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: "an evaluation of the australian research council s journal ranking"
  Abstract: As part of its program of ‘Excellence in Research for Australia’ (ERA), the Australian Research Council ranked journals into four categories (A*, A, B, and C) in preparation for their performance evaluation of Australian universities. The ranking is important because it likely to have a major impact on publication choices and research dissemination in Australia. The ranking is problematic because it is evident that some disciplines have been treated very differently than others. This paper reveals weaknesses in the ERA journal ranking and highlights the poor correlation between ERA rankings and other acknowledged metrics of journal standing. It highlights the need for a reasonable representation of journals ranked as A* in each scientific discipline.

Connected through hyperedge HE-1 (induced by source paper "assessing evaluation procedures for individual researchers the case of the italian national scientific qualification"):
  with members:
    - "quantitative analysis of the italian national scientific qualification"
    - "an assessment of the first scientific habilitation for university appointments in italy"
    - "betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks"

Connected through hyperedge HE-2 (induced by source paper "publication patterns of award winning forest scientists and implications for the australian era journal ranking"):
  with members:
    - "the relation between eigenfactor audience factor and influence weight"
    - "measuring contextual citation impact of scientific journals"
    - "a principal component analysis of 39 scientific impact measures"
    - "bias in the journal impact factor"
    - "ranking forestry journals using the h index"

Connected through hyperedge HE-3 (induced by source paper "metrics to evaluate research performance in academic institutions a critique of era 2010 as applied in forestry and the indirect h2 index as a possible alternative"):
  with members:
    - "evaluating research from informed peer review to bibliometrics"
    - "rescaling citations of publications in physics"
    - "allocative efficiency in public research funding can bibliometrics help"
    - "ranking forestry journals using the h index"

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)