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 "comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition"):
  Abstract: There has been recent interest in the use of machine learning (ML) approaches within mathematical software to make choices that impact on the computing performance without affecting the mathematical correctness of the result. We address the problem of selecting the variable ordering for cylindrical algebraic decomposition (CAD), an important algorithm in Symbolic Computation. Prior work to apply ML on this problem implemented a Support Vector Machine (SVM) to select between three existing human-made heuristics, which did better than anyone heuristic alone. Here we extend this result by training ML models to select the variable ordering directly, and by trying out a wider variety of ML techniques.

Includes members:
  Member "using machine learning to improve cylindrical algebraic decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "theoryguru a mathematica package to apply quantifier elimination technology to economics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "non linear real arithmetic benchmarks derived from automated reasoning in economics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "machine learning for mathematical software":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "a case study on the parametric occurrence of multiple steady states":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "deepmath deep sequence models for premise selection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic")
  Member "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cylindrical algebraic decomposition with equational constraints")

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.SC(Symbolic Computation)