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Record W4411656672 · doi:10.51847/3gqtv2x4th

10.51847/3GqTv2x4th

2000· article· en· W4411656672 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEngineering
TopicErgonomics and Human Factors
Canadian institutionsnot available
Fundersnot available
KeywordsHuman factors and ergonomicsEngineeringPoison controlMedicineMedical emergency

Abstract

fetched live from OpenAlex

Ergonomics is always trying to create an effective, safe, and convenient workplace.Effective application of ergonomics in the design of the system can provide balance between jobs and characteristics of the employees.This can lead to labor force productivity, increased safety, physical and mental well-being, and job satisfaction of the employees.On the other hand, performance is doing works and tasks properly and rightly or spending the least amount of time or energy for the greatest work done.If an organization can achieve to certain goal with spending less resources compared with other organizations, it is said that it has higher performance.Increased productivity enhances efficiency and it helps in achieving organizational goals.Joyce Marilyn Joyce, President of the Institute in Seattle in USA believes that companies considering performance and quality control should employ ergonomics in their plans, as commercial intuition.Successful companies have integrated ergonomics plan with safety, quality control and production plans to maximize the performance.In this paper, we examine ergonomics and employee performance.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.9810.976

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 head0.004
GPT teacher head0.146
Teacher spread0.141 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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