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: "are the authors of highly cited articles also the most productive ones"
  Abstract: Ever more frequently, governments have decided to implement policy measures intended to foster and reward excellence in scientific research. This is in fact the intended purpose of national research assessment exercises. These are typically based on the analysis of the quality of the best research products; however, a different approach to analysis and intervention is based on the measure of productivity of the individual scientists, meaning the overall impact of their entire scientific production over the period under observation. This work analyzes the convergence of the two approaches, asking if and to what measure the most productive scientists achieve highly cited articles; or vice versa, what share of highly cited articles is achieved by scientists that are “non-top” for productivity. To do this we use bibliometric indicators, applied to the 2004–2008 publications authored by academics of Italian universities and indexed in the Web of Science.

Connected through hyperedge HE-1 (induced by source paper "a simple centrality index for scientific social recognition"):
  with members:
    - "the h index can be easily manipulated"
    - "lobby index as a network centrality measure"
    - "the inconsistency of the h index"

Connected through hyperedge HE-2 (induced by source paper "ranking research institutions by the number of highly cited articles per scientist"):
  with members:
    - "mapping excellence in national research systems the case of italy"
    - "a sensitivity analysis of researchers productivity rankings to the time of citation observation"
    - "how do you define and measure research productivity"
    - "inefficiency in selecting products for submission to national research assessment exercises"
    - "the importance of accounting for the number of co authors and their order when assessing research performance at the individual level in the life sciences"
    - "what is the appropriate length of the publication period over which to assess research performance"
    - "the leiden ranking 2011 2012 data collection indicators and interpretation"
    - "revisiting size effects in higher education research productivity"

Connected through hyperedge HE-3 (induced by source paper "highly cited papers in library and information science lis authors institutions and network structures"):
  with members:
    - "the generation of large networks from web of science data"
    - "which of the world s institutions employ the most highly cited researchers an analysis of the data from highlycited com"
    - "how are excellent highly cited papers defined in bibliometrics a quantitative analysis of the literature"
    - "information metrics imetrics a research specialty with a socio cognitive identity"
    - "the use of percentiles and percentile rank classes in the analysis of bibliometric data opportunities and limits"

Connected through hyperedge HE-4 (induced by source paper "individual research performance a proposal for comparing apples to oranges"):
  with members:
    - "measuring science irresistible temptations easy shortcuts and dangerous consequences"
    - "revisiting the scaling of citations for research assessment"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "national scale research performance assessment at the individual level"
    - "rescaling citations of publications in physics"

Connected through hyperedge HE-5 (induced by source paper "the importance of accounting for the number of co authors and their order when assessing research performance at the individual level in the life sciences"):
  with members:
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "national scale research performance assessment at the individual level"
    - "research productivity are higher academic ranks more productive than lower ones"
    - "caveats for the journal and field normalizations in the cwts leiden evaluations of research performance"

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)