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 "eliciting expertise without verification"):
  Abstract: A central question of crowd-sourcing is how to elicit expertise from agents. This is even more difficult when answers cannot be directly verified. A key challenge is that sophisticated agents may strategically withhold effort or information when they believe their payoff will be based upon comparison with other agents whose reports will likely omit this information due to lack of effort or expertise. #R##N#Our work defines a natural model for this setting based on the assumption that \emph{more sophisticated agents know the beliefs of less sophisticated agents}. #R##N#We then provide a mechanism design framework for this setting. From this framework, we design several novel mechanisms, for both the single and multiple question settings, that (1) encourage agents to invest effort and provide their information honestly; (2) output a correct "hierarchy" of the information when agents are rational.

Includes members:
  Member "peer prediction with heterogeneous tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "impact of social learning on privacy preserving data collection")
  Member "putting peer prediction under the micro economic scope and making truth telling focal":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a technical survey on statistical modelling and design methods for crowdsourcing quality control")
  Member "learning to incentivize eliciting effort via output agreement":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "prior free data acquisition for accurate statistical estimation")
  Member "informed truthfulness in multi task peer prediction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "surrogate scoring rules")
  Member "equilibrium selection in information elicitation without verification via information monotonicity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "surrogate scoring rules")
  Member "sequential peer prediction learning to elicit effort using posted prices":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "prior free data acquisition for accurate statistical estimation")
  Member "crowdsourced judgement elicitation with endogenous proficiency":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "surrogate scoring rules")
  Member "mechanisms for making crowds truthful":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "report sensitive spot checking in peer grading systems")

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)