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: "power laws in citation distributions evidence from scopus"
  Abstract: Modeling distributions of citations to scientific papers is crucial for understanding how science develops. However, there is a considerable empirical controversy on which statistical model fits the citation distributions best. This paper is concerned with rigorous empirical detection of power-law behaviour in the distribution of citations received by the most highly cited scientific papers. We have used a large, novel data set on citations to scientific papers published between 1998 and 2002 drawn from Scopus. The power-law model is compared with a number of alternative models using a likelihood ratio test. We have found that the power-law hypothesis is rejected for around half of the Scopus fields of science. For these fields of science, the Yule, power-law with exponential cut-off and log-normal distributions seem to fit the data better than the pure power-law model. On the other hand, when the power-law hypothesis is not rejected, it is usually empirically indistinguishable from most of the alternative models. The pure power-law model seems to be the best model only for the most highly cited papers in "Physics and Astronomy". Overall, our results seem to support theories implying that the most highly cited scientific papers follow the Yule, power-law with exponential cut-off or log-normal distribution. Our findings suggest also that power laws in citation distributions, when present, account only for a very small fraction of the published papers (less than 1% for most of science fields) and that the power-law scaling parameter (exponent) is substantially higher (from around 3.2 to around 4.7) than found in the older literature.

Connected through hyperedge HE-1 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications"):
  with members:
    - "scholarly twitter metrics"
    - "social media metrics for new research evaluation"
    - "mendeley readership as a filtering tool to identify highly cited publications"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "using almetrics for contextualised mapping of societal impact from hits to networks"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"
    - "tweets as impact indicators examining the implications of automated bot accounts on twitter"

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"
    - "amplifying the impact of open access wikipedia and the diffusion of science"
    - "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"
    - "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 "analysis of reference and citation copying in evolving bibliographic networks"):
  with members:
    - "relay linking models for prominence and obsolescence in evolving networks"
    - "quantifying long term scientific impact"

Connected through hyperedge HE-4 (induced by source paper "research assessment by percentile based double rank analysis"):
  with members:
    - "citation score normalized by cited references csncr the introduction of a new citation impact indicator"
    - "efficiency of research performance and the glass researcher"
    - "identifying potential breakthrough publications using refined citation analyses three related explorative approaches"
    - "a review of the literature on citation impact indicators"
    - "regression for citation data an evaluation of different methods"
    - "how are excellent highly cited papers defined in bibliometrics a quantitative analysis of the literature"
    - "distributions for cited articles from individual subjects and years"
    - "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers"

Connected through hyperedge HE-5 (induced by source paper "on the heterogeneous distributions in paper citations"):
  with members:
    - "skewness of citation impact data and covariates of citation distributions a large scale empirical analysis based on web of science data"
    - "citation count distributions for large monodisciplinary journals"
    - "citations indicators of quality the impact fallacy"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"
    - "predicting the long term citation impact of recent publications"
    - "a review of the literature on citation impact indicators"
    - "distributions for cited articles from individual subjects and years"

Connected through hyperedge HE-6 (induced by source paper "the emergence and evolution of the research fronts in hiv aids research"):
  with members:
    - "hierarchy of knowledge translation from health problems to ad hoc drug design"
    - "hegemonic structure of basic clinical and patented knowledge on ebola research a us army reductionist initiative"

Connected through hyperedge HE-7 (induced by source paper "the scaling relationship between citation based performance and coauthorship patterns in natural sciences"):
  with members:
    - "a new methodology for constructing a publication level classification system of science"

Connected through hyperedge HE-8 (induced by source paper "the precision of the arithmetic mean geometric mean and percentiles for citation data an experimental simulation modelling approach"):
  with members:
    - "national disciplinary and temporal variations in the extent to which articles with more authors have more impact evidence from a geometric field normalised citation indicator"
    - "the vqr italy s second national research assessment methodological failures and ranking distortions"
    - "the relationship between the number of authors of a publication its citations and the impact factor of the publishing journal evidence from italy"
    - "more precise methods for national research citation impact comparisons"
    - "national research impact indicators from mendeley readers"
    - "tweets vs mendeley readers how do these two social media metrics differ"
    - "regression for citation data an evaluation of different methods"
    - "distributions for cited articles from individual subjects and years"

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)