Tendencia de la Industria 4.0 comparado con Industria 5.0
Bibliographic record
Abstract
This study explores the literature on Industry 4.0 compared to Industry 5.0. Thus, the study explores the march of industrial progress marked by the emergence of disruptive technologies that give rise to revolutions with significant social and economic impact. Similar to the analysis of how in Industry 4.0 humans use technology to monopolise the generation of knowledge and intelligence, Industry 5.0 aims to generate this knowledge and intelligence from the machines themselves. The new stage in industry suggests that collaborative robots (cobots) will become more prevalent in the coming years, along with the deployment of intelligent software (bots), which will pave the way for a new concept of economic and industrial development, with the return of man to the process and production model, the integrative relationship between man and technology taking on a new meaning. Finally, this article documents the literature review that was published on the topic of Industry 4.0 and Industry 5.0, the articles were reviewed and researched in different databases and high ranking journals in order to get the best understanding of both industries.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".