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: "on tit for tat franceschini and maisano versus anvur regarding the italian research assessment exercise vqr 2011 2014"
  Abstract: The response by Benedetto, Checchi, Graziosi & Malgarini (2017) (hereafter "BCG&M"), past and current members of the Italian Agency for Evaluation of University and Research Systems (ANVUR), to Franceschini and Maisano's ("F&M") article (2017), inevitably draws us into the debate. BCG&M in fact complain "that almost all criticisms to the evaluation procedures adopted in the two Italian research assessments VQR 2004-2010 and 2011-2014 limit themselves to criticize the procedures without proposing anything new and more apt to the scope". Since it is us who raised most criticisms in the literature, we welcome this opportunity to retrace our vainly "constructive" recommendations, made with the hope of contributing to assessments of the Italian research system more in line with the state of the art in scientometrics. We see it as equally interesting to confront the problem of the failure of knowledge transfer from R&D (scholars) to engineering and production (ANVUR's practitioners) in the Italian VQRs. We will provide a few notes to help the reader understand the context for this failure. We hope that these, together with our more specific comments, will also assist in communicating the reasons for the level of scientometric competence expressed in BCG&M's heated response to F&M's criticism.

Connected through hyperedge HE-1 (induced by source paper "when research assessment exercises leave room for opportunistic behavior by the subjects under evaluation"):
  with members:
    - "peer review versus bibliometrics which method better predicts the scholarly impact of publications"
    - "diversification versus specialization in scientific research which strategy pays off"
    - "bibliometric evaluation of research performance where do we stand"
    - "do they agree bibliometric evaluation versus informed peer review in the italian research assessment exercise"
    - "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"
    - "the vqr italy s second national research assessment methodological failures and ranking distortions"
    - "the determinants of academic career advancement evidence from italy"
    - "inefficiency in selecting products for submission to national research assessment exercises"

Connected through hyperedge HE-2 (induced by source paper "errors and secret data in the italian research assessment exercise a comment to a reply"):
  with members:
    - "do they agree bibliometric evaluation versus informed peer review in the italian research assessment exercise"
    - "the vqr italy s second national research assessment methodological failures and ranking distortions"
    - "national peer review research assessment exercises for the hard sciences can be a complete waste of money the italian case"

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)