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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:

Using Geospatial Data and Random Forest To Predict PFAS Contamination in Fish Tissue in the Columbia River Basin, United States
Nicole M. DeLuca, Ashley Mullikin, Peter Brumm, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 37, pp. 14024-14035
Open Access | Times Cited: 11

Showing 11 citing articles:

PFAS in Nigeria: Identifying data gaps that hinder assessments of ecotoxicological and human health impacts
Kenneth N Kikanme, Nicole M Dennis, Ochuko Felix Orikpete, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e29922-e29922
Open Access | Times Cited: 12
Target and suspect per- and polyfluoroalkyl substances in fish from an AFFF-impacted waterway
Elena B. Nilsen, Derek J. Muensterman, Lya Carini, et al.
The Science of The Total Environment (2023) Vol. 906, pp. 167798-167798
Open Access | Times Cited: 14
Transforming PFAS management: A critical review of machine learning applications for enhanced monitoring and treatment
Md Hasan-Ur Rahman, Rabbi Sikder, Tanvir Ahamed Tonmoy, et al.
Journal of Water Process Engineering (2025) Vol. 70, pp. 106941-106941
Closed Access
Ecological risks of PFAS in China’s surface water: A machine learning approach
Xinmiao Huang, Huijuan Wang, Xiaoyong Song, et al.
Environment International (2025) Vol. 196, pp. 109290-109290
Open Access
Using machine learning to reveal drivers of soil microplastics and assess their stock: A national-scale study
Lin‐Jie Zhang, Feng Wang, Wenyue Wang, et al.
Journal of Hazardous Materials (2024) Vol. 478, pp. 135466-135466
Closed Access | Times Cited: 2
Application Of Machine Learning To Understand Pfas Occurrence, Distribution, Transport And Removal In Water
Adewale Ajao
(2024)
Open Access | Times Cited: 1
Statistical Mapping of PFOA and PFOS in Groundwater throughout the Contiguous United States
B.H. Park, Hyunseung Kang, Christopher Zahasky
Environmental Science & Technology (2024) Vol. 58, Iss. 44, pp. 19843-19850
Closed Access | Times Cited: 1
Distribution Characteristics and Driving Factors of Collichthys lucidus Species in Offshore Waters of Zhejiang Province, China
Wendan Xuan, Hongliang Zhang, Haobo Zhang, et al.
Fishes (2024) Vol. 9, Iss. 3, pp. 83-83
Open Access
Environmental public health research at the U.S. Environmental Protection Agency: A blueprint for exposure science in a connected world
Lindsay Wichers Stanek, Wayne E. Cascio, Timothy Barzyk, et al.
Journal of Exposure Science & Environmental Epidemiology (2024)
Open Access
Predicted Potential for Aquatic Exposure Effects of Per- and Polyfluorinated Alkyl Substances (PFAS) in Pennsylvania’s Statewide Network of Streams
Sara E. Breitmeyer, Andrew Williams, Matthew D. Conlon, et al.
Toxics (2024) Vol. 12, Iss. 12, pp. 921-921
Open Access
Optimizing the development of contaminated land in China: Exploring machine-learning to identify risk markers
Xiufeng Ni, Zeyuan Liu, Ji‐Zhong Wang, et al.
Journal of Hazardous Materials (2023) Vol. 465, pp. 133057-133057
Open Access | Times Cited: 1
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