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: "amplifying the impact of open access wikipedia and the diffusion of science"
  Abstract: With the rise of Wikipedia as a first-stop source for scientific information, it is important to understand whether Wikipedia draws upon the research that scientists value most. Here we identify the 250 most heavily used journals in each of 26 research fields (4,721 journals, 19.4M articles) indexed by the Scopus database, and test whether topic, academic status, and accessibility make articles from these journals more or less likely to be referenced on Wikipedia. We find that a journal's academic status (impact factor) and accessibility (open access policy) both strongly increase the probability of it being referenced on Wikipedia. Controlling for field and impact factor, the odds that an open access journal is referenced on the English Wikipedia are 47% higher compared to paywall journals. These findings provide evidence is that a major consequence of open access policies is to significantly amplify the diffusion of science, through an intermediary like Wikipedia, to a broad audience.

Connected through hyperedge HE-1 (induced by source paper "quantifying engagement with citations on wikipedia"):
  with members:
    - "citation needed a taxonomy and algorithmic assessment of wikipedia s verifiability"
    - "mapping the backbone of the humanities through the eyes of wikipedia"
    - "detecting and gauging impact on wikipedia page views"
    - "eliciting new wikipedia users interests via automatically mined questionnaires for a warm welcome not a cold start"
    - "why the world reads wikipedia beyond english speakers"
    - "structuring wikipedia articles with section recommendations"
    - "why we read wikipedia"
    - "growing wikipedia across languages via recommendation"

Connected through hyperedge HE-2 (induced by source paper "science through wikipedia a novel representation of open knowledge through co citation networks"):
  with members:
    - "mapping the backbone of the humanities through the eyes of wikipedia"
    - "the insoluble problems of books what does altmetric com have to offer"
    - "knowledge acquisition a complex networks approach"
    - "using network science and text analytics to produce surveys in a scientific topic"
    - "using almetrics for contextualised mapping of societal impact from hits to networks"
    - "power laws in citation distributions evidence from scopus"
    - "mapping citation patterns of book chapters in the book citation index"
    - "global maps of science based on the new web of science categories"

Connected through hyperedge HE-3 (induced by source paper "mapping the backbone of the humanities through the eyes of wikipedia"):
  with members:
    - "mapping citation patterns of book chapters in the book citation index"
    - "global maps of science based on the new web of science categories"
    - "the structure of the arts humanities citation index a mapping on the basis of aggregated citations among 1 157 journals"
    - "science overlay maps a new tool for research policy and library management"

Connected through hyperedge HE-4 (induced by source paper "how frequently are articles in predatory open access journals cited"):
  with members:
    - "scholarly journal publishing in transition from restricted to open access"

Connected through hyperedge HE-5 (induced by source paper "using deep learning for title based semantic subject indexing to reach competitive performance to full text"):
  with members:
    - "lstm a search space odyssey"
    - "on the state of the art of evaluation in neural language models"
    - "do convolutional networks need to be deep for text classification"
    - "comparative study of cnn and rnn for natural language processing"
    - "recent trends in deep learning based natural language processing"
    - "deep extreme multi label learning"
    - "using titles vs full text as source for automated semantic document annotation"
    - "multichannel variable size convolution for sentence classification"

Connected through hyperedge HE-6 (induced by source paper "cloud kotta enabling secure and scalable data analytics in the cloud"):
  with members:
    - "a secure data enclave and analytics platform for social scientists"
    - "fast flexible models for discovering topic correlation across weakly related collections"
    - "bigexcel a web based framework for exploring big data in social sciences"
    - "distributed representations of words and phrases and their compositionality"
    - "the author topic model for authors and documents"

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)