Can we truly trust every peer-reviewed study? In this episode, Nicole Kargin, founder of ResearchDoc AI and University of Austin student, discusses how AI can help evaluate the credibility of scientific research and address the global replication crisis.

Nicole’s work tackles the flaws in academic publishing, from misleading citation practices to systemic issues in peer review, creating what she describes as a “credit score” for research—helping scientists, policymakers, and the public identify studies that are methodologically sound and reproducible.

In this conversation, we explore:

• How ResearchDoc AI quantifies the quality and reliability of academic publications.
• Why citations and journal prestige can create a false sense of credibility.
• The limitations of traditional peer review and its role in the replication crisis.
• How AI and data-driven methods can improve research transparency and reproducibility.

If you’re curious about the future of science, research validation, and AI-powered quality assessment, this episode provides insight into building trust in the studies that shape our world.

Follow Nicole Kargin and ResearchDoc AI on LinkedIn, Twitter, and visit their website.

Episode also available on Apple Podcasts: https://apple.co/38oMlMr

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