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 "incentives for truthful evaluations"):
  Abstract: We consider crowdsourcing problems where the users are asked to provide evaluations for items; the user evaluations are then used directly, or aggregated into a consensus value. Lacking an incentive scheme, users have no motive in making effort in completing the evaluations, providing inaccurate answers instead. We propose incentive schemes that are truthful and cheap: truthful as the optimal user behavior consists in providing accurate evaluations, and cheap because the truthfulness is achieved with little overhead cost. We consider both discrete evaluation tasks, where an evaluation can be done either correctly, or incorrectly, with no degrees of approximation in between, and quantitative evaluation tasks, where evaluations are real numbers, and the error is measured as distance from the correct value. For both types of tasks, we propose hierarchical incentive schemes that can be effected with a small amount of additional evaluations, and that scale to arbitrarily large crowd sizes: they have the property that the strength of the incentive does not weaken with increasing hierarchy depth. Interestingly, we show that for these schemes to work, the only requisite is that workers know their place in the hierarchy in advance.

Includes members:
  Member "incentivizing evaluation via limited access to ground truth peer prediction makes things worse":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "credible sample elicitation")
  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 "truth serums for massively crowdsourced evaluation tasks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dominantly truthful multi task peer prediction with a constant number of tasks")
  Member "the peerrank method for peer assessment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "online fair division a survey")
  Member "methods for ordinal peer grading":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast and robust rank aggregation against model misspecification")
  Member "tuned models of peer assessment in moocs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "key phrase classification in complex assignments")
  Member "inducing honest reporting without observing outcomes an application to the peer review process":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "incentives for truthful peer grading")
  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)