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OpenAlex Citation Counts

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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:

Unveiling Microbial Nitrogen Metabolism in Rivers using a Machine Learning Approach
Yuying Jia, Xiangang Hu, Weilu Kang, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 15, pp. 6605-6615
Closed Access | Times Cited: 19

Showing 19 citing articles:

Data-Driven Approach for Designing Eco-Friendly Heterocyclic Compounds for the Soil Microbiome
Bingfeng Chen, Meng Liu, Zhenyan Zhang, et al.
Environmental Science & Technology (2025)
Closed Access | Times Cited: 2
Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect
Yifei Qiu, Jingyu Niu, Chuchu Zhang, et al.
Water Research (2025) Vol. 274, pp. 123129-123129
Closed Access | Times Cited: 1
Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications
Luqi Wang, Dongsheng Liu, Yifan Sun, et al.
Ecotoxicology and Environmental Safety (2024) Vol. 283, pp. 116815-116815
Open Access | Times Cited: 7
Improved mapping of heavy metals in agricultural soils using machine learning augmented with spatial regionalization indices
Xudong Ma, Dong‐Xing Guan, ChaoSheng Zhang, et al.
Journal of Hazardous Materials (2024) Vol. 478, pp. 135407-135407
Closed Access | Times Cited: 4
Spatial Mapping and Prediction of Groundwater Quality Using Ensemble Learning Models and SHapley Additive exPlanations with Spatial Uncertainty Analysis
Shilong Yang, Danyuan Luo, Jiayao Tan, et al.
Water (2024) Vol. 16, Iss. 17, pp. 2375-2375
Open Access | Times Cited: 4
A Comprehensive OBD Data Analysis Framework: Identification and Factor Analysis of High-Emission Heavy-Duty Vehicles
Zeping Cao, Kai Shi, Hao Qin, et al.
Environmental Pollution (2025), pp. 125751-125751
Closed Access
Common issues of data science on the eco-environmental risks of emerging contaminants
Xiangang Hu, Dong Xu, Zhangjia Wang
Environment International (2025) Vol. 196, pp. 109301-109301
Open Access
Developing Physiologically Compatible Electron Donors for Reductive Dechlorination by Dissimilatory Iron-Reducing Bacteria Using Machine Learning
Yang Yu, Jiuling Li, Defeng Xing, et al.
ACS ES&T Engineering (2025)
Closed Access
Data-driven prediction of effluent quality in wastewater treatment processes: Model performance optimization and missing-data handling
Zhicheng Deng, Jinquan Wan, Gang Ye, et al.
Journal of Water Process Engineering (2025) Vol. 71, pp. 107352-107352
Closed Access
Picoplankton Groups and Their Responses to Environmental Factors in Small Cascade Hydropower Stations
Peiquan Li, Zhongxin Luo, Xianfang Zhu, et al.
Water (2025) Vol. 17, Iss. 6, pp. 903-903
Open Access
Sedimentary recorded nitrogen-transforming microbes reflect climate fluctuations in a glacial lake on the Qinghai-Tibetan Plateau over a millennium timescale
Jing Wang, Hanxiao Zhang, Shouliang Huo, et al.
Journal of Great Lakes Research (2025), pp. 102579-102579
Closed Access
Hydraulic and thermal performance trigger the deterministic assembly of water microbiomes: From biogeographical homogenization to ecological model
Guilin Wu, Haihan Zhang, Tinglin Huang, et al.
Water Research (2025), pp. 123626-123626
Closed Access
Supervised machine learning for understanding and predicting the status of bistable eukaryotic plankton community in urbanized rivers
Jiahui Shang, Yi Li, Wenlong Zhang, et al.
Water Research (2024) Vol. 266, pp. 122419-122419
Closed Access | Times Cited: 3
Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference
Pengfei Hou, Shiqi Liu, Duofei Hu, et al.
Bioresource Technology (2024) Vol. 414, pp. 131638-131638
Closed Access | Times Cited: 3
Water periods impact the structure and metabolic potential of the nitrogen-cycling microbial communities in rivers of arid and semi-arid regions
Qingqing Pang, Guohua Zhao, Dan Wang, et al.
Water Research (2024) Vol. 267, pp. 122472-122472
Closed Access | Times Cited: 2
Heavy metals in roadside soil along an expressway connecting two megacities in China: Accumulation characteristics, sources and influencing factors
Min Peng, Yang Zheng, Zijia Liu, et al.
The Science of The Total Environment (2024) Vol. 955, pp. 177095-177095
Closed Access | Times Cited: 1
Interpretable causal machine learning optimization tool for improving efficiency of internal carbon source-biological denitrification
Shiqi Liu, Zeqing Long, Jinsong Liang, et al.
Bioresource Technology (2024) Vol. 416, pp. 131787-131787
Closed Access | Times Cited: 1
Impact of low-dose free chlorine on the conjugative transfer of antibiotic resistance genes in wastewater effluents: Identifying key environmental factors for predictive modeling
Ye Xu, Wenchao Yu, Xiaowen Wang, et al.
Journal of Hazardous Materials (2024) Vol. 485, pp. 136824-136824
Closed Access
Microbial biomass stoichiometry and proportion of Fe organic complexes separately shape the heterogeneity of mixotrophic denitrification and net N2O sinks in iron-carbon amended ecological ditch
Bi–Ni Jiang, Yingying Zhang, Yan Wang, et al.
Water Research (2024) Vol. 272, pp. 122945-122945
Closed Access
Mitigating pesticide mixture hazard in global surface waters through agricultural management
Jian Chen, Li Zhao, Bin Wang, et al.
One Earth (2024), pp. 101163-101163
Closed Access
Targeted prevention strategy: Exploring the interaction effect of environmental and social factors on infectious diseases
Shuo Wang, Xinying Zhou, T. Zhang, et al.
The Science of The Total Environment (2024) Vol. 959, pp. 178218-178218
Closed Access
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