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: "on the testability of causal models with latent and instrumental variables"
  Abstract: Certain causal models involving unmeasured variables induce no independence constraints among the observed variables but imply, nevertheless, inequality contraints on the observed distribution. This paper derives a general formula for such instrumental variables, that is, exogenous variables that directly affect some variables but not all. With the help of this formula, it is possible to test whether a model involving instrumental variables may account for the data, or, conversely, whether a given variables can be deemed instrumental.

Connected through hyperedge HE-1 (induced by source paper "identifying independencies in causal graphs with feedback"):
  with members:
    - "counterfactual probabilities computational methods bounds and applications"
    - "a definition and graphical representation for causality"
    - "causal networks semantics and expressiveness"

Connected through hyperedge HE-2 (induced by source paper "instrumentality tests revisited"):
  with members:
    - "causality in bayesian belief networks"
    - "graphical models and exponential families"
    - "decision theoretic foundations for causal reasoning"

Connected through hyperedge HE-3 (induced by source paper "inequality constraints in causal models with hidden variables"):
  with members:
    - "counterfactual probabilities computational methods bounds and applications"
    - "quantifier elimination for statistical problems"
    - "graphical models and exponential families"
    - "causal discovery from a mixture of experimental and observational data"
    - "instrumentality tests revisited"
    - "a bayesian approach to learning causal networks"
    - "on the testable implications of causal models with hidden variables"
    - "decision theoretic foundations for causal reasoning"

Connected through hyperedge HE-4 (induced by source paper "on the testable implications of causal models with hidden variables"):
  with members:
    - "graphical models and exponential families"

Connected through hyperedge HE-5 (induced by source paper "information theoretic inference of common ancestors"):
  with members:
    - "quantifying unique information"
    - "quantifying synergistic mutual information"
    - "discovering structure in high dimensional data through correlation explanation"
    - "bivariate measure of redundant information"
    - "entropic inequalities and marginal problems"
    - "causal networks semantics and expressiveness"
    - "nonnegative decomposition of multivariate information"
    - "information inequalities for joint distributions with interpretations and applications"

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.AI(Artificial Intelligence)