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: "variability of research performance across disciplines within universities in non competitive higher education systems"
  Abstract: Many nations are adopting higher education strategies that emphasize the development of elite universities able to compete at the international level in the attraction of skills and resources. Elite universities pursue excellence in all their disciplines and fields of action. The impression is that this does not occur in "non-competitive" education systems, and that instead, within single universities excellent disciplines will coexist with mediocre ones. To test this, the authors measure research productivity in the hard sciences for all Italian universities over the period 2004---2008 at the levels of the institution, their individual disciplines and fields within them. The results show that the distribution of excellent disciplines is not concentrated in a few universities: top universities show disciplines and fields that are often mediocre, while generally mediocre universities will often include top disciplines.

Connected through hyperedge HE-1 (induced by source paper "the ratio of top scientists to the academic staff as an indicator of the competitive strength of universities"):
  with members:
    - "measuring science irresistible temptations easy shortcuts and dangerous consequences"
    - "the impact of unproductive and top researchers on overall university research performance"
    - "from rankings to funnel plots the question of accounting for uncertainty when assessing university research performance"
    - "ranking research institutions by the number of highly cited articles per scientist"
    - "the determinants of academic career advancement evidence from italy"
    - "which of the world s institutions employ the most highly cited researchers an analysis of the data from highlycited com"
    - "how do you define and measure research productivity"
    - "career advancement and scientific performance in universities"

Connected through hyperedge HE-2 (induced by source paper "the combined effects of age and seniority on research performance of full professors"):
  with members:
    - "measuring science irresistible temptations easy shortcuts and dangerous consequences"
    - "variation in research collaboration patterns across academic ranks"
    - "career advancement and scientific performance in universities"
    - "individual research performance a proposal for comparing apples to oranges"
    - "what is the appropriate length of the publication period over which to assess research performance"
    - "how important is choice of the scaling factor in standardizing citations"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "research productivity are higher academic ranks more productive than lower ones"

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)