The Scopus Radar Readiness Model for Mitigating Algorithmic Discontinuation Risks
DOI:
https://doi.org/10.17977/um065.v6.i3.2026.3Keywords:
Bibliometric anomalies, Editorial integrity, Paper mill detection, Publication ethics, Scopus radarAbstract
The integrity of the global academic record is under unprecedented threat due to the industrialization of scientific misconduct, driven by paper mills, citation cartels, and identity theft, prompting major bibliographic databases to replace manual curation with algorithmic systems. This study examines the operational mechanics of the Scopus Radar tool, an unsupervised anomaly detection system designed to identify and eliminate articles exhibiting anomalous behavior. We reconstruct the bibliometric indicators that lead to discontinuation by triangulating data from the November 2025 Scopus Discontinued Titles list, public Elsevier policy papers, and independent bibliometric research. Our study of 62 cancelled journals shows that Publication Concerns (59.7%) and Outlier conduct (14.5%) are the top grounds for removal. There are definite tendencies when it comes to hyper-concentrated authorship, quick volume velocity spikes, and citation stacking that does not make sense. We also see a "contagion effect," where certain publications have far greater rates of quitting than others. Based on these findings, we propose the Scopus Radar Readiness Model (SRRM). The model is based on the Core Practices of the Committee on Publication Ethics (COPE) and has four stages of growth. This roadmap gives editorial boards the tools they need to go from reactive compliance to proactive integrity assurance. They can do this by using internal bibliometric audits to find and fix problems before they lead to external algorithmic enforcement. The results show that journals need to use Level 4 Optimized integrity practices to stay alive in a time when automated gatekeeping is common.
References
Aries Systems. (2024). Combatting the paper mill phenomenon. https://www.ariessys.com/blog/combatting-the-paper-mill-phenomenon-connecting-editors-with-automated-fraud-detection/
arXiv. (2022). Analysis of publications by authors of Ukrainian institutes in Scopus-delisted titles. https://arxiv.org/pdf/2210.06798
arXiv. (2025). Semantic forensics for tortured phrases. https://arxiv.org/html/2512.10435v1
Baccini, A., Barabesi, L., Khelifa, R., & Petrovich, E. (2023). Geographic distribution of editorial boards. https://arxiv.org/html/2304.04242v2
BioRxiv. (2025). Machine learning model to distinguish between paper mill papers and genuine cancer research papers. https://www.biorxiv.org/content/10.1101/2025.08.29.673016v1.full.pdf
Cabanac, G., Labbé, C., & Magazinov, A. (2021). Investigating the detection of tortured phrases in scientific literature. https://www.researchgate.net/publication/353258515_Tortured_phrases_A_dubious_writing_style_emerging_in_science_Evidence_of_critical_issues_affecting_established_journals
Committee on Publication Ethics, & STM. (2022). Paper mills research. https://publicationethics.org/guidance/research-and-reports/paper-mills-research
Committee on Publication Ethics. (2019). Citation manipulation. https://publicationethics.org/guidance/discussion-document/citation-manipulation
Committee on Publication Ethics. (2024). Editors requiring authors to cite papers in their journal. https://publicationethics.org/guidance/cope-position/editors-requiring-authors-cite-papers-their-journal
Committee on Publication Ethics. (n.d.-a). COPE ethics toolkit for journal editors and publishers. https://members.publicationethics.org/sites/default/files/cope-ethics-toolkit-journal-editors-publishers.pdf
Committee on Publication Ethics. (n.d.-b). Paper mills. https://publicationethics.org/topic-discussions/paper-mills
Committee on Publication Ethics. (n.d.-c). Increasing number of fraudulent papers. https://publicationethics.org/press/increasing-number-fraudulent-papers-produced-paper-mills-press-release
Committee on Publication Ethics. (n.d.-d). COPE strategic plan. https://publicationethics.org/media/423/download?attachment
CSE Science Editor. (n.d.). The STM Integrity Hub. https://www.csescienceeditor.org/article/the-stm-integrity-hub/
DataRobot. (n.d.). Anomaly detection. https://docs.datarobot.com/en/docs/modeling/special-workflows/unsupervised/anomaly-detection.html
Davis, P. (2017). Reverse engineering JCR’s self-citation and citation stacking thresholds. The Scholarly Kitchen. https://scholarlykitchen.sspnet.org/2017/06/05/reverse-engineering-jcrs-self-citation-citation-stacking-thresholds/
Elsevier. (2020). Scopus content curation: Re-evaluation. https://www.researchgate.net/profile/Mohammed-Nasr-3/post/Journals_list_that_discontinued_from_Scopus-February_2020/attachment/5f1717475e3fff0001793d34/AS%3A915773425987585%401595348807720/download/Scopus+Content+Curation-+Re-evaluation.pdf
