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 "individual research performance a proposal for comparing apples to oranges"):
  Abstract: The evaluation of performance at the individual level is of fundamental importance in informing management decisions. The literature provides various indicators and types of measures, however a problem that is still unresolved and little addressed is how to compare the performance of researchers working in different fields (apples to oranges). In this work we propose a solution, testing various scaling factors for the distributions of research productivity in 174 scientific fields. The analysis is based on the observation of scientific production by all Italian university researchers active in the hard sciences over the period 2004–2008, as indexed by the Web of Science. The most effective scaling factor is the average of the productivity distribution of researchers with productivity above zero.

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 "are the authors of highly cited articles also the most productive ones":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a simple centrality index for scientific social recognition")
  Member "revisiting the scaling of citations for research assessment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (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-5 (induced by source paper "a sensitivity analysis of researchers productivity rankings to the time of citation observation")
  Member "rescaling citations of publications in physics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching")

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)