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 "large publishing consortia produce higher citation impact research but co author contributions are hard to evaluate"):
  Abstract: This paper introduces a simple agglomerative clustering method to identify large publishing consortia with at least 20 authors and 80% shared authorship between articles. Based on Scopus journal articles 1996-2018, under these criteria, nearly all (88%) of the large consortia published research with citation impact above the world average, with the exceptions being mainly the newer consortia for which average citation counts are unreliable. On average, consortium research had almost double (1.95) the world average citation impact on the log scale used (Mean Normalised Log Citation Score). At least partial alphabetical author ordering was the norm in most consortia. The 250 largest consortia were for nuclear physics and astronomy around expensive equipment, and for predominantly health-related issues in genomics, medicine, public health, microbiology and neuropsychology. For the health-related issues, except for the first and last few authors, authorship seem to primary indicate contributions to the shared project infrastructure necessary to gather the raw data. It is impossible for research evaluators to identify the contributions of individual authors in the huge alphabetical consortia of physics and astronomy, and problematic for the middle and end authors of health-related consortia. For small scale evaluations, authorship contribution statements could be used, when available.

Includes members:
  Member "granularity of algorithmically constructed publication level classifications of research publications identification of topics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "the accuracy of confidence intervals for field normalised indicators":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "female citation impact superiority 1996 2018 in six out of seven english speaking nations")
  Member "three practical field normalised alternative indicator formulae for research evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the demise of single authored publications in computer science a citation network analysis")
  Member "is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration an analysis based on data from f1000prime and normalized citation scores":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "academic collaboration rates and citation associations vary substantially between countries and fields")
  Member "an empirical analysis of the use of alphabetical authorship in scientific publishing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "female citation impact superiority 1996 2018 in six out of seven english speaking nations")
  Member "a unified approach to mapping and clustering of bibliometric networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "visualizing the context of citations referencing papers published by eugene garfield a new type of keyword co occurrence analysis")

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)