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 "consistency of interdisciplinarity measures"):
  Abstract: Assessing interdisciplinarity is an important and challenging work in bibliometric studies. Previous studies tend to emphasize that the nature and concept of interdisciplinary is ambiguous and uncertain (e.g. Leydesdorff & Rafols 2010, Rafols & Meyer, 2010, Sugimoto & Weingart, 2014). As a consequence, various different measures of interdisciplinarity have been proposed. However, few studies have examined the relations between these measures. In this context, this paper aims to systematically review these interdisciplinarity measures, and explore their inherent relations. We examine these measures in relation to the Web of Science (WoS) journal subject categories (SCs), and also an interdisciplinary research center at Aarhus University. In line with the conclusion of Digital Science (2016), our results reveal that the current situation of interdisciplinarity measurement in science studies is confusing and unsatisfying. We obtained surprisingly dissimilar results with measures that supposedly should measure similar features. We suggest that interdisciplinarity as a measurement construct should be used and interpreted with caution in future research evaluation and research policies.

Includes members:
  Member "how journal rankings can suppress interdisciplinary research a comparison between innovation studies and business management":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the differing meanings of indicators under different policy contexts the case of internationalisation")
  Member "indicators of the interdisciplinarity of journals diversity centrality and citations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "comparing the impact of subfields in scientific journals")

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)