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 "assessing national strengths and weaknesses in research fields"):
  Abstract: National policies aimed at fostering the effectiveness of scientific systems should be based on reliable strategic analysis identifying strengths and weaknesses at field level. Approaches and indicators thus far proposed in the literature have not been completely satisfactory, since they fail to distinguish the effect of the size of production factors from that of their quality, particularly the quality of labor. The current work proposes an innovative “input-oriented” approach, which permits: (i) estimation of national research performance in a field and comparison to that of other nations, independent of the size of their respective research staffs; and, for fields of comparable intensity of publication, (ii) identification of the strong and weak research fields within a national research system on the basis of international comparison. In reference to the second objective, the proposed approach is applied to the Italian case, through the analysis of the 2006–2010 scientific production of the Italian academic system, in the 200 research fields where bibliometric analysis is meaningful.

Includes members:
  Member "measuring science irresistible temptations easy shortcuts and dangerous consequences":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the collaboration behavior of top scientists")
  Member "what is the effect of country specific characteristics on the research performance of scientific institutions using multi level statistical models to rank and map universities and research focused institutions worldwide":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching")
  Member "the collaboration behaviors of scientists in italy a field level analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "authorship analysis of specialized vs diversified research output")
  Member "what is the appropriate length of the publication period over which to assess research performance":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "mapping excellence in the geography of science an approach based on scopus data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the challenges ahead of spatial scientometrics focusing on the city level")
  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")

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)