human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "technological research in the eu is less efficient than the world average eu research policy risks europeans future"):
  Abstract: We have studied the efficiency of research in the EU by a percentile-based citation approach that analyzes the distribution of country papers among the world papers. Going up in the citation scale, the frequency of papers from efficient countries increases while the frequency from inefficient countries decreases. In the percentile-based approach, this trend, which is permanent at any citation level, is measured by the ep index that equals the Ptop 1%/Ptop 10% ratio. By using the ep index we demonstrate that EU research on fast-evolving technological topics is less efficient than the world average and that the EU is far from being able to compete with the most advanced countries. The ep index also shows that the USA is well ahead of the EU in both fast- and slow-evolving technologies, which suggests that the advantage of the USA over the EU in innovation is due to low research efficiency in the EU. In accord with some previous studies, our results show that the European Commission's ongoing claims about the excellence of EU research are based on a wrong diagnosis. The EU must focus its research policy on the improvement of its inefficient research. Otherwise, the future of Europeans is at risk.

Includes members:
  Member "research assessment by percentile based double rank analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the h index for research assessment simple and popular but shown by mathematical analysis to be inconsistent and misleading")
  Member "the elephant in the room the problem of quantifying productivity in evaluative scientometrics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "research assessment by percentile based double rank analysis")
  Member "how do you define and measure research productivity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the h index for research assessment simple and popular but shown by mathematical analysis to be inconsistent and misleading")
  Member "the european union china and the united states in the top 1 and top 10 layers of most frequently cited publications competition and collaborations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the challenges ahead of spatial scientometrics focusing on the city level")
  Member "on the calculation of percentile based bibliometric indicators":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "the use of percentiles and percentile rank classes in the analysis of bibliometric data opportunities and limits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "the leiden ranking 2011 2012 data collection indicators and interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")

Question: Please tell me which class the source paper 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)