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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:

Explainable machine learning improves interpretability in the predictive modeling of biological stream conditions in the Chesapeake Bay Watershed, USA
Kelly O. Maloney, Claire Buchanan, Rikke D. Jepsen, et al.
Journal of Environmental Management (2022) Vol. 322, pp. 116068-116068
Open Access | Times Cited: 23

Showing 23 citing articles:

A framework for optimizing environmental covariates to support model interpretability in digital soil mapping
Babak Kasraei, Margaret G. Schmidt, Jin Zhang, et al.
Geoderma (2024) Vol. 445, pp. 116873-116873
Open Access | Times Cited: 15
Exploring sludge yield patterns through interpretable machine learning models in China's municipal wastewater treatment plants
Y. Hu, Renke Wei, Ke Yu, et al.
Resources Conservation and Recycling (2024) Vol. 204, pp. 107467-107467
Closed Access | Times Cited: 11
Comparing artificial and deep neural network models for prediction of coagulant amount and settled water turbidity: Lessons learned from big data in water treatment operations
Subin Lin, Jiwoong Kim, Chuanbo Hua, et al.
Journal of Water Process Engineering (2023) Vol. 54, pp. 103949-103949
Closed Access | Times Cited: 14
Enhancing prediction and inference of daily in-stream nutrient and sediment concentrations using an extreme gradient boosting based water quality estimation tool - XGBest
Shubham Jain, Arun Bawa, Katie Mendoza, et al.
The Science of The Total Environment (2025) Vol. 963, pp. 178517-178517
Open Access
Using tide for rainfall runoff simulation with feature projection and reversible instance normalization
Zheng Fang, Simin Qu, Xiaoqiang Yang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Stressor-driven changes in freshwater biological indicators inform spatial management strategies using expert knowledge, observational data, and hierarchical models
Sean C. Emmons, Matthew J. Cashman, Rosemary M. Fanelli, et al.
Ecological Indicators (2025) Vol. 174, pp. 113501-113501
Closed Access
Hydrological variability significantly influences aquatic biological integrity at the spatial scale in semi-arid watersheds
Lina Li, Rui Xia, Xinghui Xia, et al.
Journal of Hydrology (2025), pp. 133359-133359
Closed Access
Synergistic Effects of Environmental Factors on Benthic Diversity: Machine Learning Analysis
Yiyang Feng, Mengyu Yang, Hao Chen, et al.
Water Research (2025) Vol. 282, pp. 123789-123789
Closed Access
Interpretable machine learning for evaluating risk factors of freeway crash severity
Seyed Alireza Samerei, Kayvan Aghabayk
International Journal of Injury Control and Safety Promotion (2024) Vol. 31, Iss. 3, pp. 534-550
Closed Access | Times Cited: 3
Artificial Intelligence in Landscape Ecology: Recent Advances, Perspectives, and Opportunities
Amy E. Frazier, Lei Song
Current Landscape Ecology Reports (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 3
The nonlinear relationship between air quality and housing prices by machine learning
Weiwen Zhang, Sheng Pan, Zhiyuan Li, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 53, pp. 114375-114390
Closed Access | Times Cited: 7
Using Artificial Neural Networks to Predict Operational Parameters of a Drinking Water Treatment Plant (DWTP)
Stylianos Gyparakis, Ioannis Trichakis, Evan Diamadopoulos
Water (2024) Vol. 16, Iss. 19, pp. 2863-2863
Open Access | Times Cited: 2
Examining the Relationship Between Dwelling Energy Efficiency and Fuel Poverty for Retrofit Strategies: A Case Study of the United Kingdom
Minghao Liu, Zhonghua Gou
Energy (2024) Vol. 311, pp. 133457-133457
Closed Access | Times Cited: 2
Physical habitat is more than a sediment issue: A multi-dimensional habitat assessment indicates new approaches for river management
Matthew J. Cashman, G. F. Lee, Leah E Staub, et al.
Journal of Environmental Management (2024) Vol. 371, pp. 123139-123139
Open Access | Times Cited: 2
Observed and projected functional reorganization of riverine fish assemblages from global change
Taylor Woods, Mary C. Freeman, Kevin P. Krause, et al.
Global Change Biology (2023) Vol. 29, Iss. 13, pp. 3759-3780
Open Access | Times Cited: 6
Explainable artificial intelligence approach for yield strength prediction in as-cast multi-principal element alloys
Kyungtae Lee, Prasanna V. Balachandran
Materialia (2022) Vol. 26, pp. 101628-101628
Open Access | Times Cited: 7
The supporting role of Artificial Intelligence and Machine/Deep Learning in monitoring the marine environment: a bibliometric analysis
Fabiana Di Ciaccio
Ecological Questions (2024) Vol. 35, Iss. 1, pp. 1-30
Open Access | Times Cited: 1
Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions
John Thomas Delaney, Danelle M. Larson
Conservation Biology (2023) Vol. 38, Iss. 3
Open Access | Times Cited: 3
Ecological Modeling in Environmental Management: History and Applications
Arnab Banerjee, Brian D. Fath, Ursula M. Scharler, et al.
Elsevier eBooks (2023), pp. 6-22
Closed Access | Times Cited: 1
Rr-Tide: Are Transformers Effective for Runoff Prediction?
Zheng Fang, Simin Qu, Xiaoqiang Yang, et al.
(2024)
Closed Access
A novel coupling interpretable machine learning framework for water quality prediction and environmental effect understanding in different flow discharge regulations of hydro-projects
Xizhi Nong, Cheng Lai, Lihua Chen, et al.
The Science of The Total Environment (2024) Vol. 950, pp. 175281-175281
Closed Access
Predictive Modeling Reveals Elevated Conductivity Relative to Background Levels in Freshwater Tributaries within the Chesapeake Bay Watershed, USA
Rosemary M. Fanelli, Joel Moore, Charles C. Stillwell, et al.
ACS ES&T Water (2024) Vol. 4, Iss. 11, pp. 4978-4989
Open Access
The Watershed Health Assessment Framework: Integrating Geospatial Data and System Science to Advance Natural Resource Management in Minnesota
Beth J. Knudsen, Kevin P. Krause, Paul Radomski, et al.
˜The œhandbook of environmental chemistry (2024)
Closed Access
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