human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "national research assessment exercises the effects of changing the rules of the game during the game"):
  Abstract: National research evaluation exercises provide a comparative measure of research performance of the nation's institutions, and as such represent a tool for stimulating research productivity, particularly if the results are used to inform selective funding by government. While a school of thought welcomes frequent changes in evaluation criteria in order to prevent the subjects evaluated from adopting opportunistic behaviors, it is evident that the "rules of the game" should above all be functional towards policy objectives, and therefore be known with adequate forewarning prior to the evaluation period. Otherwise, the risk is that policy-makers will find themselves faced by a dilemma: should they reward universities that responded best to the criteria in effect at the outset of the observation period or those that result as best according to rules that emerged during or after the observation period? This study verifies if and to what extent some universities are penalized instead of rewarded for good behavior, in pursuit of the objectives of the "known" rules of the game, by comparing the research performances of Italian universities for the period of the nation's next evaluation exercise (2004---2008): first as measured according to criteria available at the outset of the period and next according to those announced at the end of the period.

Includes members:
  Member "the dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "national scale research performance assessment at the individual level":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a sensitivity analysis of researchers productivity rankings to the time of citation observation")
  Member "allocative efficiency in public research funding can bibliometrics help":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "diversification versus specialization in scientific research which strategy pays off")
  Member "the measurement of italian universities research productivity by a non parametric bibliometric methodology":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mapping excellence in national research systems the case of italy")

Question: Please tell me which class the source paper 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)