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 "how do you define and measure research productivity"):
  Abstract: Productivity is the quintessential indicator of efficiency in any production system. It seems it has become a norm in bibliometrics to define research productivity as the number of publications per researcher, distinguishing it from impact. In this work we operationalize the economic concept of productivity for the specific context of research activity and show the limits of the commonly accepted definition. We propose then a measurable form of research productivity through the indicator "Fractional Scientific Strength (FSS)", in keeping with the microeconomic theory of production. We present the methodology for measure of FSS at various levels of analysis: individual, field, discipline, department, institution, region and nation. Finally, we compare the ranking lists of Italian universities by the two definitions of research productivity.

Includes members:
  Member "measuring science irresistible temptations easy shortcuts and dangerous consequences":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the collaboration behavior of top scientists")
  Member "a sensitivity analysis of researchers productivity rankings to the time of citation observation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a scientometric evaluation of 50 greek science and engineering university departments using google scholar")
  Member "measuring institutional research productivity for the life sciences the importance of accounting for the order of authors in the byline":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on tit for tat franceschini and maisano versus anvur regarding the italian research assessment exercise vqr 2011 2014")
  Member "individual research performance a proposal for comparing apples to oranges":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "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":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case")
  Member "what is the appropriate length of the publication period over which to assess research performance":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "the leiden ranking 2011 2012 data collection indicators and interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "revisiting size effects in higher education research productivity":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")

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)