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: "patterns of authors contribution in scientific manuscripts"
  Abstract: Science is becoming increasingly more interdisciplinary, giving rise to more diversity in the areas of expertise. In such a complex environment, the participation of authors became more specialized, hampering the task of evaluating authors according to their contributions. While some metrics were adapted to account for the order (or rank) of authors in a paper, many journals are now requiring a description of their specific roles in the publication. Surprisingly, the investigation of the relationships between credited contributions and author's rank has been limited to a few studies. Here we analyzed such a kind of data and show, quantitatively, that the regularity in the authorship contributions decreases with the number of authors in a paper. Furthermore, we found that the rank of authors and their roles in papers follow three general patterns according to the nature of their contributions: (i) the total contribution increases with author's rank; (ii) the total contribution decreases with author's rank; and (iii) the total contribution is symmetric, with most of contributions being performed by first and last authors. This was accomplished by collecting and analyzing the data retrieved from PLoS One and by devising a measurement of the effective number of authors in a paper. The analysis of such patterns confirms that some aspects of the author ranking are in accordance with the expected convention, such as the first and last authors being more likely to contribute more diversely in a scientific work. Conversely, such analysis also revealed that authors in the intermediary positions of the rank contribute more in specific roles, such as collecting data. This indicates that the an unbiased evaluation of researchers must take into account the distinct types of scientific contributions.

Connected through hyperedge HE-1 (induced by source paper "comparing the impact of subfields in scientific journals"):
  with members:
    - "practical method to reclassify web of science articles into unique subject categories and broad disciplines"
    - "recency predicts bursts in the evolution of author citations"
    - "knowledge acquisition a complex networks approach"
    - "citation success index an intuitive pair wise journal comparison metric"
    - "concentric network symmetry grasps authors styles in word adjacency networks"
    - "a review of the literature on citation impact indicators"
    - "citations versus journal impact factor as proxy of quality could the latter ever be preferable"
    - "indicators of the interdisciplinarity of journals diversity centrality and citations"

Connected through hyperedge HE-2 (induced by source paper "a complex network approach to political analysis application to the brazilian chamber of deputies"):
  with members:
    - "from louvain to leiden guaranteeing well connected communities"
    - "word sense disambiguation a complex network approach"
    - "extractive multi document summarization using multilayer networks"
    - "analyzing dynamic ideological communities in congressional voting networks"
    - "knowledge acquisition a complex networks approach"
    - "using network science and text analytics to produce surveys in a scientific topic"
    - "using complex networks for text classification discriminating informative and imaginative documents"
    - "cohesion and coalition formation in the european parliament roll call votes and twitter activities"

Connected through hyperedge HE-3 (induced by source paper "co contributorship network and division of labor in individual scientific collaborations"):
  with members:
    - "applying centrality measures to impact analysis a coauthorship network analysis"

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)