This paper is marked retracted in the scholarly record (OpenAlex). Interpret its findings with caution.
Retraction: Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data

Abstract
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsAnomaly Detection Techniques and Applications
The PLOS One Editors retract this article [1] due to concerns about authorship and potential manipulation of the publication process. We regret that the issues were not identified prior to the article’s publication.
All authors either did not respond directly or could not be reached.
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