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 "statistical epistemic logic"):
  Abstract: We introduce a modal logic for describing statistical knowledge, which we call statistical epistemic logic. We propose a Kripke model dealing with probability distributions and stochastic assignments, and show a stochastic semantics for the logic. To our knowledge, this is the first semantics for modal logic that can express the statistical knowledge dependent on non-deterministic inputs and the statistical significance of observed results. By using statistical epistemic logic, we express a notion of statistical secrecy with a confidence level. We also show that this logic is useful to formalize statistical hypothesis testing and differential privacy in a simple and abstract manner.

Includes members:
  Member "local obfuscation mechanisms for hiding probability distributions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "privacy preserving multiple tensor factorization for synthesizing large scale location traces")
  Member "hybrid statistical estimation of mutual information and its application to information flow":
    also connected through other hyperedges:
      (none)
  Member "towards logical specification of statistical machine learning":
    also connected through other hyperedges:
      (none)
  Member "hyperpctl a temporal logic for probabilistic hyperproperties":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "statistical model checking for hyperproperties")
  Member "on the anonymization of differentially private location obfuscation":
    also connected through other hyperedges:
      (none)
  Member "proving differential privacy in hoare logic":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "guidelines for implementing and auditing differentially private systems")
  Member "statistical model checking an overview":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "probabilistic verification of fairness properties via concentration")
  Member "an epistemic approach to coercion resistance for electronic voting protocols":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "formal analysis of an e health protocol")

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.LO(Logic in Computer Science)