Review of sustainable concrete based on photocatalytic to reduce the environmental impact in large works in Peru
Bibliographic record
Abstract
This bibliographical review allows us to know clearly and concisely the use and effectiveness of photocatalytic concrete applied to tracks or roads, and in buildings. This study analyzes sustainable concrete based on photocatalytic to reduce the environmental impact in large-scale works through the application for the collection and review of articles published in the scientific base of Scopus using the VOSviewer software tool that analyzes a large amount of data from a group of investigations, this research is carried out from the publications of the year 2000 to the year 2022. Graphs were obtained from the database analysis with the words “Concrete”, “Photocatalytic”, “Environmental” and “Work” with the highest interest in all analysis groups. The results obtained allow us to understand the innovation of concrete based on photocatalytic in order to reduce air pollution since this need is current throughout the world, more so in globalized and rapidly growing countries, the analysis in Peru is not found no research related to the subject and there are no large-scale works related to reducing air pollution, but there are proposals to improve air quality in Lima, the capital of Peru, however this contribution is minimal to be able to positively impact the air . The manufacturing process and the materials to implement for the manufacture of concrete based on the photocatalytic were also analyzed, visualizing the advantages and disadvantages of this concrete based on the photocatalytic, adding other additional components to improve the durability of the concrete application and being viable. to apply to large-scale works. This research has the purpose of presenting a general view of the application, manufacture, advantages and disadvantages of concrete based on photocatalytic, it is important to develop and apply it in large-scale works subsidized by the Peruvian state, since these can generate a positive impact on society and the environment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".