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 "evaluating research and researchers by the journal impact factor is it better than coin flipping"):
  Abstract: Abstract   The journal impact factor (JIF) is the average of the number of citations of the papers published in a journal, calculated according to a specific formula; it is extensively used for the evaluation of research and researchers. The method assumes that all papers in a journal have the same scientific merit, which is measured by the JIF of the publishing journal. This implies that the number of citations measures scientific merits but the JIF does not evaluate each individual paper by its own number of citations. Therefore, in the comparative evaluation of two papers, the use of the JIF implies a risk of failure, which occurs when a paper in the journal with the lower JIF is compared to another with fewer citations in the journal with the higher JIF. To quantify this risk of failure, this study calculates the failure probabilities, taking advantage of the lognormal distribution of citations. In two journals whose JIFs are ten-fold different, the failure probability is low. However, in most cases when two papers are compared, the JIFs of the journals are not so different. Then, the failure probability can be close to 0.5, which is equivalent to evaluating by coin flipping.

Includes members:
  Member "systematic analysis of agreement between metrics and peer review in the uk ref":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "probability and expected frequency of breakthroughs a robust method of research assessment based on the double rank property of citation distributions":
    also connected through other hyperedges:
      (none)
  Member "core elements in the process of citing publications conceptual overview of the literature":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "citation recommendation approaches and datasets")
  Member "use of the journal impact factor for assessing individual articles need not be wrong":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "inferring the causal effect of journals on citations")
  Member "can the journal impact factor be used as a criterion for the selection of junior researchers a large scale empirical study based on researcherid data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "heuristics as conceptual lens for understanding and studying the usage of bibliometrics in research evaluation")
  Member "citation success index an intuitive pair wise journal comparison metric":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "comparing the impact of subfields in scientific journals")
  Member "citation count distributions for large monodisciplinary journals":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the heterogeneous distributions in paper citations")
  Member "citations indicators of quality the impact fallacy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")

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)