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 "cylindrical algebraic decomposition with equational constraints"):
  Abstract: Cylindrical Algebraic Decomposition (CAD) has long been one of the most important algorithms within Symbolic Computation, as a tool to perform quantifier elimination in first order logic over the reals. More recently it is finding prominence in the Satisfiability Checking community as a tool to identify satisfying solutions of problems in nonlinear real arithmetic. #R##N#The original algorithm produces decompositions according to the signs of polynomials, when what is usually required is a decomposition according to the truth of a formula containing those polynomials. One approach to achieve that coarser (but hopefully cheaper) decomposition is to reduce the polynomials identified in the CAD to reflect a logical structure which reduces the solution space dimension: the presence of Equational Constraints (ECs). #R##N#This paper may act as a tutorial for the use of CAD with ECs: we describe all necessary background and the current state of the art. In particular, we present recent work on how McCallum's theory of reduced projection may be leveraged to make further savings in the lifting phase: both to the polynomials we lift with and the cells lifted over. We give a new complexity analysis to demonstrate that the double exponent in the worst case complexity bound for CAD reduces in line with the number of ECs. We show that the reduction can apply to both the number of polynomials produced and their degree.

Includes members:
  Member "identifying the parametric occurrence of multiple steady states for some biological networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved cross validation for classifiers that make algorithmic choices to minimise runtime without compromising output correctness")
  Member "using machine learning to improve cylindrical algebraic decomposition":
    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 "theoryguru a mathematica package to apply quantifier elimination technology to economics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition")
  Member "machine learning for mathematical software":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using machine learning to improve cylindrical algebraic decomposition")
  Member "towards incremental cylindrical algebraic decomposition in maple":
    also connected through other hyperedges:
      (none)
  Member "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using machine learning to improve cylindrical algebraic decomposition")
  Member "a case study on the parametric occurrence of multiple steady states":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")

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)