human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "aristotle vs ringelmann on superlinear production in open source software"
  Abstract: Abstract   Organizations exist because they provide additional production gains, in comparison to horizontal ways of allocating resources, such as markets (Coase, 1937), and the open source movement is deemed to be a new kind of peer-production organization somehow in between hierarchically organized firms and markets (Benkler, 2002). However, to strive as a new kind of organization, open source must provide production gains, which in turn should be measurable. The open source movement is particularly interesting to study for this reason. Here, we confront and discuss two contrasting views, which were reported in the literature recently. On the one hand, Sornette et al. (2014) uncovered a superlinear production mechanism, which quantifies Aristotle adage: “the whole is more than the sum of its parts”. On the other hand, Scholtes et al. (2016) found opposite results, and referred to Maximilien Ringelmann, a French agricultural engineer (1861–1931), who discovered the tendency for individual members of a group to become increasingly less productive as the size of their group increases (Ringelmann, 1913). Since Ringelmann, the topic of collective intelligence has interested numbers of researchers in social sciences and social psychology (Woolley et al., 2010), as well as practitioners in management aiming at improving the performance of their team (Woolley et al., 2015). In most research and practice case studies, the Ringelmann effect has been found to hold, while, in contrast, the superlinear effect found by Sornette et al. is novel and may challenge common wisdom (Sornette et al., 2014). Here, we compare these two theories, weigh their strengths and weaknesses, and discuss how they have been tested with empirical data. We find that they may not contradict each other as much as was claimed by Scholtes et al. (2016).

Question: Please tell me which class the center node 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.SE(Software Engineering)