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 a response to scholtes et al on superlinear production in open source software"
  Abstract: On December 19, 2015, Scholtes et al.'s work was published online in the Journal of Empirical Software Engineering, in which they challenged the exciting findings that we (with another co-author) presented in 2014, showing that open source software production exhibits superlinear productive bursts. We presented our findings as the first quantification of Aristotle's famous adage: The whole is more than the sum of its parts. In contrast, Scholtes et al. 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. Since Ringelmann, the topic of collective intelligence has interested numbers of researchers in social sciences, as well as practitioners in management aiming at improving the performance of their team. And indeed, in most research and practice case studies, the Ringelmann effect has been found to hold. Our results challenge common wisdom, precisely because the Ringelmann effect has been replicated in countless experiments. We are glad that the study by Scholtes et al. allows us to explain further our findings by highlighting the methodological aspects that condition our diverging results. In particular, the definitions of group sizes and measurement periods are essential to explain the different conclusions. This healthy debate enriches the understanding on group productivity, in particular in the case of open source software production.

Connected through hyperedge HE-1 (induced by source paper "aristotle vs ringelmann on superlinear production in open source software"):
  with members:
    - "given enough eyeballs all bugs are shallow revisiting eric raymond with bug bounty programs"
    - "using prediction markets to incentivize and measure collective knowledge production"
    - "coase s penguin or linux and the nature of the firm"

Connected through hyperedge HE-2 (induced by source paper "collaboration drives individual productivity"):
  with members:
    - "predicting and explaining behavioral data with structured feature space decomposition"
    - "information overload in group communication from conversation to cacophony in the twitch chat"
    - "understanding the group dynamics and success of teams"

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)