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 state of the art ten years after a state of the art future research in music information retrieval"):
  Abstract: AbstractA decade has passed since the first review of research on a ‘flagship application’ of music information retrieval (MIR): the problem of music genre recognition (MGR). During this time, about 500 works addressing MGR have been published, and at least 10 campaigns have been run to evaluate MGR systems. This makes MGR one of the most researched areas of MIR. So, where does MGR now lie? We show that in spite of this massive amount of work, MGR does not lie far from where it began, and the paramount reason for this is that most evaluation in MGR lacks validity. We perform a case study of all published research using the most-used benchmark dataset in MGR during the past decade: GTZAN. We show that none of the evaluations in these many works is valid to produce conclusions with respect to recognizing genre, i.e. that a system is using criteria relevant for recognizing genre. In fact, the problems of validity in evaluation also affect research in music emotion recognition and autotagging. We conclude by ...

Includes members:
  Member "on evaluation validity in music autotagging":
    also connected through other hyperedges:
      (none)
  Member "deep scattering spectrum":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "one or two components the scattering transform answers")

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.SD(Sound)