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 h index for research assessment simple and popular but shown by mathematical analysis to be inconsistent and misleading"):
  Abstract: Citation distributions are lognormal. We use 30 lognormally distributed synthetic series of numbers that simulate real series of citations to investigate the consistency of the h index. Using the lognormal cumulative distribution function, the equation that defines the h index can be formulated; this equation shows that h has a complex dependence on the number of papers (N). Specifically, after a certain limit, an increase of N has a very small effect on h, which contradicts a rational expectation. We also investigate the correlation between h and the number of papers exceeding various citation thresholds, from 5 to 500 citations. The best correlation, for 100 citations, is not linear, and numerous data points deviate from the general trend. The size-independent indicator h/N shows no correlation with the probability of publishing a paper exceeding any of the citation thresholds. In contrast with the h index, the total number of citations in the series shows a high linear correlation with the number of papers exceeding the thresholds of 10 and 50 citations. Dividing by N, the mean number of citations correlates with the probability of publishing a paper that exceeds any level of citations. The dependence is never linear, but for the thresholds of 20 and 30 citations, the deviation from linearity is low. Thus, in synthetic series, the number of citations and the mean number of citations are much better indicators of research performance than h and h/N. We discuss that this conclusion can be extended to real citation series.

Includes members:
  Member "like for like bibliometric substitutes for peer review advantages and limits of indicators calculated from the ep index":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "might europe one day again be a global scientific powerhouse analysis of erc publications suggests it will not be possible without changes in research policy")
  Member "research assessment by percentile based double rank analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "technological research in the eu is less efficient than the world average eu research policy risks europeans future")
  Member "not dead just resting the practical value of per publication citation indicators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "how do you define and measure research productivity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "the inconsistency of the h index":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "h α an index to quantify an individual s scientific leadership")

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)