# The 'Problematic Paper Screener' automatically selects suspect publications for post-publication (re)assessment

arXiv: https://arxiv.org/abs/2210.04895 · HTML: https://mlsanity.com/paper/2210.04895/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Oct 2022.

## Built on by (most cited first, 4 of 4)

- [Pub-Guard-LLM: Detecting Retracted Biomedical Articles with Reliable Explanations](https://mlsanity.com/paper/2502.15429/) (2025)
- [Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review](https://mlsanity.com/paper/2510.14462/) (2025)
- [Semantic Reconstruction of Adversarial Plagiarism: A Context-Aware Framework for Detecting and Restoring "Tortured Phrases" in Scientific Literature](https://mlsanity.com/paper/2512.10435/) (2025)
- [CrossAudit: A Git-Native, Cross-Vendor Audit Loop for Agentic Science](https://mlsanity.com/paper/2608.28631/) (2026)

## Abstract (arXiv)

Post publication assessment remains necessary to check erroneous or fraudulent scientific publications. We present an online platform, the 'Problematic Paper Screener' (https://www.irit.fr/~Guillaume.Cabanac/problematic-paper-screener) that leverages both automatic machine detection and human assessment to identify and flag already published problematic articles. We provide a new effective tool to curate the scientific literature.