Trinka AI adds New Checks to its Highly Used Citation Quality Report that Strengthens Research Integrity
Mumbai, India, February 18, 2026
Trinka AI, the trusted academic writing and integrity platform, announced the launch of two new checks - citations from potential predatory journals and identification of duplicate reference entries - under its Citation Quality Report. The update also introduces a newly structured tiered risk reporting system that categorizes citation issues from High Risk to No Risk.
Citations are more than formatting elements. They reflect the rigor and credibility of a manuscript. Even experienced researchers may inadvertently cite questionable journals or include duplicate references when consolidating drafts, which can negatively impact peer review outcomes or lead to desk rejections. Trinka’s latest enhancement expands citation screening to include deeper citation integrity checks.
The new capability includes two major additions:
Predatory Journal Detection: Flags citations from journals associated with predatory publishing practices, helping authors avoid referencing sources that may undermine their work’s credibility.
Duplicate Reference Detection: Automatically identifies repeated reference entries, enabling users to maintain a clean and professional reference list.
To further streamline the review process, the updated citation engine introduces a risk tiering model that groups issues based on severity:
- High Risk: Retracted or unverified sources
- Medium Risk: Predatory journal citations and duplicate references
- Low Risk: Older citations or with a journal bias
- No Risk: Clean, good-to-go references
This prioritization framework enables authors and institutions to address the most critical citation concerns first, improving manuscript readiness before submission.
With this launch, Trinka continues to help researchers strengthen both the clarity and credibility of their work.
To learn more, visit https://www.trinka.ai/features/citation-checker or contact connect@trinka.ai.