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: "on the macwilliams identity for convolutional codes"
  Abstract: The adjacency matrix associated with a convolutional code collects in a detailed manner information about the weight distribution of the code. A MacWilliams Identity Conjecture, stating that the adjacency matrix of a code fully determines the adjacency matrix of the dual code, will be formulated, and an explicit formula for the transformation will be stated. The formula involves the MacWilliams matrix known from complete weight enumerators of block codes. The conjecture will be proven for the class of convolutional codes where either the code itself or its dual does not have Forney indices bigger than one. For the general case the conjecture is backed up by many examples, and a weaker version will be established.

Connected through hyperedge HE-1 (induced by source paper "on the macwilliams identity for classical and quantum convolutional codes"):
  with members:
    - "correction of data and syndrome errors by stabilizer codes"
    - "normal factor graphs and holographic transformations"
    - "a macwilliams identity for convolutional codes the general case"
    - "on the weight distribution of convolutional codes"

Connected through hyperedge HE-2 (induced by source paper "macwilliams identities for terminated convolutional codes"):
  with members:
    - "a macwilliams identity for convolutional codes the general case"

Connected through hyperedge HE-3 (induced by source paper "on isometries for convolutional codes"):
  with members:
    - "a macwilliams identity for convolutional codes the general case"
    - "state space realizations and monomial equivalence for convolutional codes"
    - "on the weight distribution of convolutional codes"

Connected through hyperedge HE-4 (induced by source paper "codes on graphs duality and macwilliams identities"):
  with members:
    - "normal factor graphs and holographic transformations"
    - "macwilliams identities for terminated convolutional codes"
    - "a macwilliams identity for convolutional codes the general case"

Connected through hyperedge HE-5 (induced by source paper "macwilliams identities for codes on graphs"):
  with members:
    - "a macwilliams identity for convolutional codes the general case"

Connected through hyperedge HE-6 (induced by source paper "a macwilliams identity for convolutional codes the general case"):
  with members:
    - "on the weight distribution of convolutional codes"
    - "the dynamics of group codes dual abelian group codes and systems"

Connected through hyperedge HE-7 (induced by source paper "superregular matrices and the construction of convolutional codes having a maximum distance profile"):
  with members:
    - "on the weight distribution of convolutional codes"
    - "a class of one dimensional mds convolutional codes"

Connected through hyperedge HE-8 (induced by source paper "state space realizations and monomial equivalence for convolutional codes"):
  with members:
    - "on the weight distribution of convolutional codes"

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)