GAPRS: Mapping Scientific Knowledge with Claim Dependency Graphs
Introduction Most scientific papers are underread, peer review capacity is limited, and much innovation never reaches broad audiences. Current methods of scientific discovery are manual and slow. GAPRS transforms papers into interactive epistemic graphs where both humans and LLMs can reason over claims, assumptions, invalidators, and dependencies , accelerating discovery and surfacing hidden insights. Section 1: Core Idea At the heart of GAPRS is the concept of claims as nodes , with edges representing support, dependency, or extrapolation between them. Here’s an example using Attention Is All You Need (Vaswani et al., 2017): Claim Statement Confidence C1 Self-Attention achieves state-of-the-art performance on sequence modeling tasks High C2 Transformer architecture enables more efficient parallelization than RNNs High C3 Self-Attention allows modeling of long-range dependencies better than RNNs Medium C4 Positional encoding is sufficient to provide sequence order information Mediu...