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: "assessing national strengths and weaknesses in research fields"
  Abstract: National policies aimed at fostering the effectiveness of scientific systems should be based on reliable strategic analysis identifying strengths and weaknesses at field level. Approaches and indicators thus far proposed in the literature have not been completely satisfactory, since they fail to distinguish the effect of the size of production factors from that of their quality, particularly the quality of labor. The current work proposes an innovative “input-oriented” approach, which permits: (i) estimation of national research performance in a field and comparison to that of other nations, independent of the size of their respective research staffs; and, for fields of comparable intensity of publication, (ii) identification of the strong and weak research fields within a national research system on the basis of international comparison. In reference to the second objective, the proposed approach is applied to the Italian case, through the analysis of the 2006–2010 scientific production of the Italian academic system, in the 200 research fields where bibliometric analysis is meaningful.

Connected through hyperedge HE-1 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case"):
  with members:
    - "the impact of unproductive and top researchers on overall university research performance"
    - "revisiting the scientometric conceptualization of impact and its measurement"
    - "gender bias in academic recruitment"
    - "the determinants of academic career advancement evidence from italy"
    - "how do you define and measure research productivity"
    - "the spin off of elite universities in non competitive undifferentiated higher education systems an empirical simulation in italy"
    - "career advancement and scientific performance in universities"
    - "individual research performance a proposal for comparing apples to oranges"

Connected through hyperedge HE-2 (induced by source paper "the determinants of academic career advancement evidence from italy"):
  with members:
    - "the impact of unproductive and top researchers on overall university research performance"
    - "relatives in the same university faculty nepotism or merit"
    - "how do you define and measure research productivity"
    - "career advancement and scientific performance in universities"
    - "individual research performance a proposal for comparing apples to oranges"
    - "the importance of accounting for the number of co authors and their order when assessing research performance at the individual level in the life sciences"
    - "what is the appropriate length of the publication period over which to assess research performance"
    - "the dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems"

Connected through hyperedge HE-3 (induced by source paper "the collaboration behaviors of scientists in italy a field level analysis"):
  with members:
    - "gender differences in research collaboration"
    - "identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "the dangers of performance based research funding in non competitive higher education systems"
    - "the relationship between scientists research performance and the degree of internationalization of their research"
    - "university industry collaboration in italy a bibliometric examination"
    - "research collaboration and productivity is there correlation"

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)