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: "assessing the accuracy of the h and g indexes for measuring researchers productivity"
  Abstract: Bibliometric indicators are increasingly used in support of decisions about recruitment, career advancement, rewards, and selective funding for scientists. Given the importance of the applications, bibliometricians are obligated to carry out empirical testing of the robustness of the indicators, in simulations of real contexts. In this work, we compare the results of national-scale research assessments at the individual level, based on the following three different indexes: the h-index, the g-index, and “fractional scientific strength” (FSS), an indicator previously proposed by the authors. For each index, we construct and compare rankings lists of all Italian academic researchers working in the hard sciences during the period 2001–2005. The analysis quantifies the shifts in ranks that occur when researchers' productivity rankings by simple indicators such as the h- or g-indexes are compared with those by more accurate FSS.

Connected through hyperedge HE-1 (induced by source paper "a comparison of university performance scores and ranks by mncs and fss"):
  with members:
    - "testing the trade off between productivity and quality in research activities"
    - "a farewell to the mncs and like size independent indicators"
    - "efficiency of research performance and the glass researcher"
    - "evaluating university research same performance indicator different rankings"
    - "does quantity make a difference the importance of publishing many papers"
    - "ranking research institutions by the number of highly cited articles per scientist"
    - "how do you define and measure research productivity"
    - "measuring institutional research productivity for the life sciences the importance of accounting for the order of authors in the byline"

Connected through hyperedge HE-2 (induced by source paper "a farewell to the mncs and like size independent indicators"):
  with members:
    - "more precise methods for national research citation impact comparisons"
    - "ranking research institutions by the number of highly cited articles per scientist"
    - "how do you define and measure research productivity"
    - "national scale research performance assessment at the individual level"
    - "cwts crown indicator measures citation impact of a research group s publication oeuvre"
    - "towards a new crown indicator some theoretical considerations"
    - "caveats for the journal and field normalizations in the cwts leiden evaluations of research performance"
    - "remaining problems with the new crown indicator mncs of the cwts"

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)