A research-grade framework for forecasting tokenomic gene evolution across market cycles. Analyzes historical gene frequencies, models behavioral drift, and predicts future gene expression using interpretable trend and moving-average forecasting. Designed for tokenomics research, risk analysis, and evolutionary cryptoeconomics.

On-chain governance and incentive framework for open-source organizations with committee voting, token-holder proposals, project rewards, dual tokens, lockup, and dividends.

🔍 Analyze and forecast tokenomic gene frequencies across market cycles with this research-focused tool for effective market dynamics understanding.