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 accuracy of confidence intervals for field normalised indicators"):
  Abstract: When comparing the average citation impact of research groups, universities and countries, field normalisation reduces the influence of discipline and time. Confidence intervals for these indicators can help with attempts to infer whether differences between sets of publications are due to chance factors. Although both bootstrapping and formulae have been proposed for these, their accuracy is unknown. In response, this article uses simulated data to systematically compare the accuracy of confidence limits in the simplest possible case, a single field and year. The results suggest that the MNLCS (Mean Normalised Log-transformed Citation Score) confidence interval formula is conservative for large groups but almost always safe, whereas bootstrap MNLCS confidence intervals tend to be accurate but can be unsafe for smaller world or group sample sizes. In contrast, bootstrap MNCS (Mean Normalised Citation Score) confidence intervals can be very unsafe, although their accuracy increases with sample sizes.

Includes members:
  Member "use of the journal impact factor for assessing individual articles need not be wrong":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evaluating research and researchers by the journal impact factor is it better than coin flipping")
  Member "three practical field normalised alternative indicator formulae for research evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the demise of single authored publications in computer science a citation network analysis")
  Member "conceptual difficulties in the use of statistical inference in citation analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the research production of nations and departments a statistical model for the share of publications")
  Member "are the discretised lognormal and hooked power law distributions plausible for citation data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mendeley reader counts for us computer science conference papers and journal articles")
  Member "are there too many uncited articles zero inflated variants of the discretised lognormal and hooked power law distributions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "three practical field normalised alternative indicator formulae for research evaluation")
  Member "citation count distributions for large monodisciplinary journals":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "evaluating research and researchers by the journal impact factor is it better than coin flipping")
  Member "national research impact indicators from mendeley readers":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "readership data and research impact")
  Member "predicting the long term citation impact of recent publications":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")

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)