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: "predicting publication long term impact through a combination of early citations and journal impact factor"
  Abstract: Abstract   The ability to predict the long-term impact of a scientific article soon after its publication is of great value towards accurate assessment of research performance. In this work we test the hypothesis that good predictions of long-term citation counts can be obtained through a combination of a publication's early citations and the impact factor of the hosting journal. The test is performed on a corpus of 123,128 WoS publications authored by Italian scientists, using linear regression models. The average accuracy of the prediction is good for citation time windows above two years, decreases for lowly-cited publications, and varies across disciplines. As expected, the role of the impact factor in the combination becomes negligible after only two years from publication.

Connected through hyperedge HE-1 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications"):
  with members:
    - "systematic analysis of agreement between metrics and peer review in the uk ref"
    - "peer review and citation data in predicting university rankings a large scale analysis"
    - "do citations and readership identify seminal publications"
    - "revisiting the scientometric conceptualization of impact and its measurement"
    - "selecting competent referees to assess research projects proposals a study of referees registers"
    - "do they agree bibliometric evaluation versus informed peer review in the italian research assessment exercise"
    - "refrain from adopting the combination of citation and journal metrics to grade publications as used in the italian national research assessment exercise vqr 2011 2014"
    - "citations indicators of quality the impact fallacy"

Connected through hyperedge HE-2 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities"):
  with members:
    - "the impact of unproductive and top researchers on overall university research performance"
    - "the elephant in the room the problem of quantifying productivity in evaluative scientometrics"
    - "the ratio of top scientists to the academic staff as an indicator of the competitive strength of universities"
    - "not dead just resting the practical value of per publication citation indicators"
    - "efficiency of research performance and the glass researcher"
    - "ranking research institutions by the number of highly cited articles per scientist"
    - "predicting the long term citation impact of recent publications"
    - "how do you define and measure research productivity"

Connected through hyperedge HE-3 (induced by source paper "testing for universality of mendeley readership distributions"):
  with members:
    - "revisiting the scientometric conceptualization of impact and its measurement"
    - "an investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level"
    - "skewness of citation impact data and covariates of citation distributions a large scale empirical analysis based on web of science data"
    - "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"
    - "how well developed are altmetrics a cross disciplinary analysis of the presence of alternative metrics in scientific publications"
    - "revisiting the scaling of citations for research assessment"
    - "altmetrics in the wild using social media to explore scholarly impact"

Connected through hyperedge HE-4 (induced by source paper "predicting publication productivity for researchers a latent variable model"):
  with members:
    - "predicting citation counts based on deep neural network learning techniques"
    - "predicting publication productivity for researchers a piecewise poisson model"
    - "can scientific impact be predicted"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"
    - "quantifying long term scientific impact"

Connected through hyperedge HE-5 (induced by source paper "predicting publication productivity for researchers a piecewise poisson model"):
  with members:
    - "predicting citation counts based on deep neural network learning techniques"
    - "can scientific impact be predicted"
    - "accuracy of simple initials based methods for author name disambiguation"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"

Connected through hyperedge HE-6 (induced by source paper "revisiting the scientometric conceptualization of impact and its measurement"):
  with members:
    - "core elements in the process of citing publications conceptual overview of the literature"
    - "a farewell to the mncs and like size independent indicators"
    - "refrain from adopting the combination of citation and journal metrics to grade publications as used in the italian national research assessment exercise vqr 2011 2014"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "citations indicators of quality the impact fallacy"
    - "a review of theory and practice in scientometrics"
    - "predicting the long term citation impact of recent publications"
    - "tweets vs mendeley readers how do these two social media metrics differ"

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)