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: "predicting results of the research excellence framework using departmental h index revisited"
  Abstract: We revisit our recent study [Predicting results of the Research Excellence Framework using departmental h-index, Scientometrics, 2014, 102:2165---2180; arXiv:1411.1996] in which we attempted to predict outcomes of the UK's Research Excellence Framework (REF 2014) using the so-called departmental h-index. Here we report that our predictions failed to anticipate with any accuracy either overall REF outcomes or movements of individual institutions in the rankings relative to their positions in the previous Research Assessment Exercise (RAE 2008).

Connected through hyperedge HE-1 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications"):
  with members:
    - "systematic analysis of agreement between metrics and peer review in the uk ref"
    - "predicting publication long term impact through a combination of early citations and journal impact factor"
    - "peer review and citation data in predicting university rankings a large scale analysis"
    - "do citations and readership identify seminal publications"
    - "revisiting the scientometric conceptualization of impact and its measurement"
    - "selecting competent referees to assess research projects proposals a study of referees registers"
    - "do they agree bibliometric evaluation versus informed peer review in the italian research assessment exercise"
    - "refrain from adopting the combination of citation and journal metrics to grade publications as used in the italian national research assessment exercise vqr 2011 2014"

Connected through hyperedge HE-2 (induced by source paper "systematic analysis of agreement between metrics and peer review in the uk ref"):
  with members:
    - "peer review and citation data in predicting university rankings a large scale analysis"
    - "predicting results of the research excellence framework using departmental h index"
    - "comparison of a citation based indicator and peer review for absolute and specific measures of research group excellence"
    - "a new methodology for constructing a publication level classification system of science"
    - "big macs and eigenfactor scores don t let correlation coefficients fool you"

Connected through hyperedge HE-3 (induced by source paper "bibliometric index for academic leadership"):
  with members:
    - "some variations on the standard theoretical models for the h index a comparative analysis"
    - "comparison of the h index for different fields of research using bootstrap methodology"
    - "the academic trace of the performance matrix a mathematical synthesis of the h index and the integrated impact indicator i3"
    - "socializing 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)