{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://froggit.ai/public/capsules/a4cf2dcf-45c3-4523-88e7-b0fc4bf5e821","identifier":"a4cf2dcf-45c3-4523-88e7-b0fc4bf5e821","url":"https://froggit.ai/public/capsules/a4cf2dcf-45c3-4523-88e7-b0fc4bf5e821","name":"Froggit: Scientific Retractions and Research Integrity Issues","text":"# Froggit: Scientific Retractions and Research Integrity Issues\n\n## 1. Scale of the retraction problem\n\n- Retraction is defined as a correction to scientific literature issued when there is a major flaw, fraud, or misuse of ethical practices in published work; with increasing growth of research output, the number of retracted studies has also increased, raising concerns about research ethics and transparency (https://arxiv.org/abs/2606.07554v1).\n- Systematic studies of retractions in computer science and other STEM fields remain scarce, according to the WithdrarXiv project, which presents what it describes as the first large-scale dataset of withdrawn papers from arXiv, containing over 14,000 papers and their associated records (https://arxiv.org/abs/2412.03775v1).\n\n## 2. Paper mills and AI-generated content\n\n- Scientific paper mills and AI-generated content are posing a growing threat to research integrity, while retractions reveal only a fraction of the problem, according to TalTech researcher Anton Sokolov (https://news.err.ee/1610155906/effect-of-research-paper-mills-enough-to-start-affecting-llm-query-results).\n- The same report frames the effect of research paper mills as sufficient to start affecting LLM query results (https://news.err.ee/1610155906/effect-of-research-paper-mills-enough-to-start-affecting-llm-query-results).\n\n## 3. Monitoring and early-warning approaches\n\n- RetraLytix is presented as an integrated analytics dashboard for mapping global trends in scientific retractions (https://arxiv.org/abs/2606.07554v1).\n- A study on social media as an early indicator of problematic research analysed 3,815 tweets referencing 604 retracted articles, alongside 3,373 tweets, using human annotation and large language models to identify critical tweets (https://arxiv.org/abs/2403.16851v3).\n- The study's stated motivation is that timely detection of problematic research is essential for safeguarding scientific integrity (https://arxiv.org/abs/2403.16851v3).\n\n## 4.","keywords":["trinity-research","sentinel_research","large-language-model","defi","education-research"],"about":[],"citation":["https://arxiv.org/abs/2606.07554v1","https://arxiv.org/abs/2412.03775v1","https://arxiv.org/abs/2403.16851v3","https://arxiv.org/abs/2404.15306v1","https://arxiv.org/abs/2308.04297v1","https://arxiv.org/abs/2309.16388v2","https://www.coursera.org/articles/what-is-a-major-in-college?msockid=08cfe37ea271674d3a3bf480a395666d","https://news.err.ee/1610155906/effect-of-research-paper-mills-enough-to-start-affecting-llm-query-results","https://www.coursera.org/articles/what-is-a-major-in-college"],"isPartOf":{"@type":"Dataset","name":"Froggit.ai Knowledge Graph","url":"https://froggit.ai"},"publisher":{"@type":"Organization","name":"Froggit.ai","url":"https://froggit.ai"},"dateCreated":"2026-10-26T17:16:22.113151Z","dateModified":"2026-10-26T17:16:22.113151Z","isBasedOn":"https://arxiv.org/abs/2606.07554v1","additionalProperty":[{"@type":"PropertyValue","name":"trust_level","value":100},{"@type":"PropertyValue","name":"verification_status","value":"sources_verified"},{"@type":"PropertyValue","name":"provenance_status","value":"valid"},{"@type":"PropertyValue","name":"evidence_level","value":"institutional"},{"@type":"PropertyValue","name":"content_hash","value":"bb2cdeee2638d4812da5918f5aded1f044f378932308bd90d349f73934a4d2e6"}]}