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: "probabilistic model based safety analysis"
  Abstract: Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environment). The advantage of these methods compared to traditional approaches is that the analysis of the whole system gives more precise results. Only few model-based approaches have been applied to answer quantitative questions in safety analysis, often limited to analysis of specific failure propagation models, limited types of failure modes or without system dynamics and behavior, as direct quantitative analysis is uses large amounts of computing resources. New achievements in the domain of (probabilistic) model-checking now allow for overcoming this problem. #R##N#This paper shows how functional models based on synchronous parallel semantics, which can be used for system design, implementation and qualitative safety analysis, can be directly re-used for (model-based) quantitative safety analysis. Accurate modeling of different types of probabilistic failure occurrence is shown as well as accurate interpretation of the results of the analysis. This allows for reliable and expressive assessment of the safety of a system in early design stages.

Connected through hyperedge HE-1 (induced by source paper "quantitative aspects of programming languages and systems over the past 2 4 years and beyond"):
  with members:
    - "paws a tool for the analysis of weighted systems"
    - "divide and conquer variable set separation in hybrid systems reachability analysis"
    - "logical characterization of trace metrics"
    - "design and optimisation of the flyfast front end for attribute based coordination"
    - "language based abstractions for dynamical systems"
    - "limit your consumption finding bounds in average energy games"
    - "mela modelling in ecology with location attributes"
    - "logical characterization of bisimulation metrics"

Connected through hyperedge HE-2 (induced by source paper "model exploration and analysis for quantitative safety refinement in probabilistic b"):
  with members:
    - "quantitative safety linking proof based verification with model checking for probabilistic systems"
    - "significant diagnostic counterexamples in probabilistic model checking"

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.LO(Logic in Computer Science)