Initially, the team identified over 2 million addresses as potential Sybils but later refined their criteria to minimize false identifications, resulting in a more precise classification.

cointelegraph.com

Previous articleAxie Infinity Introduces Governance Portal and Axie Score System
Next articleThis Week in AI: OpenAI moves away from safety