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A deep research study introducing the Gene Drift Hypothesis: a framework explaining how tokenomics mutate across market cycles. Analyzes evolutionary forces, selective pressures, behavioral traits, and economic genes that rise, fall, or mutate through bull/bear phases, shaping token species over time.

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.

A research-grade exploration of the Tokenomics Ecological Framework, analyzing how tokens behave as predator, prey, parasite, and symbiotic species. Examines ecosystem interactions, evolutionary pressures, species population cycles, and the dynamics of economic predation, mutation, drift, and long-term survival across market cycles.

🧬 Explore the Gene Drift Hypothesis to understand how tokenomics evolve and adapt through market cycles and behavioral changes in on-chain assets.

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

🌱 Explore tokenomics through an ecological lens, analyzing predator-prey dynamics and interactions among token species for better understanding and strategy.