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: "world shares of publications of the usa eu 27 and china compared and predicted using the new interface of the web of science versus scopus"
  Abstract: The new interface of the Web of Science (of Thomson Reuters) enables users to retrieve sets larger than 100,000 documents in a single search. This makes it possible to compare publication trends for China, the USA, EU-27, and a number of smaller countries. China no longer grew exponentially during the 2000s, but linearly. Contrary to previous predictions on the basis of exponential growth or Scopus data, the cross-over of the lines for China and the USA is postponed to the next decade (after 2020) according to this data. These long extrapolations, however, should be used only as indicators and not as predictions. Along with the dynamics in the publication trends, one also has to take into account the dynamics of the databases used for the measurement.

Connected through hyperedge HE-1 (induced by source paper "the european union china and the united states in the top 1 and top 10 layers of most frequently cited publications competition and collaborations"):
  with members:
    - "how are excellent highly cited papers defined in bibliometrics a quantitative analysis of the literature"
    - "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers"
    - "how have the eastern european countries of the former warsaw pact developed since 1990 a bibliometric study"
    - "caveats for using statistical significance tests in research assessments"
    - "the use of percentiles and percentile rank classes in the analysis of bibliometric data opportunities and limits"
    - "the leiden ranking 2011 2012 data collection indicators and interpretation"
    - "publish or patent bibliometric evidence for empirical trade offs in national funding strategies"
    - "testing differences statistically with the leiden ranking"

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)