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: "oceanic games centralization risks and incentives in blockchain mining"
  Abstract: To participate in the distributed consensus of permissionless blockchains, prospective nodes -- or miners -- provide proof of designated, costly resources. However, in contrast to the intended decentralization, current data on blockchain mining unveils increased concentration of these resources in a few major entities, typically mining pools. To study strategic considerations in this setting, we employ the concept of Oceanic Games, Milnor and Shapley (1978). Oceanic Games have been used to analyze decision making in corporate settings with small numbers of dominant players (shareholders) and large numbers of individually insignificant players, the ocean. Unlike standard equilibrium models, they focus on measuring the value (or power) per entity and per unit of resource} in a given distribution of resources. These values are viewed as strategic components in coalition formations, mergers and resource acquisitions. Considering such issues relevant to blockchain governance and long-term sustainability, we adapt oceanic games to blockchain mining and illustrate the defined concepts via examples. The application of existing results reveals incentives for individual miners to merge in order to increase the value of their resources. This offers an alternative perspective to the observed centralization and concentration of mining power. Beyond numerical simulations, we use the model to identify issues relevant to the design of future cryptocurrencies and formulate prospective research questions.

Connected through hyperedge HE-1 (induced by source paper "double spend counterattacks threat of retaliation in proof of work systems"):
  with members:
    - "mind the mining"
    - "bitcoin a natural oligopoly"
    - "optimal selfish mining strategies in bitcoin"
    - "analysis of hashrate based double spending"
    - "majority is not enough bitcoin mining is vulnerable"

Connected through hyperedge HE-2 (induced by source paper "presto a systematic framework for blockchain consensus protocols"):
  with members:
    - "weighted voting on the blockchain improving consensus in proof of stake protocols"
    - "blockchain trilemma solver algorand has dilemma over undecidable messages"
    - "blockchain technologies for the internet of things research issues and challenges"
    - "strongchain transparent and collaborative proof of work consensus"
    - "a survey on consensus mechanisms and mining strategy management in blockchain networks"
    - "sok tools for game theoretic models of security for cryptocurrencies"
    - "incentives in ethereum s hybrid casper protocol"
    - "scilla a smart contract intermediate level language"

Connected through hyperedge HE-3 (induced by source paper "sok tools for game theoretic models of security for cryptocurrencies"):
  with members:
    - "a survey on consensus mechanisms and mining strategy management in blockchain networks"
    - "selfish mining in ethereum"
    - "impossibility of full decentralization in permissionless blockchains"
    - "squirrl automating attack discovery on blockchain incentive mechanisms with deep reinforcement learning"
    - "an axiomatic approach to block rewards"
    - "reward sharing schemes for stake pools"
    - "compounding of wealth in proof of stake cryptocurrencies"
    - "blockmania from block dags to consensus"

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.GT(Computer Science and Game Theory)