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Record W4406148460 · doi:10.1504/ijhfms.2024.143775

Use of JACK modelling software to quantify the reachability of ISO 6682

2024· article· en· W4406148460 on OpenAlexaff
Sara Perfetto, Katie Goggins, Melanie Cloutier, Alison Godwin

Bibliographic record

VenueInternational Journal of Human Factors Modelling and Simulation · 2024
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsLaurentian University
Fundersnot available
KeywordsReachabilitySoftwareComputer scienceReliability engineeringEngineeringAlgorithmProgramming language

Abstract

fetched live from OpenAlex

For decades, human factor experts have pushed for the redesign of mining machine cabs to improve operator sightlines and ergonomics. Current cab design does not accommodate a full range of operator sizes, causing many workers to adopt non-neutral postures, which can increase their risk for musculoskeletal injury. This work examined the reachability of the zone of comfort (ZoC) for hand control locations in JACK software as defined for a range of operators. Once reach envelopes were overlaid onto the cabs for a variety of sized operators, no condition existed where an operator could reach 100% of the ZoC for hand controls. The best reachability was achieved by the largest operator, while the 5th percentile Latino female can fully reach only 29.7% of controls without using flexion. This work is the first to examine the validity of ISO 6682 from an equity, diversity, and inclusion perspective.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.394
GPT teacher head0.503
Teacher spread0.108 · 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 designSimulation or modeling
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

Citations0
Published2024
Admission routes1
Has abstractyes

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