human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "citation success index an intuitive pair wise journal comparison metric"
  Abstract: In this paper we present "citation success index", a metric for comparing the citation capacity of pairs of journals. Citation success index is the probability that a random paper in one journal has more citations than a random paper in another journal (50% means the two journals do equally well). Unlike the journal impact factor (IF), the citation success index depends on the broadness and the shape of citation distributions. Also, it is insensitive to sporadic highly-cited papers that skew the IF. Nevertheless, we show, based on 16,000 journals containing ~2.4 million articles, that the citation success index is a relatively tight function of the ratio of IFs of journals being compared, due to the fact that journals with same IF have quite similar citation distributions. The citation success index grows slowly as a function of IF ratio. It is substantial (>90%) only when the ratio of IFs exceeds ~6, whereas a factor of two difference in IF values translates into a modest advantage for the journal with higher IF (index of ~70%). We facilitate the wider adoption of this metric by providing an online calculator that takes as input parameters only the IFs of the pair of journals.

Connected through hyperedge HE-1 (induced by source paper "comparing the impact of subfields in scientific journals"):
  with members:
    - "practical method to reclassify web of science articles into unique subject categories and broad disciplines"
    - "recency predicts bursts in the evolution of author citations"
    - "patterns of authors contribution in scientific manuscripts"
    - "knowledge acquisition a complex networks approach"
    - "concentric network symmetry grasps authors styles in word adjacency networks"
    - "a review of the literature on citation impact indicators"
    - "citations versus journal impact factor as proxy of quality could the latter ever be preferable"
    - "indicators of the interdisciplinarity of journals diversity centrality and citations"

Connected through hyperedge HE-2 (induced by source paper "impact factor volatility to a single paper a comprehensive analysis"):
  with members:
    - "how a single paper affects the impact factor implications for scholarly publishing"
    - "the use of percentiles and percentile rank classes in the analysis of bibliometric data opportunities and limits"
    - "towards a new crown indicator an empirical analysis"

Connected through hyperedge HE-3 (induced by source paper "evaluating research and researchers by the journal impact factor is it better than coin flipping"):
  with members:
    - "systematic analysis of agreement between metrics and peer review in the uk ref"
    - "probability and expected frequency of breakthroughs a robust method of research assessment based on the double rank property of citation distributions"
    - "core elements in the process of citing publications conceptual overview of the literature"
    - "use of the journal impact factor for assessing individual articles need not be wrong"
    - "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"
    - "citation count distributions for large monodisciplinary journals"
    - "citations indicators of quality the impact fallacy"
    - "a review of the literature on citation impact indicators"

Question: Please tell me which class the center node 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)