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: "liposomes versus metallic nanostructures differences in the process of knowledge translation in cancer"
  Abstract: This research maps the knowledge translation process for two different types of nanotechnologies applied to cancer: liposomes and metallic nanostructures (MNs). We performed a structural analysis of citation networks and text mining supported in controlled vocabularies. In the case of liposomes, our results identify subnetworks (invisible colleges) associated with different therapeutic strategies: nanopharmacology, hyperthermia, and gene therapy. Only in the pharmacological strategy was an organized knowledge translation process identified, which, however, is monopolized by the liposomal doxorubicins. In the case of MNs, subnetworks are not differentiated by the type of therapeutic strategy, and the content of the documents is still basic research. Research on MNs is highly focused on developing a combination of molecular imaging and photothermal therapy.

Connected through hyperedge HE-1 (induced by source paper "hierarchy of knowledge translation from health problems to ad hoc drug design"):
  with members:
    - "hegemonic structure of basic clinical and patented knowledge on ebola research a us army reductionist initiative"
    - "mapping knowledge translation and innovation processes in cancer drug development the case of liposomal doxorubicin"

Connected through hyperedge HE-2 (induced by source paper "the effects of research level and article type on the differences between citation metrics and f1000 recommendations"):
  with members:
    - "inter rater reliability and convergent validity of f1000prime peer review"
    - "mapping knowledge translation and innovation processes in cancer drug development the case of liposomal doxorubicin"
    - "citation analysis may severely underestimate the impact of clinical research as compared to basic research"
    - "the validation of advanced bibliometric indicators through peer assessments a comparative study using data from incites and f1000"

Connected through hyperedge HE-3 (induced by source paper "hegemonic structure of basic clinical and patented knowledge on ebola research a us army reductionist initiative"):
  with members:
    - "mapping knowledge translation and innovation processes in cancer drug development the case of liposomal doxorubicin"

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.DL(Digital Libraries)