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 preeminence of ethnic diversity in scientific collaboration"
  Abstract: Inspired by the social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists to study the relationship between research impact and five classes of diversity: ethnicity, discipline, gender, affiliation, and academic age. Using randomized baseline models, we establish the presence of homophily in ethnicity, gender and affiliation. We then study the effect of diversity on scientific impact, as reflected in citations. Remarkably, of the classes considered, ethnic diversity had the strongest correlation with scientific impact. To further isolate the effects of ethnic diversity, we used randomized baseline models and again found a clear link between diversity and impact. To further support these findings, we use coarsened exact matching to compare the scientific impact of ethnically diverse papers and scientists with closely-matched control groups. Here, we find that ethnic diversity resulted in an impact gain of 10.63% for papers, and 47.67% for scientists. Diversity is believed to raise effectiveness and performance but it contains many aspects. Here the authors studied the relationship between research impact and five classes of diversity and found that ethnic diversity had the strongest correlation with scientific impact.

Connected through hyperedge HE-1 (induced by source paper "neural embeddings of scholarly periodicals reveal complex disciplinary organizations"):
  with members:
    - "the geometry of culture analyzing the meanings of class through word embeddings"
    - "semaxis a lightweight framework to characterize domain specific word semantics beyond sentiment"
    - "a style based generator architecture for generative adversarial networks"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "semantics derived automatically from language corpora contain human like biases"
    - "node2vec scalable feature learning for networks"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "man is to computer programmer as woman is to homemaker debiasing word embeddings"

Connected through hyperedge HE-2 (induced by source paper "china may need to support more small teams in scientific research"):
  with members:
    - "practical method to reclassify web of science articles into unique subject categories and broad disciplines"
    - "collaboration diversity and scientific impact"
    - "funding acknowledgment analysis queries and caveats"
    - "the relationship among research productivity research collaboration and their determinants"
    - "characterization description and considerations for the use of funding acknowledgement data in web of science"
    - "understanding the group dynamics and success of teams"
    - "field normalized citation impact indicators and the choice of an appropriate counting method"

Connected through hyperedge HE-3 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching"):
  with members:
    - "the geography of references in elite articles which countries contribute to the archives of knowledge"
    - "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-4 (induced by source paper "the secret lives of names name embeddings from social media"):
  with members:
    - "nationality classification using name embeddings"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-5 (induced by source paper "international research collaboration novelty conventionality and atypicality in knowledge recombination"):
  with members:
    - "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers"

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)