Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Ensemble learning-based applied research on heavy metals prediction in a soil-rice system
Huijuan Hao, Panpan Li, Wentao Jiao, et al.
The Science of The Total Environment (2023) Vol. 898, pp. 165456-165456
Closed Access | Times Cited: 16

Showing 16 citing articles:

Adapting machine learning for environmental spatial data - A review
Marta Jemeļjanova, Alexander Kmoch, Evelyn Uuemaa
Ecological Informatics (2024) Vol. 81, pp. 102634-102634
Open Access | Times Cited: 10
Prediction models for bioavailability of Cu and Zn during composting: Insights into machine learning
Bing Bai, Lixia Wang, Fachun Guan, et al.
Journal of Hazardous Materials (2024) Vol. 471, pp. 134392-134392
Closed Access | Times Cited: 9
Machine learning-driven source identification and ecological risk prediction of heavy metal pollution in cultivated soils
Zihan Bi, Jian Sun, Yutong Xie, et al.
Journal of Hazardous Materials (2024) Vol. 476, pp. 135109-135109
Closed Access | Times Cited: 6
Multiple pathway exposure risks and driving factors of heavy metals in soil-crop system in a Pb/Zn smelting city, China
Jianwei Liu, Shuo Qiao, Hui Chen, et al.
Journal of Cleaner Production (2024) Vol. 459, pp. 142523-142523
Closed Access | Times Cited: 5
Predicting Cd accumulation in crops and identifying nonlinear effects of multiple environmental factors based on machine learning models
Xiaosong Lu, Li Sun, Ya Zhang, et al.
The Science of The Total Environment (2024) Vol. 951, pp. 175787-175787
Closed Access | Times Cited: 5
Application of genetic programming in electrokinetic treatment of soil and COPR: Focus on Cr(VI) fractionation
Qiu Yu, Yi Zheng, Zhao Jiang, et al.
Journal of environmental chemical engineering (2025), pp. 115420-115420
Closed Access
Predicting cadmium enrichment in crops/vegetables and identifying the effects of soil factors based on transfer learning methods
Rui Chen, Zean Liu, Jingyan Yang, et al.
Ecotoxicology and Environmental Safety (2025) Vol. 291, pp. 117823-117823
Open Access
A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability
Renjie Zhang, Xionghui Ji, Yunhe Xie, et al.
Ecotoxicology and Environmental Safety (2025) Vol. 292, pp. 117926-117926
Open Access
Prediction and optimization of wastewater treatment process effluent chemical oxygen demand and energy consumption based on typical ensemble learning models
Jian Chen, Jinquan Wan, Gang Ye, et al.
Bioresource Technology (2024) Vol. 411, pp. 131362-131362
Closed Access | Times Cited: 3
Prediction of the impact of ecological restoration technology on the restoration of heavy metal pollution in agricultural soil
Yizhou Peng, Grigorieva Iya Yu
Geology Ecology and Landscapes (2024), pp. 1-17
Open Access | Times Cited: 2
Evaluating heavy metals-related risk in staple crops and making financing strategy for corresponding soil remediation across China
Baiqin Zhou, Fangjun Wang, Huiping Li, et al.
Journal of Hazardous Materials (2024) Vol. 480, pp. 136135-136135
Closed Access | Times Cited: 1
Screening of Practical Low-accumulating Crops in Cadmium-polluted Farmland: A Field Survey and Field Trail in Guangdong Province, China
Jianbin Deng, Zhaoxin Xu, Yuan Dai, et al.
Journal of Cleaner Production (2024), pp. 144508-144508
Closed Access | Times Cited: 1
Ensemble learning-assisted quantitative identifying influencing factors of cadmium and arsenic concentration in rice grain based multiplexed data
Yakun Wang, Zhuo Zhang, Cheng Cheng, et al.
Journal of Hazardous Materials (2024) Vol. 485, pp. 136869-136869
Closed Access | Times Cited: 1
Machine Learning Models for Predicting Bioavailability of Traditional and Emerging Aromatic Contaminants in Plant Roots
Siyuan Li, Yuting Shen, Meng Gao, et al.
Toxics (2024) Vol. 12, Iss. 10, pp. 737-737
Open Access
Machine learning models with innovative outlier detection techniques for predicting heavy metal contamination in soils
Ram Proshad, S Asha, Rong Kun Jason Tan, et al.
Journal of Hazardous Materials (2024) Vol. 481, pp. 136536-136536
Closed Access
Meta-Analysis of the Impacts of Applying Livestock and Poultry Manure on Cadmium Accumulation in Soil and Crops
Tao Tang, Hang ZHOU, Zhuo Yang, et al.
Agronomy (2024) Vol. 14, Iss. 12, pp. 2942-2942
Open Access
Page 1

Scroll to top