human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "A Statistical Semantics for Causation Key words: causality, induction, learning"):
  Abstract: We propose a model-theoretic definition of causation, and show that, contrary to common folklore, genuine causal influences can be distinguished from spurious covari-ations following standard norms of inductive reasoning. We also establish a complete characterization of the conditions under which such a distinction is possible. Finally, we provide a proof-theoretical procedure for inductive causation and show that, for a large class of data and structures, effective algorithms exist that uncover the direction of causal influences as defined above.

Includes members:
  Member "Two Algorithms for Inducing Structural Equation Models from Data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Causal inference, path analysis, and recursive struc-tural equations models. In C. Clogg, editor, Sociological Methodology,")
  Member "Regression Can Build Predictive Causal Models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Causal inference, path analysis, and recursive struc-tural equations models. In C. Clogg, editor, Sociological Methodology,")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Probabilistic_Methods