CTGAN-Based Data Augmentation and XGBoost-LSTM Strength Prediction of CSG.

Guanghui Li, Yupeng Zhang, Qingqing Tian, Lei Guo, Qihui Chai

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Guanghui LiSchool of Water Conservancy, North China University of Water Resources and Electric Power (Longzihu Campus), Zhengzhou 450046, China.

Yupeng ZhangSchool of Water Conservancy, North China University of Water Resources and Electric Power (Longzihu Campus), Zhengzhou 450046, China.

Qingqing TianSchool of Water Conservancy, North China University of Water Resources and Electric Power (Longzihu Campus), Zhengzhou 450046, China.

Lei GuoSchool of Water Conservancy, North China University of Water Resources and Electric Power (Longzihu Campus), Zhengzhou 450046, China.

Qihui ChaiSchool of Water Conservancy, North China University of Water Resources and Electric Power (Longzihu Campus), Zhengzhou 450046, China.

Funding

the Key Technologies and Applications for Whole-Process Refined Regulation of Water Resources in Irrigation Districts Based on Digital Twin 251111210700the Mechanical Properties and Risk Early Warning Mechanism of Cemented Sand and Gravel Dam 252300420047the Science and Technology Innovation Leading Talent Support Program of Henan Province 254200510037

6 · The paper itself

Abstract

Cementitious sand and gravel (CSG) is commonly used in construction engineering; however, its mix proportion design is complex, and traditional physical experiments face limitations such as long cycles, high costs, and susceptibility to external factors when obtaining high-quality sample data. In this study, a foundational dataset was first acquired through physical experiments: 100 sets of CSG specimens with different mix proportions (cement content 40, 50, 60, 70 kg/m

Indexed as

CSGCTGANdata augmentationmodel performanceXGBoost–LSTM

Identifiers

PMID42513882

DOI10.3390/ma19143150

PMCPMC13413826

What OpenQuestion holds

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LicenceCC BY

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Registered trials

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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.