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: "how coupled are mass spectrometry and capillary electrophoresis"
  Abstract: The understanding of how science works can contribute to making scientific development more effective. In this paper, we report an analysis of the organization and interconnection between two important issues in chemistry, namely mass spectrometry (MS) and capillary electrophoresis (CE). For that purpose, we employed science of science techniques based on complex networks. More specifically, we considered a citation network in which the nodes and connections represent papers and citations, respectively. Interesting results were found, including a good separation between some clusters of articles devoted to instrumentation techniques and applications. However, the papers that describe CE-MS did not lead to a well-defined cluster. In order to better understand the organization of the citation network, we considered a multi-scale analysis, in which we used the information regarding sub-clusters. Firstly, we analyzed the sub-cluster of the first article devoted to the coupling between CE and MS, which was found to be a good representation of its sub-cluster. The second analysis was about the sub-cluster of a seminal paper known to be the first that dealt with proteins by using CE-MS. By considering the proposed methodologies, our paper paves the way for researchers working with both techniques, since it elucidates the knowledge organization and can therefore lead to better literature reviews.

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.DL(Digital Libraries)