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Record W4296367628 · doi:10.23880/eoij-16000284

Case Studies on the Body Postures and Technical Design of Small Angle Grinders

2022· article· en· W4296367628 on OpenAlexaff
Kurt Landau

Bibliographic record

VenueErgonomics International Journal · 2022
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsSquatting positionKneelingBent molecular geometryTrunkWork (physics)PolishingEngineeringStructural engineeringMechanical engineeringOrthodonticsEngineering drawingPhysical therapyMedicine

Abstract

fetched live from OpenAlex

Our case studies refer to small angle grinders. Work tasks, physical stresses during use, and stresses on the hand-arm system are discussed. For this purpose, a survey was administered to 42 work persons from four different industries. Angle grinders were the most important hand tools for the respondents. They used angle grinders for eight activities (from flexing to polishing). In addition, 17 detailed video analyses of the work processes with 5 different angle grinder makes were carried out in selected workshops. The survey results on working postures in the last week as well as within the last year indicated mainly bent and twisted trunk postures, squatting and kneeling at work. To that extent, these results correspond with the OWAS studies by Ellegast R, et al. The video studies pointed out the very frequent twisted or bent hand-arm postures. The (ergonomically recommended) alignment of tool axis and hand-arm axis is not possible when using angle grinders. Nevertheless, the vast majority of our test subjects are satisfied with the dimensions and characteristics of small angle grinders. The analysis results are transferred into a list of ergonomic requirements for product designers.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.349

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 head0.051
GPT teacher head0.330
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations2
Published2022
Admission routes1
Has abstractyes

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