AI can help scientists publish less

arXiv:2606.13829v1 Announce Type: cross Abstract: We can do more than defend science from a flood of AI-assisted papers. Used well, AI offers a historic opportunity

arXiv:2606.13738v1 Announce Type: new
Abstract: The emergence of biological complexity can be viewed as a transition from fragmented local interactions to extensive integrated organization, raising the question of how large-scale connectivity emerges from simple interacting elements. We investigated whether this transition can be understood as a consequence of hypergraph percolation driven by higher-order interactions. We performed computational simulations where elementary units constituted nodes and collective interactions formed hyperedges of variable size. Increasing hyperedge density enabled the characterization of connected-component growth, fragmentation, interaction overlap, participation and structural redundancy. Critical transition regions were identified as sparse local assemblies rapidly reorganized into extensive connected structures. These transitions were characterized by abrupt expansion of the largest connected component, progressive consolidation of previously disconnected clusters and increasing overlap among higher-order interactions. Connectivity growth was accompanied by the accumulation of alternative pathways and nested interaction patterns, pointing towards large-scale reorganization over a narrow range of interaction densities. Our findings suggest that, alongside the progressive evolution of molecular complexity, the origin of life and the emergence of biological organization may have involved rapid organizational transitions driven by higher-order connectivity and interaction architecture.

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