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: "funding acknowledgment analysis queries and caveats"
  Abstract: Thomson Reuters's Web of Science WoS began systematically collecting acknowledgment information in August 2008. Since then, bibliometric analysis of funding acknowledgment FA has been growing and has aroused intense interest and attention from both academia and policy makers. Examining the distribution of FA by citation index database, by language, and by acknowledgment type, we noted coverage limitations and potential biases in each analysis. We argue that despite its great value, bibliometric analysis of FA should be used with caution.

Connected through hyperedge HE-1 (induced by source paper "china may need to support more small teams in scientific research"):
  with members:
    - "practical method to reclassify web of science articles into unique subject categories and broad disciplines"
    - "the preeminence of ethnic diversity in scientific collaboration"
    - "collaboration diversity and scientific impact"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "funding information in web of science an updated overview"):
  with members:
    - "solving multiple criteria r d project selection problems with a data driven evidential reasoning rule"
    - "missing author address information in web of science an explorative study"
    - "the sum of it all revealing collaboration patterns by combining authorship and acknowledgements"
    - "characterization description and considerations for the use of funding acknowledgement data in web of science"
    - "the journal coverage of web of science and scopus a comparative analysis"

Connected through hyperedge HE-3 (induced by source paper "missing author address information in web of science an explorative study"):
  with members:
    - "book reviews in academic journals patterns and dynamics"
    - "a spatial scientometric analysis of the publication output of cities worldwide"
    - "constructing bibliometric networks a comparison between full and fractional counting"
    - "a new methodology for constructing a publication level classification system of science"
    - "globalisation of science in kilometres"

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)