ArticleScientific reports2024
Development of machine learning models for forecasting the strength of resilient modulus of subgrade soil: genetic and artificial neural network approaches.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Multi-Objective Optimization and Prediction of Mechanical Properties of Green Basalt Fiber-Reinforced Concrete Using Evolutionary ML Algorithms.Materials (Basel, Switzerland) · 2026Article
- Strength and resilient performance of expansive subgrades stabilized with apricot kernel shell ash.Scientific reports · 2026Article
- Prediction of the Unconfined Compressive Strength of One-Part Geopolymer-Stabilized Soil Under Acidic Erosion: Comparison of Multiple Machine Learning Models.Materials (Basel, Switzerland) · 2026Article
- Predicting the strength of microsilica lime stabilized sulfate sand using hybrid machine learning models optimized with sparrow search algorithm.Scientific reports · 2025Article
- Identification of soil texture and color using machine learning algorithms and satellite imagery.Scientific reports · 2025Article
- Back analysis of mechanical parameters based on GPSO-BP neural network and its application.Scientific reports · 2025Article
- Estimation of Compressive Strength of Basalt Fiber-Reinforced Kaolin Clay Mixture Using Extreme Learning Machine.Materials (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurately predicting the Modulus of Resilience (M
Indexed as
Identifiers
What OpenQuestion holds
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.