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: "testing the trade off between productivity and quality in research activities"
  Abstract: In recent years there has been an increasingly pressing need for the evaluation of results from public sector research activity, particularly to permit the efficient allocation of ever scarcer resources. Many of the studies and evaluation exercises that have been conducted at the national and international level emphasize the quality dimension of research output, while neglecting that of productivity. This work is intended to test for the possible existence of correlation between quantity and quality of scientific production and determine whether the most productive researchers are also those that achieve results that are qualitatively better than those of their colleagues. The analysis proposed refers to the entire Italian university system and is based on the observation of production in the hard sciences by above 26,000 researchers in the period 2001 to 2005. The results show that the output of more productive researchers is superior in quality than that of less productive researchers. The relation between productivity and quality results as largely insensitive to the types of indicators or the test methods applied and also seems to differ little among the various disciplines examined.

Connected through hyperedge HE-1 (induced by source paper "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"):
  with members:
    - "an investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level"
    - "use of the journal impact factor for assessing individual articles need not be wrong"
    - "a farewell to the mncs and like size independent indicators"
    - "a review of the literature on citation impact indicators"
    - "methods for the generation of normalized citation impact scores in bibliometrics which method best reflects the judgements of experts"
    - "what is the effect of country specific characteristics on the research performance of scientific institutions using multi level statistical models to rank and map universities and research focused institutions worldwide"
    - "how to evaluate individual researchers working in the natural and life sciences meaningfully a proposal of methods based on percentiles of citations"
    - "towards a new crown indicator an empirical analysis"

Connected through hyperedge HE-2 (induced by source paper "a comparison of university performance scores and ranks by mncs and fss"):
  with members:
    - "a farewell to the mncs and like size independent indicators"
    - "efficiency of research performance and the glass researcher"
    - "evaluating university research same performance indicator different rankings"
    - "does quantity make a difference the importance of publishing many papers"
    - "ranking research institutions by the number of highly cited articles per scientist"
    - "how do you define and measure research productivity"
    - "measuring institutional research productivity for the life sciences the importance of accounting for the order of authors in the byline"
    - "assessing the accuracy of the h and g indexes for measuring researchers productivity"

Connected through hyperedge HE-3 (induced by source paper "the dispersion of the citation distribution of top scientists publications"):
  with members:
    - "revisiting the scaling of citations for research assessment"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "national scale research performance assessment at the individual level"
    - "the dangers of performance based research funding in non competitive higher education systems"

Connected through hyperedge HE-4 (induced by source paper "how to evaluate individual researchers working in the natural and life sciences meaningfully a proposal of methods based on percentiles of citations"):
  with members:
    - "the leiden ranking 2011 2012 data collection indicators and interpretation"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"
    - "assessing the varying level of impact measurement accuracy as a function of the citation window length"
    - "evaluating research from informed peer review to bibliometrics"
    - "the inconsistency of the h index"
    - "assessing scientific research performance and impact with single indices"

Connected through hyperedge HE-5 (induced by source paper "the field standardized average impact of national research systems compared to world average the case of italy"):
  with members:
    - "measuring science irresistible temptations easy shortcuts and dangerous consequences"
    - "national scale research performance assessment at the individual level"

Connected through hyperedge HE-6 (induced by source paper "national research assessment exercises a measure of the distortion of performance rankings when labor input is treated as uniform"):
  with members:
    - "gender differences in research productivity a bibliometric analysis of the italian academic system"
    - "university industry collaboration in italy a bibliometric examination"
    - "allocative efficiency in public research funding can bibliometrics help"
    - "the measurement of italian universities research productivity by a non parametric bibliometric methodology"

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)