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: "distortive effects of initial based name disambiguation on measurements of large scale coauthorship networks"
  Abstract: Scholars have often relied on name initials to resolve name ambiguities in large-scale coauthorship network research. This approach bears the risk of incorrectly merging or splitting author identities. The use of initial-based disambiguation has been justified by the assumption that such errors would not affect research findings too much. This paper tests that assumption by analyzing coauthorship networks from five academic fields-biology, computer science, nanoscience, neuroscience, and physics-and an interdisciplinary journal, PNAS. Name instances in data sets of this study were disambiguated based on heuristics gained from previous algorithmic disambiguation solutions. We use disambiguated data as a proxy of ground-truth to test the performance of three types of initial-based disambiguation. Our results show that initial-based disambiguation can misrepresent statistical properties of coauthorship networks: It deflates the number of unique authors, number of components, average shortest paths, clustering coefficient, and assortativity, while it inflates average productivity, density, average coauthor number per author, and largest component size. Also, on average, more than half of top 10 productive or collaborative authors drop off the lists. Asian names were found to account for the majority of misidentification by initial-based disambiguation due to their common surname and given name initials.

Connected through hyperedge HE-1 (induced by source paper "the citation advantage of linking publications to research data"):
  with members:
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "the discretised lognormal and hooked power law distributions for complete citation data best options for modelling and regression"
    - "regression for citation data an evaluation of different methods"
    - "efficient estimation of word representations in vector space"
    - "mandated data archiving greatly improves access to research data"
    - "linking to data effect on citation rates in astronomy"
    - "the numpy array a structure for efficient numerical computation"
    - "self selected or mandated open access increases citation impact for higher quality research"

Connected through hyperedge HE-2 (induced by source paper "convexity in scientific collaboration networks"):
  with members:
    - "convex skeletons of complex networks"
    - "convexity in complex networks"
    - "constructing bibliometric networks a comparison between full and fractional counting"
    - "full and fractional counting in bibliometric networks"
    - "betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks"
    - "applying centrality measures to impact analysis a coauthorship network analysis"
    - "co authorship networks in the digital library research community"

Connected through hyperedge HE-3 (induced by source paper "author name disambiguation of bibliometric data a comparison of several unsupervised approaches"):
  with members:
    - "evaluating author name disambiguation for digital libraries a case of dblp"
    - "effective unsupervised author disambiguation with relative frequencies"
    - "scale free collaboration networks an author name disambiguation perspective"
    - "exploiting citation networks for large scale author name disambiguation"

Connected through hyperedge HE-4 (induced by source paper "evaluating author name disambiguation for digital libraries a case of dblp"):
  with members:
    - "homonym detection in curated bibliographies learning from dblp s experience full version"
    - "evaluating co authorship networks in author name disambiguation for common names"
    - "ethnicity sensitive author disambiguation using semi supervised learning"
    - "growth rates of modern science a bibliometric analysis based on the number of publications and cited references"
    - "exploiting citation networks for large scale author name disambiguation"
    - "accuracy of simple initials based methods for author name disambiguation"
    - "coauthorship and citation patterns in the physical review"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"

Connected through hyperedge HE-5 (induced by source paper "the impact of imbalanced training data on machine learning for author name disambiguation"):
  with members:
    - "evaluating author name disambiguation for digital libraries a case of dblp"
    - "scaling author name disambiguation with cnf blocking"
    - "ethnicity sensitive author disambiguation using semi supervised learning"
    - "smote synthetic minority over sampling technique"

Connected through hyperedge HE-6 (induced by source paper "scale free collaboration networks an author name disambiguation perspective"):
  with members:
    - "evaluating author name disambiguation for digital libraries a case of dblp"
    - "coauthorship and citation patterns in the physical review"
    - "pagerank for ranking authors in co citation networks"

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)