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 "the revised snip indicator of elsevier s scopus"):
  Abstract: The modified SNIP indicator of Elsevier, as recently explained by Waltman et al. (2013) in this journal, solves some of the problems which Leydesdorff & Opthof (2010 and 2011) indicated in relation to the original SNIP indicator (Moed, 2010 and 2011). The use of an arithmetic average, however, remains unfortunate in the case of scientometric distributions because these can be extremely skewed (Seglen, 1992 and 1997). The new indicator cannot (or hardly) be reproduced independently when used for evaluation purposes, and remains in this sense opaque from the perspective of evaluated units and scholars.

Includes members:
  Member "alternatives to the journal impact factor i3 and the top 10 or top 25 of the most highly cited papers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evaluating journal quality a review of journal citation indicators and ranking in business and management")
  Member "a further step forward in measuring journals scientific prestige the sjr2 indicator":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "prevalence of potentially predatory publishing in scopus on the country level")
  Member "the leiden ranking 2011 2012 data collection indicators and interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "some modifications to the snip journal impact indicator":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "prevalence of potentially predatory publishing in scopus on the country level")
  Member "testing differences statistically with the leiden ranking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the integrated impact indicator i3 revisited a non parametric alternative to the journal impact factor")
  Member "scopus s source normalized impact per paper snip versus a journal impact factor based on fractional counting of citations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "field normalization of scientometric indicators")
  Member "the danger of pseudo science in informetrics":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how to evaluate universities in terms of their relative citation impacts fractional counting of citations and the normalization of differences among disciplines")
  Member "caveats for the journal and field normalizations in the cwts leiden evaluations of research performance":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "how well does i3 perform for impact measurement compared to other bibliometric indicators the convergent validity of several field normalized indicators")

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)