Elsevier. (n.d.-a). Title re-evaluation. https://www.elsevier.com/products/scopus/content/content-policy-and-selection
Elsevier. (n.d.-b). Scopus content policy and selection. https://www.elsevier.com/products/scopus/content/content-policy-and-selection
Elsevier. (n.d.-c). The importance of high-quality content curation and reevaluation in Scopus. https://assets.ctfassets.net/o78em1y1w4i4/4e0v9wh0vDmzyNnXTh0cCf/31eac680074c579a5c33fda620efa093/The-importance-of-high-quality-content-curation-and-reevaluation-in-Scopus.pdf
Elsevier. (n.d.-d). Fighting the problem of fraud in publishing. https://www.elsevier.com/en-au/connect/fighting-the-problem-of-fraud-in-publishing
Espin, J., Palmas, S., Carrasco-Rueda, F., Riemer, K., Allen, P. E., Berkebile, N., … Hecht, K. A. (2017). A persistent lack of international representation on editorial boards in environmental biology. PLOS Biology, 15(12), e2002760. https://pmc.ncbi.nlm.nih.gov/articles/PMC5726619/ DOI: https://doi.org/10.1371/journal.pbio.2002760
Futurity Publishing. (2025). Excluded journals from Scopus: October 2025. https://futurity-publishing.com/excluded-october2025/
Georgia Institute of Technology. (n.d.). Anomaly detection thresholds. https://faculty.cc.gatech.edu/~ada/papers/im11.pdf
Hanson, M. A., Barreiro, P. G., Crosetto, P., & Brockington, D. (2023). The strain on scientific publishing. https://arxiv.org/abs/2309.15884
Heneberg, P. (2016). From excessive journal self-cites to citation stacking. PLOS ONE, 11(4), e0153730. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0153730 DOI: https://doi.org/10.1371/journal.pone.0153730
Kojaku, S., Livan, G., & Masuda, N. (2021). Detecting anomalous citation groups in journal networks. Scientific Reports, 11, 15030. https://www.nature.com/articles/s41598-021-93572-3 DOI: https://doi.org/10.1038/s41598-021-93572-3
Macháček, V., & Srholec, M. (2022). Predatory publishing in Scopus: Evidence on cross-country differences. Scientometrics, 127(3), 1593–1621. https://direct.mit.edu/qss/article/3/3/859/113621 DOI: https://doi.org/10.1162/qss_a_00213
MDPI. (2024). Annual publication volume and business models of OA journals. Publications, 12(4), 46. https://www.mdpi.com/2304-6775/12/4/46 DOI: https://doi.org/10.3390/publications12040046
MIT Press. (2025). Using bibliometrics to detect questionable authorship. Quantitative Science Studies. https://direct.mit.edu/qss/article/doi/10.1162/qss_a_00339/125732
PeerJ. (2022). Developing a maturity model framework. PeerJ Computer Science. https://peerj.com/articles/cs-3183/
PLOS Biology. (2021). A survey of biomedical journals to detect editorial bias and nepotistic behavior. PLOS Biology, 19(11), e3001133. https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001133 DOI: https://doi.org/10.1371/journal.pbio.3001133
PLOS ONE. (2024). Journal self-citations in COVID-19 research. PLOS ONE, 19(7), e0314976. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0314976 DOI: https://doi.org/10.1371/journal.pone.0314976
PNAS. (2024). Coordinated production of fraudulent science. Proceedings of the National Academy of Sciences, 121(42). https://www.pnas.org/doi/10.1073/pnas.2420092122
Retraction Watch. (2025). Researcher identity verification framework. https://retractionwatch.com/2025/05/19/researcher-identity-verification-framework-stm-author-editor-reviewer/
STM. (n.d.). The STM Integrity Hub. https://www.stm-assoc.org/stm-integrity-hub/
Szomszor, M., Pendlebury, D. A., & Adams, J. (2020). How much is too much? The difference between research influence and self-citation excess. Scientometrics, 123(2), 1119–1147. DOI: https://doi.org/10.1007/s11192-020-03417-5
Taylor & Francis. (n.d.). Best practice guidelines for peer review. https://editorresources.taylorandfrancis.com/managing-peer-review-process/best-practice-guidelines-for-peer-review/
Wilches-Visbal, J. H., Pérez-Anaya, O., & Castillo-Pedraza, M. C. (2024). Discontinued reasons of journals in Scopus: Analysis and reflections. https://www.researchgate.net/publication/377727326
World Bank. (2024). Inequality indices to monitor geographic differences. https://documents1.worldbank.org/curated/en/099549506102441825/pdf/IDU-bd155bac-6d78-43af-8833-f87564a9d6c8.pdf
Wu, F., Zhang, H., & Ran, W. (2020). Does the institutional diversity of editorial boards increase journal quality? Scientometrics. https://www.researchgate.net/publication/341410819
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Eko Pramudya Laksana, Ikhwan Arief, Mochammad Tanzil Multazam, Busro Busro, Arif Zainudin, Akhmad Anwar Dani, Andista Candra Yusro, Dedi Rahman Nur, Utama Alan Deta, Much Fuad Saifuddin, Mohammad Fauziddin, Muhamad Ratodi, Asep Erlan Maulana, Muh. Firyal Akbar, Lucky Zamzami, Aldy Rialdy Atmadja
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
