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 "on the predictability of the number of convex vertices"):
  Abstract: Convex hulls are a fundamental geometric tool used in a number of algorithms. As a side-effect of exhaustive tests for an algorithm for which a convex hull computation was the first step, interesting experimental results were found and are the sunject of this paper. They establish that the number of convex vertices of natural datasets can be predicted, if not precisely at least within a defined range. Namely it was found that the number of convex vertices of a dataset of N points lies in the range 2.35 N^0.091 <= h <= 19.19 N^0.091. This range obviously does not describe neither natural nor artificial worst-cases but corresponds to the distributions of natural data. This can be used for instance to define a starting size for pre-allocated arrays or to evaluate output-sensitive algorithms. A further consequence of these results is that the random models of data used to test convex hull algorithms should be bounded by rectangles and not as they usually are by circles if they want to represent accurately natural datasets

Includes members:
  Member "the number of distinct distances from a vertex of a convex polygon":
    also connected through other hyperedges:
      (none)
  Member "on the reflexivity of point sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "correcting self intersecting polygons using minimal memory a simple and efficient algorithm and thoughts on line segment intersection algorithms")

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.CG(Computational Geometry)