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 "some modifications to the snip journal impact indicator"):
  Abstract: The SNIP (source normalized impact per paper) indicator is an indicator of the citation impact of scientific journals. The indicator, introduced by Henk Moed in 2010, is included in Elsevier's Scopus database. The SNIP indicator uses a source normalized approach to correct for differences in citation practices between scientific fields. The strength of this approach is that it does not require a field classification system in which the boundaries of fields are explicitly defined. In this paper, a number of modifications that will be made to the SNIP indicator are explained, and the advantages of the resulting revised SNIP indicator are pointed out. It is argued that the original SNIP indicator has some counterintuitive properties, and it is shown mathematically that the revised SNIP indicator does not have these properties. Empirically, the differences between the original SNIP indicator and the revised one turn out to be relatively small, although some systematic differences can be observed. Relations with other source normalized indicators proposed in the literature are discussed as well.

Includes members:
  Member "a further step forward in measuring journals scientific prestige the sjr2 indicator":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "prevalence of potentially predatory publishing in scopus on the country level")
  Member "source normalized indicators of citation impact an overview of different approaches and an empirical comparison":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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")
  Member "how can journal impact factors be normalized across fields of science an assessment in terms of percentile ranks and fractional counts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "field normalization of scientometric indicators")
  Member "the inconsistency of the h index":
    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 "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-5 (induced by source paper "field normalization of scientometric indicators")
  Member "towards a new crown indicator some theoretical considerations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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")
  Member "the relation between eigenfactor audience factor and influence weight":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "field normalization of scientometric indicators")
  Member "measuring contextual citation impact of scientific journals":
    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)