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Record W2228370306 · doi:10.4271/2003-28-0038

Applications of Digital Humans in Vehicle Design and Workplace design

2003· article· en· W2228370306 on OpenAlexaff
Éric Coutu

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2003
Typearticle
Languageen
FieldEngineering
TopicErgonomics and Human Factors
Canadian institutionsDassault Systèmes (Canada)
Fundersnot available
KeywordsComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">In today's world of “Reducing Time to Launch”, there is a strong requirement to model the physical elements of the human alongside the models of vehicles, workplaces and equipments, and study and validate the man machine interaction for validating ergonomics and comfort. This paper addresses this need, and explains the intricacies of Human modeling, ergonomic analyses, and applications of ergonomics. This paper details the need and current trends in ergonomic validation in a design environment, concurrently for vehicle ergonomics and manufacturing workplace ergonomics, in a completely digital form.</div>

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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 designObservational
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

Citations1
Published2003
Admission routes1
Has abstractyes

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