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: "fractional authorship in nuclear physics"
  Abstract: Large, multi-institutional groups or collaborations of scientists are engaged in nuclear physics research projects, and the number of research facilities is dwindling. These collaborations have their own authorship rules, and they produce a large number of highly-cited papers. Multiple authorship of nuclear physics publications creates a problem with the assessment of an individual author's productivity relative to his/her colleagues and renders ineffective a performance metrics solely based on annual publication and citation counts. Many institutions are increasingly relying on the total number of first-author papers; however, this approach becomes counterproductive for large research collaborations with an alphabetical order of authors. A concept of fractional authorship (the claiming of credit for authorship by more than one individual) helps to clarify this issue by providing a more complete picture of research activities. In the present work, nuclear physics fractional and total authorships have been investigated using nuclear data mining techniques. Historic total and fractional authorship averages have been extracted from the Nuclear Science References (NSR) database, and the current range of fractional contributions has been deduced. The results of this study and their implications are discussed and conclusions presented.

Connected through hyperedge HE-1 (induced by source paper "a categorization of arguments for counting methods for publication and citation indicators"):
  with members:
    - "a critical cluster analysis of 44 indicators of author level performance"
    - "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"
    - "a methodology to measure the effectiveness of academic recruitment and turnover"
    - "national disciplinary and temporal variations in the extent to which articles with more authors have more impact evidence from a geometric field normalised citation indicator"
    - "field normalized citation impact indicators and the choice of an appropriate counting method"
    - "a review of the literature on citation impact indicators"
    - "excellence networks in science a web based application based on bayesian multilevel logistic regression bmlr for the identification of institutions collaborating successfully"
    - "individual research performance a proposal for comparing apples to oranges"

Connected through hyperedge HE-2 (induced by source paper "first version of a categorization of arguments for counting methods for publication and citation indicators"):
  with members:
    - "a methodology to measure the effectiveness of academic recruitment and turnover"

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)