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 "h α an index to quantify an individual s scientific leadership"):
  Abstract: Abstract The $$\alpha$$ α person is the dominant person in a group. We define the $$\alpha$$ α -author of a paper as the author of the paper with the highest h-index among all the coauthors, and an $$\alpha$$ α -paper of a scientist as a paper authored or coauthored by the scientist where he/she is the $$\alpha$$ α -author. For most but not all papers in the literature there is only one $$\alpha$$ α -author. We define the $$h_\alpha$$ h α index of a scientist as the number of papers in the h-core of the scientist (i.e. the set of papers that contribute to the h-index of the scientist) where this scientist is the $$\alpha$$ α -author. We also define the $$h'_\alpha$$ h α ′ index of a scientist as the number of $$\alpha$$ α -papers of this scientist that have $$\ge$$ ≥ $$h'_\alpha$$ h α ′ citations. $$h_\alpha$$ h α and $$h'_\alpha$$ h α ′ contain similar information, while $$h'_\alpha$$ h α ′ is conceptually more appealing it is harder to obtain from existing databases, hence of less current practical interest. We propose that the $$h_\alpha$$ h α and/or $$h'_\alpha$$ h α ′ indices, or other variants discussed in the paper, are useful complements to the h-index of a scientist to quantify his/her scientific achievement, that rectify an inherent drawback of the h-index, its inability to distinguish between authors with different coauthorships patterns. A high h index in conjunction with a high $$h_\alpha /h$$ h α / h ratio is a hallmark of scientific leadership.

Includes members:
  Member "a modification to hirsch index allowing comparisons across different scientific fields":
    also connected through other hyperedges:
      (none)
  Member "assessing the true role of coauthors in the h index measure of an author scientific impact":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "quantitative and qualitative analysis of editor behavior through maybe coercive citations")
  Member "central indexes to the citation distribution a complement to the h index":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "h index and its alternative a review")
  Member "the inconsistency of the h index":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the h index for research assessment simple and popular but shown by mathematical analysis to be inconsistent and misleading")

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)