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: "bitcoin cooperative proof of stake"
  Abstract: A hard-fork reconfiguration of the peer to peer Bitcoin network is described that substitutes tamper-evident logs and proof-of-stake consensus for proof-of-work consensus. The block creation rewards and transaction fees are reallocated to establish and staff a secure financial data network capable of handling the world's transactions with subsecond response time. The new system pays dividends to stake-offering bitcoin holders. In contrast to Satoshi Nakamoto's mesh network consisting of competing peers, this system uses an enterprise class network that is efficient, robust, and scalable, consisting of cooperating peers. The network backbone nodes host trustless nomadic agents. Thousands of distributed full nodes are paid to replicate a singleton blockchain built upon every 10 minutes by a nomadic mint agent whose actions are verified by its peers. This arrangement enables immediate acknowledgment to an issuing node that its transaction has been accepted. Less effort means that subsidized transaction costs will be lower. Network reconfiguration enables the processing of numerous microtransactions. Stake-weighted distributed consensus is achieved when necessary with less than one-half arbitrarily faulty nodes. Important invariants of the Satoshi Social Contract between core developers and users are maintained: The reward schedule, the blockchain format, the fixed number of bitcoins, and the decentralized, trustless protocol are untouched. The system remains a global distributed database, with additions to the database by consent of the majority, based on a set of transparent rules they follow.

Connected through hyperedge HE-1 (induced by source paper "finbrain when finance meets ai 2 0"):
  with members:
    - "from eliza to xiaoice challenges and opportunities with social chatbots"
    - "struc2vec learning node representations from structural identity"
    - "deepar probabilistic forecasting with autoregressive recurrent networks"
    - "neural collaborative filtering"
    - "end to end task completion neural dialogue systems"
    - "metacontrol for adaptive imagination based optimization"
    - "adversarial learning for neural dialogue generation"
    - "deepfm a factorization machine based neural network for ctr prediction"

Connected through hyperedge HE-2 (induced by source paper "blockchain a graph primer"):
  with members:
    - "a survey on security and privacy issues of bitcoin"
    - "dandelion redesigning the bitcoin network for anonymity"
    - "bitcoin transaction graph analysis"

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.CY(Computers and Society)