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 "designing informative securities"):
  Abstract: We create a formal framework for the design of informative securities in prediction markets. These securities allow a market organizer to infer the likelihood of events of interest as well as if he knew all of the traders' private signals. We consider the design of markets that are always informative, markets that are informative for a particular signal structure of the participants, and informative markets constructed from a restricted selection of securities. We find that to achieve informativeness, it can be necessary to allow participants to express information that may not be directly of interest to the market organizer, and that understanding the participants' signal structure is important for designing informative prediction markets.

Includes members:
  Member "representing aggregate belief through the competitive equilibrium of a securities market":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "isoelastic agents and wealth updates in machine learning markets")
  Member "compact securities markets for pareto optimal reallocation of risk":
    also connected through other hyperedges:
      (none)
  Member "a collaborative mechanism for crowdsourcing prediction problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "smooth markets a basic mechanism for organizing gradient based learners")
  Member "a new understanding of prediction markets via no regret learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a decomposition of forecast error in prediction markets")
  Member "an optimization based framework for automated market making":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "arbitrage free combinatorial market making via integer programming")
  Member "complexity of combinatorial market makers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "how to calculate partition functions using convex programming hierarchies provable bounds for variational methods")

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.GT(Computer Science and Game Theory)