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: "two models of nonadaptive group testing for designing screening experiments"
  Abstract: We discuss two non-standard models of nonadaptive combinatorial search which develop the conventional disjunct search model of Du and Hwang (1993) for a small number of defective elements contained in a finite ground set or a population. The first model called asearch of defective supersets (complexes)was suggested in D’yachkovetal. (2000c,d). The second model which can be called asearch of defective subsets in the presence of inhibitorswas introduced for the case of an adaptive search by Farachetal. (1997) and De Bonis and Vaccaro (1998). For these models, we study the constructive search methods based on the known constructions for the disjunct model from Kautz and Singleton (1964) and from D’yachkovetal. (2000a,b).

Connected through hyperedge HE-1 (induced by source paper "learning immune defectives graph through group tests"):
  with members:
    - "non adaptive group testing with inhibitors"
    - "semiquantitative group testing"
    - "non adaptive group testing explicit bounds and novel algorithms"

Connected through hyperedge HE-2 (induced by source paper "superimposed codes and threshold group testing"):
  with members:
    - "lectures on designing screening experiments"
    - "semiquantitative group testing"
    - "semi quantitative group testing"
    - "improved constructions for non adaptive threshold group testing"

Connected through hyperedge HE-3 (induced by source paper "non adaptive group testing with inhibitors"):
  with members:
    - "sparse signal processing with linear and non linear observations a unified shannon theoretic approach"
    - "non adaptive group testing explicit bounds and novel algorithms"

Connected through hyperedge HE-4 (induced by source paper "multi group testing for items with real valued status under standard arithmetic"):
  with members:
    - "lectures on designing screening experiments"
    - "semiquantitative group testing"
    - "boolean compressed sensing and noisy group testing"
    - "semi quantitative group testing"

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.IT(Information Theory)