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 "how can journal impact factors be normalized across fields of science an assessment in terms of percentile ranks and fractional counts"):
  Abstract: Using the CD-ROM version of the Science Citation Index 2010 (N = 3,705 journals), we study the (combined) effects of (i) fractional counting on the impact factor (IF) and (ii) transformation of the skewed citation distributions into a distribution of 100 percentiles and six percentile rank classes (top-1%, top-5%, etc.). Do these approaches lead to field-normalized impact measures for journals? In addition to the two-year IF (IF2), we consider the five-year IF (IF5), the respective numerators of these IFs, and the number of Total Cites, counted both as integers and fractionally. These various indicators are tested against the hypothesis that the classification of journals into 11 broad fields by PatentBoard/National Science Foundation provides statistically significant between-field effects. Using fractional counting the between-field variance is reduced by 91.7% in the case of IF5, and by 79.2% in the case of IF2. However, the differences in citation counts are not significantly affected by fractional counting. These results accord with previous studies, but the longer citation window of a fractionally counted IF5 can lead to significant improvement in the normalization across fields.

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 "accounting for the uncertainty in the evaluation of percentile ranks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how to improve the outcome of performance evaluations in terms of percentiles for citation frequencies of my papers")
  Member "impact factor outdated artefact or stepping stone to journal certification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a novel kuhnian ontology for epistemic classification of stm scholarly articles")
  Member "percentile ranks and the integrated impact indicator i3":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "fractional counting of citations in research evaluation a cross and interdisciplinary assessment of the tsinghua university in beijing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "comprehensive indicator comparisons intelligible to non experts the case of two snip versions")
  Member "universality of citation distributions revisited":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "testing for universality of mendeley readership distributions")
  Member "an evaluation of impacts in nanoscience nanotechnology steps towards standards for citation analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how important is choice of the scaling factor in standardizing citations")
  Member "how journal rankings can suppress interdisciplinary research a comparison between innovation studies and business management":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the differing meanings of indicators under different policy contexts the case of internationalisation")

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)