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 "are the authors of highly cited articles also the most productive ones"):
  Abstract: Ever more frequently, governments have decided to implement policy measures intended to foster and reward excellence in scientific research. This is in fact the intended purpose of national research assessment exercises. These are typically based on the analysis of the quality of the best research products; however, a different approach to analysis and intervention is based on the measure of productivity of the individual scientists, meaning the overall impact of their entire scientific production over the period under observation. This work analyzes the convergence of the two approaches, asking if and to what measure the most productive scientists achieve highly cited articles; or vice versa, what share of highly cited articles is achieved by scientists that are “non-top” for productivity. To do this we use bibliometric indicators, applied to the 2004–2008 publications authored by academics of Italian universities and indexed in the Web of Science.

Includes members:
  Member "mapping excellence in national research systems the case of italy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a methodology to compute the territorial productivity of scientists the case of italy")
  Member "measuring science irresistible temptations easy shortcuts and dangerous consequences":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the collaboration behavior of top scientists")
  Member "individual research performance a proposal for comparing apples to oranges":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "the importance of accounting for the number of co authors and their order when assessing research performance at the individual level in the life sciences":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case")
  Member "revisiting the scaling of citations for research assessment":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case")
  Member "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "a field standardized application of dea to national scale research assessment of universities":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a sensitivity analysis of researchers productivity rankings to the time of citation observation")
  Member "the relationship between scientists research performance and the degree of internationalization of their research":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gender disparities in international research collaboration a large scale bibliometric study of 25 000 university professors")

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)