Where the technologies converge

Code extracts every tracked sub-cluster's real Bass-diffusion trajectory, along with the topic pairs our convergence detector has already found through citation overlap. Google Gemini proposes cross-cluster, cross-category scenarios and potential products from that real data. Code then verifies the source clusters cited, the evidence label, the horizon timing, and the adoption percentages shown, while Google Gemini supplies the qualitative rationale and the product ideas, neither of which is independently checked. A scenario marked detected has a real citation-overlap score between its parent topics. One marked inferred does not clear that bar, but it isn't ungrounded either: every inferred scenario shows the real semantic similarity between its closest source topics (the same statistical method behind detection, just below the threshold that would make it official), so Google Gemini's choice to combine these specific clusters can be checked against an actual number, not just its own say-so. Near, Mid, and Long-Term are fixed checkpoints (12, 30, and 60 months out) applied the same way to every cluster, not a horizon the data itself chose. Each cluster's percentage at that checkpoint, though, comes straight from its own fitted curve.

Research insights powered by Google Gemini

Built by Donald Butts