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: "macwilliams identity for the rank metric"
  Abstract: This paper investigates the relationship between the rank weight distribution of a linear code and that of its dual code. The main result of this paper is that, similar to the MacWilliams identity for the Hamming metric, the rank weight distribution of any linear code can be expressed as an analytical expression of that of its dual code. Remarkably, our new identity has a similar form to the MacWilliams identity for the Hamming metric. Our new identity provides a significant analytical tool to the rank weight distribution analysis of linear codes. We use a linear space based approach in the proof for our new identity, and adapt this approach to provide an alternative proof of the MacWilliams identity for the Hamming metric. Finally, we determine the relationship between moments of the rank distribution of a linear code and those of its dual code, and provide an alternative derivation of the rank weight distribution of maximum rank distance codes.

Connected through hyperedge HE-1 (induced by source paper "rank distribution of delsarte codes"):
  with members:
    - "algebraic structures of mrd codes"
    - "relative generalized rank weight of linear codes and its applications to network coding"
    - "generalized weights an anticode approach"
    - "fourier reflexive partitions and macwilliams identities for additive codes"
    - "universal secure network coding via rank metric codes"
    - "on metrics for error correction in network coding"
    - "coding for errors and erasures in random network coding"
    - "macwilliams identity for codes with the rank metric"

Connected through hyperedge HE-2 (induced by source paper "rank metric codes and their duality theory"):
  with members:
    - "fourier reflexive partitions and macwilliams identities for additive codes"
    - "universal secure network coding via rank metric codes"
    - "on metrics for error correction in network coding"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"
    - "macwilliams identity for codes with the rank metric"

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)