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 "knowledge generating efficiency in innovation systems the relation between structural and temporal effects"):
  Abstract: Time series of US patents per million inhabitants show long waves that partially coincide with Kondratieff cycles. This wave structure can be attributed to different knowledge-generating paradigms that drive innovation systems thereof. The changes in the slopes between the waves indicate different efficiencies in the knowledge generation. Since knowledge-generating systems are associated with innovation systems, the efficiency can be modelled in terms of interactions among dimensions (for example, in terms of university-industry-government relations). The model predicts an efficiency increase with an increasing number of dimensions due to the effects of self-organisation among them. The time spans of the knowledge-generating cycles can also be analysed in terms of Fibonacci numbers and successive cycles are expected to exhibit shorter life cycles than previous ones. This perspective enables us to forecast expected dates of future paradigm changes.

Includes members:
  Member "rotational symmetry and the transformation of innovation systems in a triple helix of university industry government relations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "synergy in the knowledge base of u s innovation systems at national state and regional levels the contributions of high tech manufacturing and knowledge intensive services")
  Member "publish or patent bibliometric evidence for empirical trade offs in national funding strategies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data mining the foundational patents of photovoltaic materials an application of patent citation spectroscopy")

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.CY(Computers and Society)