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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:

Observing the Observers: How Participants Contribute Data to iNaturalist and Implications for Biodiversity Science
Grace J. Di Cecco, Vijay Barve, Michael W. Belitz, et al.
BioScience (2021) Vol. 71, Iss. 11, pp. 1179-1188
Closed Access | Times Cited: 174

Showing 26-50 of 174 citing articles:

Experimental evidence that behavioral nudges in citizen science projects can improve biodiversity data
Corey T. Callaghan, Maureen M. Thompson, Adam Woods, et al.
BioScience (2023) Vol. 73, Iss. 4, pp. 302-313
Closed Access | Times Cited: 14
Weather anomalies more important than climate means in driving insect phenology
Robert Guralnick, Lindsay P. Campbell, Michael W. Belitz
Communications Biology (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 14
The Commons
Arun Agrawal, James T. Erbaugh, Nabin Pradhan
Annual Review of Environment and Resources (2023) Vol. 48, Iss. 1, pp. 531-558
Open Access | Times Cited: 13
Revealing biases in insect observations: A comparative analysis between academic and citizen science data
Joan Díaz‐Calafat, Sebastià Jaume-Ramis, Karen Soacha, et al.
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0305757-e0305757
Open Access | Times Cited: 5
Biodiversity data synthesis is critical for realizing a functional post-2020 framework
Michael C. Orr, Alice C. Hughes, Mark J. Costello, et al.
Biological Conservation (2022) Vol. 274, pp. 109735-109735
Closed Access | Times Cited: 20
Who, where, when: Observer behavior influences spatial and temporal patterns of iNaturalist participation
Monica Dimson, Thomas W. Gillespie
Applied Geography (2023) Vol. 153, pp. 102916-102916
Open Access | Times Cited: 12
Young people in iNaturalist: a blended learning framework for biodiversity monitoring
Christothea Herodotou, Nashwa Ismail, Ana Ilse Benavides-Lahnstein, et al.
International Journal of Science Education Part B (2023) Vol. 14, Iss. 2, pp. 129-156
Open Access | Times Cited: 12
Effects of climate on the distribution and conservation of commonly observed European earthworms
Romy Zeiss, María J.I. Briones, Jérôme Mathieu, et al.
Conservation Biology (2023) Vol. 38, Iss. 2
Open Access | Times Cited: 12
stemflow: A Python Package for Adaptive Spatio-Temporal Exploratory Model
Yangkang Chen, Zhongru Gu, Xiangjiang Zhan
The Journal of Open Source Software (2024) Vol. 9, Iss. 94, pp. 6158-6158
Open Access | Times Cited: 4
Assessing adequacy of citizen science datasets for biodiversity monitoring
Louis J. Backstrom, Corey T. Callaghan, Nicholas P. Leseberg, et al.
Ecology and Evolution (2024) Vol. 14, Iss. 2
Open Access | Times Cited: 4
The potential of iNaturalist for bee conservation research—A study case in a southern Brazilian metropolis
Felipe Walter Pereira, Maristela Zamoner, Rodrigo Barbosa Gonçalves
Insect Conservation and Diversity (2024) Vol. 17, Iss. 2, pp. 386-395
Closed Access | Times Cited: 4
Use of a mobile plant identification application and the out‐of‐school learning method in biodiversity education
Ozan Coşkunserçe
Ecology and Evolution (2024) Vol. 14, Iss. 4
Open Access | Times Cited: 4
The city nature challenge: A global citizen science phenomenon contributing to biodiversity knowledge and informing local government practices
Estíbaliz Palma, Luis Mata, Kylie Cohen, et al.
BioScience (2024) Vol. 74, Iss. 4, pp. 290-299
Open Access | Times Cited: 4
Estimating sampling biases in citizen science datasets
Louis J. Backstrom, Corey T. Callaghan, Hannah Worthington, et al.
Ibis (2024)
Open Access | Times Cited: 4
Decoding Wildlife Habitat Shifts in a Changing Environment Through Machine Learning
Vishal Shah
International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) Vol. 11, Iss. 1, pp. 176-184
Open Access
Crowdsourced Indicators of Flora and Fauna Species: Comparisons Between iNaturalist Records and Field Observations
Hyuksoo Kwon, Bumsuk Seo, Jungin Kim, et al.
Land (2025) Vol. 14, Iss. 1, pp. 169-169
Open Access
Deep sea spy: An online citizen science annotation platform for science and ocean literacy
Marjolaine Matabos, Pierre Cottais, Riwan Leroux, et al.
Ecological Informatics (2025), pp. 103065-103065
Open Access
Powerful flowers: Public perception of grassland aesthetics is strongly related to management and biodiversity
Valentin H. Klaus, Nathan Fox, Franziska Richter, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Closed Access
Evidence of novelty and specialization behavior in participatory science reporting
Benjamin R. Goldstein, Sara Stoudt
Oikos (2025)
Open Access
When do citizen scientists record biodiversity? Non‐random temporal patterns of recording effort and associated factors
Inês T. Rosário, Patrícia Tiago, Sérgio Chozas, et al.
People and Nature (2025)
Open Access
Expert identification blitz: A rapid high value approach for assessing and improving iNaturalist identification accuracy and data precision and confidence
Thomas Mesaglio, Kelly Anne Shepherd, Juliet Ann Wege, et al.
Plants People Planet (2025)
Open Access
Synthetic control methods enable stronger causal inference using participatory science data in cities
Asia Kaiser, Laura E. Dee, Julian Resasco
Research Square (Research Square) (2025)
Closed Access
Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring
Adrianne P. Smits, Ed K. Hall, Bridget R. Deemer, et al.
Ecosphere (2025) Vol. 16, Iss. 3
Open Access
iNaturalist as a platform for documenting Chilean funga
Cristian Riquelme
Lilloa (2025), pp. 61-88
Open Access
Using Citizen Science Data as Pre-Training for Semantic Segmentation of High-Resolution UAV Images for Natural Forests Post-Disturbance Assessment
Kamyar Nasiri, William Guimont-Martin, Damien LaRocque, et al.
Forests (2025) Vol. 16, Iss. 4, pp. 616-616
Open Access

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