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: "practical method to reclassify web of science articles into unique subject categories and broad disciplines"
  Abstract: Classification of bibliographic items into subjects and disciplines in large databases is essential for many quantitative science studies. The Web of Science classification of journals into approxi...

Connected through hyperedge HE-1 (induced by source paper "comparing the impact of subfields in scientific journals"):
  with members:
    - "recency predicts bursts in the evolution of author citations"
    - "patterns of authors contribution in scientific manuscripts"
    - "knowledge acquisition a complex networks approach"
    - "citation success index an intuitive pair wise journal comparison metric"
    - "concentric network symmetry grasps authors styles in word adjacency networks"
    - "a review of the literature on citation impact indicators"
    - "citations versus journal impact factor as proxy of quality could the latter ever be preferable"
    - "indicators of the interdisciplinarity of journals diversity centrality and citations"

Connected through hyperedge HE-2 (induced by source paper "china may need to support more small teams in scientific research"):
  with members:
    - "the preeminence of ethnic diversity in scientific collaboration"
    - "collaboration diversity and scientific impact"
    - "funding acknowledgment analysis queries and caveats"
    - "the relationship among research productivity research collaboration and their determinants"
    - "characterization description and considerations for the use of funding acknowledgement data in web of science"
    - "understanding the group dynamics and success of teams"
    - "field normalized citation impact indicators and the choice of an appropriate counting method"

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)