortable environment in which driving can be performed in a safe and comfortable manner. The characterisation of the interactions between the occupant and the seat under various conditions thus constitutes an important goal for enhancing the knowledge of essential design factors that could yield improved seating comfort. This paper investigates the occupant-seat interactions through measurements and analyses of the distributed contact force, contact area and peak and mean pressure responses at the body-seat-pan and body-backrest interfaces of three different automotive seats. User’s perceived comfort levels for various seating configurations were acquired through a survey and results were analysed through analytical hierarchy process (AHP) in order to derive a quantitative expression for the perceived comfort level. A strong correlation between perceived comfort and the peak and mean pressures on the seat-pan enabled us to derive an explicit formulation of seating comfort.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.029
GPT teacher head0.347
Teacher spread0.318 · 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