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: "measuring progress of probabilistic ltl model checking"
  Abstract: Recently, Zhang and Van Breugel introduced the notion of a progress measure for a probabilistic model checker. Given a linear-time property P and a description of the part of the system that has already been checked, the progress measure returns a real number in the unit interval. The real number captures how much progress the model checker has made towards verifying P. If the progress is zero, no progress has been made. If it is one, the model checker is done. They showed that the progress measure provides a lower bound for the measure of the set of execution paths that satisfy P. They also presented an algorithm to compute the progress measure when P is an invariant. #R##N#In this paper, we present an algorithm to compute the progress measure when P is a formula of a positive fragment of linear temporal logic. In this fragment, we can express invariants but also many other interesting properties. The algorithm is exponential in the size of P and polynomial in the size of that part of the system that has already been checked. We also present an algorithm to compute a lower bound for the progress measure in polynomial time.

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"

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)