human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "regression for citation data an evaluation of different methods"):
  Abstract: Citations are increasingly used for research evaluations. It is therefore important to identify factors affecting citation scores that are unrelated to scholarly quality or usefulness so that these can be taken into account. Regression is the most powerful statistical technique to identify these factors and hence it is important to identify the best regression strategy for citation data. Citation counts tend to follow a discrete lognormal distribution and, in the absence of alternatives, have been investigated with negative binomial regression. Using simulated discrete lognormal data (continuous lognormal data rounded to the nearest integer) this article shows that a better strategy is to add one to the citations, take their log and then use the general linear (ordinary least squares) model for regression (e.g., multiple linear regression, ANOVA), or to use the generalised linear model without the log. Reasonable results can also be obtained if all the zero citations are discarded, the log is taken of the remaining citation counts and then the general linear model is used, or if the generalised linear model is used with the continuous lognormal distribution. Similar approaches are recommended for altmetric data, if it proves to be lognormally distributed.

Includes members:
  Member "distributions for cited articles from individual subjects and years":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how much research shared on facebook is hidden from public view a comparison of public and private online activity around plos one papers")
  Member "how well developed are altmetrics a cross disciplinary analysis of the presence of alternative metrics in scientific publications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "national peer review research assessment exercises for the hard sciences can be a complete waste of money the italian case":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "how to calculate the practical significance of citation impact differences an empirical example from evaluative institutional bibliometrics using adjusted predictions and marginal effects":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "do altmetrics correlate with the quality of papers a large scale empirical study based on f1000prime data")
  Member "comparison of a citation based indicator and peer review for absolute and specific measures of research group excellence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "systematic analysis of agreement between metrics and peer review in the uk ref")
  Member "national research assessment exercises a comparison of peer review and bibliometrics rankings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "towards a new crown indicator some theoretical considerations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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")
  Member "classification and powerlaws the logarithmic transformation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "categorizing hirsch index variants")

Question: Please tell me which class the source paper 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)