KGX3 detects and classifies the epistemic function of research papers. It moves beyond keywords and citation metrics to provide a complete understanding of what a paper does: confirm, stress, or break a paradigm. This transforms the static scientific record into a dynamic, predictive map that can derisk high-stake decisions faster and better than any other intelligence source.
The core technology underpinning KGX3 has been validated over the past decade. It is deployed in many adjacent fields. Mass-scale knowledge-mining platforms like Brandwatch already sift through billions of unstructured social media posts to detect subtle shifts in public opinion. Real-time intelligence systems like Dataminr identify critical geopolitical and corporate events from global data streams moments after they occur. The Bloomberg Terminal transforms terabytes of global news, financial filings, and market data into a single, queryable universe of economic intelligence. What KGX3 does is equally accurate for research papers.
KGX3 applies this same class of proven signal-detection algorithms to scientific literature. By mapping research papers to a unique coordinate triplet—(M)method, (N)evidence, (P)position, KGX3 reveals their role in shaping what researchers think and believe. This allows our members to detect the latent structural tensions that precede a paradigm shift, offering them the ultimate strategic advantage: science intelligence.