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: "quantifying long term scientific impact"
  Abstract: The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in citation patterns? Here, we derive a mechanistic model for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern. The observed patterns not only help us uncover basic mechanisms that govern scientific impact but also offer reliable measures of influence that may have potential policy implications.

Connected through hyperedge HE-1 (induced by source paper "how well does i3 perform for impact measurement compared to other bibliometric indicators the convergent validity of several field normalized indicators"):
  with members:
    - "which differences can be expected when two universities in the leiden ranking are compared some benchmarks for institutional research evaluations"
    - "creativity in science and the link to cited references is the creative potential of papers reflected in their cited references"
    - "revisiting relative indicators and provisional truths"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "citation score normalized by cited references csncr the introduction of a new citation impact indicator"
    - "a review of theory and practice in scientometrics"
    - "a review of the literature on citation impact indicators"
    - "how are excellent highly cited papers defined in bibliometrics a quantitative analysis of the literature"

Connected through hyperedge HE-2 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching"):
  with members:
    - "the preeminence of ethnic diversity in scientific collaboration"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "predicting citation counts based on deep neural network learning techniques"):
  with members:
    - "can scientific impact be predicted"
    - "deep residual learning for image recognition"
    - "a review of the characteristics of 108 author level bibliometric indicators"
    - "very deep convolutional networks for large scale image recognition"
    - "bibliometric indicators of young authors in astrophysics can later stars be predicted"
    - "neural machine translation by jointly learning to align and translate"
    - "will this paper increase your h index scientific impact prediction"
    - "deep visual semantic alignments for generating image descriptions"

Connected through hyperedge HE-4 (induced by source paper "follow the leader documents on the leading edge of semantic change get more citations"):
  with members:
    - "survey of computational approaches to diachronic conceptual change"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "dynamic word embeddings for evolving semantic discovery"
    - "diachronic word embeddings and semantic shifts a survey"
    - "bounded rationality in scholarly knowledge discovery"
    - "cultural shift or linguistic drift comparing two computational measures of semantic change"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "statistically significant detection of linguistic change"

Connected through hyperedge HE-5 (induced by source paper "link prediction via graph attention network"):
  with members:
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "fastgcn fast learning with graph convolutional networks via importance sampling"
    - "exploring small world network with an elite clique bringing embeddedness theory into the dynamic evolution of a venture capital network"
    - "struc2vec learning node representations from structural identity"
    - "node2vec scalable feature learning for networks"
    - "semi supervised classification with graph convolutional networks"
    - "convolutional neural networks on graphs with fast localized spectral filtering"
    - "a convolutional encoder model for neural machine translation"

Connected through hyperedge HE-6 (induced by source paper "modelling structure and predicting dynamics of discussion threads in online boards"):
  with members:
    - "tideh time dependent hawkes process for predicting retweet dynamics"
    - "all who wander on the prevalence and characteristics of multi community engagement"
    - "local variation of hashtag spike trains and popularity in twitter"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "modeling and predicting popularity dynamics via reinforced poisson processes"
    - "can cascades be predicted"
    - "a likelihood based framework for the analysis of discussion threads"
    - "from user comments to on line conversations"

Connected through hyperedge HE-7 (induced by source paper "predicting publication long term impact through a combination of early citations and journal impact factor"):
  with members:
    - "revisiting the scientometric conceptualization of impact and its measurement"
    - "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"
    - "predicting the long term citation impact of recent publications"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"
    - "revisiting the scaling of citations for research assessment"
    - "assessing the varying level of impact measurement accuracy as a function of the citation window length"
    - "citations versus journal impact factor as proxy of quality could the latter ever be preferable"

Connected through hyperedge HE-8 (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"
    - "predicting publication long term impact through a combination of early citations and journal impact factor"
    - "can scientific impact be predicted"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"

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)