MétaCan
Menu
Back to cohort
Record W4388986214 · doi:10.22214/ijraset.2023.56941

Impact of Industry 4.0 on Occupational Safety and Health

2023· article· en· W4388986214 on OpenAlexfundno aff
Ms. Pallavi Singh

Bibliographic record

VenueInternational Journal for Research in Applied Science and Engineering Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsnot available
FundersMinistère de l'Économie, de la Science et de l'Innovation - Québec
KeywordsBusinessIndustrial RevolutionCompromiseOrder (exchange)Occupational safety and healthTechnological revolutionProduction (economics)Industry 4.0Risk analysis (engineering)EngineeringPolitical scienceEconomicsEconomyLaw

Abstract

fetched live from OpenAlex

Abstract: In recent years, the emergence of the "Fourth Industrial Revolution", commonly referred to as Industry 4.0, has been propelled by the global surge in consumer goods demand and the imperative for environmentally sustainable manufacturing practices. The fourth technological revolution, commonly referred to as Industry 4.0, is characterized by the heightened utilization of computers and robotics. The primary objective of this revolution is to enhance the caliber, efficacy, and versatility of industrial production. As a consequence of this prevailing inclination, there shall arise alterations in the manner by which tasks are structured and executed, potentially engendering an impact upon the overall welfare of employees. Should the technologies propelling the advent of Industry 4.0 continue to evolve in isolated compartments, with enterprises' operations remaining segregated and disjointed, the attendant hazards shall escalate, thereby culminating in an overall detrimental effect on Occupational Health and Safety (OHS). The potential compromise of the advancements achieved in the proactive administration of occupational health and safety may arise when substantial modifications are implemented. In order to avert the potential clash between technological advancement and occupational health and safety, it is imperative that a collaborative effort be undertaken by researchers, field specialists, and industry professionals. This collective endeavor aims to facilitate a seamless transition towards the era of Industry 4.0.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0310.003

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 head0.113
GPT teacher head0.445
Teacher spread0.332 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal for Research in Applied Science and Engineering TechnologySame topicDigital Transformation in IndustryFrench-language works237,207