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 "the vqr italy s second national research assessment methodological failures and ranking distortions"):
  Abstract: The 2004–2010 VQR (Research Quality Evaluation), completed in July 2013, was Italy's second national research assessment exercise. The VQR performance evaluation followed a pattern also seen in other nations, as it was based on a selected subset of products. In this work, we identify the exercise's methodological weaknesses and measure the distortions that result from them in the university performance rankings. First, we create a scenario in which we assume the efficient selection of the products to be submitted by the universities and, from this, simulate a set of rankings applying the precise VQR rating criteria. Next, we compare these “VQR rankings” with those that would derive from the application of more-appropriate bibliometrics. Finally, we extend the comparison to university rankings based on the entire scientific production for the period, as indexed in the Web of Science.

Includes members:
  Member "how do you define and measure research productivity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the h index for research assessment simple and popular but shown by mathematical analysis to be inconsistent and misleading")
  Member "inefficiency in selecting products for submission to national research assessment exercises":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "when research assessment exercises leave room for opportunistic behavior by the subjects under evaluation")
  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-3 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case")
  Member "national peer review research assessment exercises for the hard sciences can be a complete waste of money the italian case":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  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 "the role of information asymmetry in the market for university industry research collaboration":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the north south divide in the italian higher education system")
  Member "national research assessment exercises a comparison of peer review and bibliometrics rankings":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")

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)