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: "does quantity make a difference the importance of publishing many papers"
  Abstract: Do highly productive researchers have significantly higher probability to produce top cited papers? Or does the increased productivity in science only result in a sea of irrelevant papers as a perverse effect of competition and the increased use of indicators for research evaluation and accountability focus? We use a Swedish author disambiguated data set consisting of 48,000 researchers and their WoS-publications during the period of 2008 2011 with citations until 2014 to investigate the relation between productivity and production of highly cited papers. As the analysis shows, quantity does make a difference.

Connected through hyperedge HE-1 (induced by source paper "a comparison of university performance scores and ranks by mncs and fss"):
  with members:
    - "testing the trade off between productivity and quality in research activities"
    - "a farewell to the mncs and like size independent indicators"
    - "efficiency of research performance and the glass researcher"
    - "evaluating university research same performance indicator different rankings"
    - "ranking research institutions by the number of highly cited articles per scientist"
    - "how do you define and measure research productivity"
    - "measuring institutional research productivity for the life sciences the importance of accounting for the order of authors in the byline"
    - "assessing the accuracy of the h and g indexes for measuring researchers productivity"

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)