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 "how should we score athletes and candidates geometric scoring rules"):
  Abstract: Individual rankings are often aggregated using scoring rules: each position in each ranking brings a certain score; the total sum of scores determines the aggregate ranking. We study whether scoring rules can be robust to adding or deleting particular candidates, as occurs with spoilers in political elections and with athletes in sports due to doping allegations. In general the result is negative, but weaker robustness criteria pin down a one-parameter family of geometric scoring rules with the scores $0, 1, 1+p, 1+p+p^2,\ldots$. These weaker criteria are independence from deleting unanimous winner (e.g., doping allegations) and independence from deleting unanimous loser (e.g., spoiler candidates). This family generalises three central rules: the Borda rule, the plurality rule and the antiplurality rule. For illustration we use recent events in biathlon; our results give simple instruments to design scoring rules for a wide range of applications.

Includes members:
  Member "measuring majority power and veto power of voting rules":
    also connected through other hyperedges:
      (none)
  Member "consistent approval based multi winner rules":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evaluating approval based multiwinner voting in terms of robustness to noise")
  Member "axiomatic characterization of committee scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "committee scoring rules axiomatic characterization and hierarchy")
  Member "multiwinner approval rules as apportionment methods":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "evaluating approval based multiwinner voting in terms of robustness to noise")

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)