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 "testing for universality of mendeley readership distributions"):
  Abstract: Abstract   Altmetrics promise useful support for assessing the impact of scientific works, including beyond the scholarly community and with very limited citation windows. Unfortunately, altmetrics scores are currently available only for recent articles and cannot be used as covariates in predicting long term impact of publications. However, the study of their statistical properties is a subject of evident interest to scientometricians. Applying the same approaches used in the literature to assess the universality of citation distributions, the intention here is to test whether the universal distribution also holds for Mendeley readerships. Results of the analysis carried out on a sample of publications randomly extracted from the Web of Science confirm that readerships seem to share similar shapes across fields and can be rescaled to a common and universal form. Such rescaling results as not particularly effective on the right tails. In other regions, rescaling causes a good collapse of field specific distributions, even for very recent publications.

Includes members:
  Member "predicting publication long term impact through a combination of early citations and journal impact factor":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "revisiting the scientometric conceptualization of impact and its measurement":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "an investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "can the journal impact factor be used as a criterion for the selection of junior researchers a large scale empirical study based on researcherid data")
  Member "skewness of citation impact data and covariates of citation distributions a large scale empirical analysis based on web of science data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the heterogeneous distributions in paper citations")
  Member "scholarly use of social media and altmetrics a review of the literature":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "how well developed are altmetrics a cross disciplinary analysis of the presence of alternative metrics in scientific publications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "revisiting the scaling of citations for research assessment":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case")

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)