human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "3d stochastic geometry model for large scale molecular communication systems"
  Abstract: Information delivery using chemical molecules is an integral part of biology at multiple distance scales and has attracted recent interest in bioengineering and communication. The collective signal strength at the receiver (i.e., the expected number of observed molecules inside the receiver), resulting from a large number of transmitters at random distances (e.g., due to mobility), can have a major impact on the reliability and efficiency of the molecular communication system. Modeling the collective signal from multiple diffusion sources can be computationally and analytically challenging. In this paper, we present the first tractable analytical model for the collective signal strength due to randomly-placed transmitters, whose positions are modelled as a homogeneous Poisson point process in three-dimensional (3D) space. By applying stochastic geometry, we derive analytical expressions for the expected number of observed molecules at a fully absorbing receiver and a passive receiver. Our results reveal that the collective signal strength at both types of receivers increases proportionally with increasing transmitter density. The proposed framework dramatically simplifies the analysis of large-scale molecular systems in both communication and biological applications.

Connected through hyperedge HE-1 (induced by source paper "chemical reactions based microfluidic transmitter and receiver for molecular communication"):
  with members:
    - "modeling duct flow for molecular communication"
    - "on the capacity of diffusion based molecular timing channels"
    - "modeling and simulation of molecular communication systems with a reversible adsorption receiver"
    - "molecular mimo from theory to prototype"
    - "a comprehensive survey of recent advancements in molecular communication"
    - "molecular communication with a reversible adsorption receiver"
    - "improving receiver performance of diffusive molecular communication with enzymes"
    - "tabletop molecular communication text messages through chemical signals"

Connected through hyperedge HE-2 (induced by source paper "analyzing large scale multiuser molecular communication via 3d stochastic geometry"):
  with members:
    - "reactive receiver modeling for diffusive molecular communication systems with molecule degradation"
    - "modeling and simulation of molecular communication systems with a reversible adsorption receiver"
    - "physical layer security in three tier wireless sensor networks a stochastic geometry approach"
    - "improving receiver performance of diffusive molecular communication with enzymes"
    - "a unifying model for external noise sources and isi in diffusive molecular communication"
    - "isi mitigation techniques in molecular communication"
    - "effect of degradation in molecular communication impairment or enhancement"
    - "using dimensional analysis to assess scalability and accuracy in molecular communication"

Connected through hyperedge HE-3 (induced by source paper "modeling and simulation of molecular communication systems with a reversible adsorption receiver"):
  with members:
    - "a comprehensive survey of recent advancements in molecular communication"
    - "joint channel parameter estimation via diffusive molecular communication"
    - "a markovian approach to the optimal demodulation of diffusion based molecular communication networks"
    - "molecular communication with a reversible adsorption receiver"
    - "optimal demodulation of reaction shift keying signals in diffusion based molecular communication networks"
    - "arrival modeling and error analysis for molecular communication via diffusion with drift"
    - "variance constrained capacity of the molecular timing channel with synchronization error"
    - "improving receiver performance of diffusive molecular communication with enzymes"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)