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 error detection in asymmetric channels"
  Abstract: We study the error detection problem in    $ {{q}} $   -ary asymmetric channels, wherein every input symbol    $ {{x}_{{i}}} $    is mapped to an output symbol    $ {{y}_{{i}}} $    satisfying    $ {{y}_{{i}} \geq {x}_{{i}}} $   . A general setting is assumed, where the noise vectors are (potentially) restricted in: 1) the amplitude,    $ {{y}_{{i}} - {x}_{{i }} \leq {a}} $   , 2) the Hamming weight,    $ {\sum _{i=1}^{n} {\mathsf {1}}_{\{y_{i} \neq x_{i}\}} \leq h} $   , and 3) the total weight,    $ {\sum _{i=1}^{n} (y_{i} - x_{i}) \leq t} $   . Optimal codes detecting these types of errors are described for certain sets of parameters    $ {{{a, h, t}}} $   , both in the standard and in the cyclic (   $ {\mathrm {mod}\, q} $   ) version of the problem. It is also demonstrated that these codes are optimal in the large alphabet limit for every    $ {{{a, h, t}}} $    and every block-length    $ {{n}} $   .

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)