ArticleHeliyon2024
Hybrid nonlinear regression model versus MARS, MEP, and ANN to evaluate the effect of the size and content of waste tire rubber on the compressive strength of concrete.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Experimental and machine learning evaluation of crumb rubber concrete strength at elevated temperatures.Scientific reports · 2026Article
- Interpretable machine learning approaches to assess the compressive strength of metakaolin blended sustainable cement mortar.Scientific reports · 2025Article
- Modeling the compressive strength behavior of concrete reinforced with basalt fiber.Scientific reports · 2025Article
- Advanced and hybrid machine learning techniques for predicting compressive strength in palm oil fuel ash-modified concrete with SHAP analysis.Scientific reports · 2025Article
- Predicting 28-day compressive strength of fibre-reinforced self-compacting concrete (FR-SCC) using MEP and GEP.Scientific reports · 2024Article
- Revolutionizing the construction industry by cutting edge artificial intelligence approaches: a review.Frontiers in artificial intelligence · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tire rubber waste is globally accumulated every year. Therefore, a solution to this problem should be found since, if landfilled, it is not biodegradable and causes environmental issues. One of the most effective ways is recycling those wastes or using them as a replacement for normal aggregate in the concrete mixture, which has high impact resistance and toughness; thus, it will be a good choice. In this study, 135 data were collected from previous literature to develop a model for the prediction of rubberized concrete compressive strength; the database comprised different mixture proportions, the maximum size of the rubber (1-40 mm), and the rubber percentage (0-100%) replacing natural fine and coarse aggregates were among the input parameters in addition to cement content (380-500 kg/m
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.