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: "the geography of references in elite articles which countries contribute to the archives of knowledge"
  Abstract: This study asks the question on which national “shoulders” the world’s top-level research stands. Traditionally, the number of citations to national papers has been the evaluative measures of national scientific standings. We raise a different question: instead of analyzing the citations to a countries’ articles (the forward view), we examine references to prior publications from specific countries cited in the most elite publications (the backward—citing—view). “Elite publications” are operationalized as the top-1% most-highly cited articles. Using the articles published from 2004 to 2013, we examine the research referenced in these works. Our results confirm the well-known fact that China has emerged to become a major player in science. However, China still belongs to the low contributors when countries are ranked as contributors to the cited references in top-1% articles. Using this perspective, the results do not support a decreasing trend for the USA; in fact, the USA exceeds expectations (compared to its publication share) in terms of references in the top-1% articles. Switzerland, Sweden, and the Netherlands also appear at the top of the list. However, the results for Germany are lower than statistically expected.

Connected through hyperedge HE-1 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching"):
  with members:
    - "the preeminence of ethnic diversity in scientific collaboration"
    - "field normalization of scientometric indicators"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "relative citation ratio rcr an empirical attempt to study a new field normalized bibliometric indicator"
    - "validity of basing authors publication strategy on journal impact factors"
    - "a review of theory and practice in scientometrics"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"
    - "a review of the literature on citation impact indicators"

Connected through hyperedge HE-2 (induced by source paper "on the challenges ahead of spatial scientometrics focusing on the city level"):
  with members:
    - "a spatial scientometric analysis of the publication output of cities worldwide"
    - "exploring the position of cities in global corporate research and development a bibliometric analysis by two different geographical approaches"
    - "concentration of research funding leads to decreasing marginal returns"
    - "a methodology to compute the territorial productivity of scientists the case of italy"
    - "a new bibliometric approach to assess the scientific specialization of regions"
    - "the european union china and the united states in the top 1 and top 10 layers of most frequently cited publications competition and collaborations"
    - "mapping excellence in the geography of science an approach based on scopus data"
    - "the detection of hot regions in the geography of science a visualization approach by using density maps"

Connected through hyperedge HE-3 (induced by source paper "the negative effects of citing with a national orientation in terms of recognition national and international citations in natural sciences papers from germany the netherlands and the uk"):
  with members:
    - "who benefits from a country s scientific research"
    - "a century of science globalization of scientific collaborations citations and innovations"
    - "citations indicators of quality the impact fallacy"
    - "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers"
    - "the european union china and the united states in the top 1 and top 10 layers of most frequently cited publications competition and collaborations"
    - "the use of percentiles and percentile rank classes in the analysis of bibliometric data opportunities and limits"

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)