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: "the spin off of elite universities in non competitive undifferentiated higher education systems an empirical simulation in italy"
  Abstract: Higher education systems featuring intense competition have developed world-class universities, capable of attracting top professors and students and considerable public–private funding. This does not occur in non-competitive systems, where highly talented faculty and students are dispersed across all institutions. In such systems, the authors propose the budding of spin-off universities, staffed by the migration of top scientists from the entire public research system. This article illustrates the proposal through an example: the spin-off of a new university in Rome, Italy staffed with the best professors from the three current public city universities. Such a faculty would offer top national research productivity, a magnet to attract the other critical ingredients of a world-class university: talented students, abundant resources and visionary governance.

Connected through hyperedge HE-1 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case"):
  with members:
    - "the impact of unproductive and top researchers on overall university research performance"
    - "revisiting the scientometric conceptualization of impact and its measurement"
    - "gender bias in academic recruitment"
    - "the determinants of academic career advancement evidence from italy"
    - "how do you define and measure research productivity"
    - "assessing national strengths and weaknesses in research fields"
    - "career advancement and scientific performance in universities"
    - "individual research performance a proposal for comparing apples to oranges"

Connected through hyperedge HE-2 (induced by source paper "an assessment of the first scientific habilitation for university appointments in italy"):
  with members:
    - "quantitative analysis of the italian national scientific qualification"
    - "the determinants of academic career advancement evidence from italy"
    - "career advancement and scientific performance in universities"
    - "the dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "the dangers of performance based research funding in non competitive higher education systems"

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)