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: "open access scientometrics and the uk research assessment exercise"
  Abstract: Scientometric predictors of research performance need to be validated by showing that they have a high correlation with the external criterion they are trying to predict. The UK Research Assessment Exercise (RAE), together with the growing movement toward making the full-texts of research articles freely available on the web -- offer a unique opportunity to test and validate a wealth of old and new scientometric predictors, through multiple regression analysis: Publications, journal impact factors, citations, co-citations, citation chronometrics (age, growth, latency to peak, decay rate), hub/authority scores, h-index, prior funding, student counts, co-authorship scores, endogamy/exogamy, textual proximity, download/co-downloads and their chronometrics, etc. can all be tested and validated jointly, discipline by discipline, against their RAE panel rankings in the forthcoming parallel panel-based and metric RAE in 2008. The weights of each predictor can be calibrated to maximize the joint correlation with the rankings. Open Access Scientometrics will provide powerful new means of navigating, evaluating, predicting and analyzing the growing Open Access database, as well as powerful incentives for making it grow faster. ~

Connected through hyperedge HE-1 (induced by source paper "criteria for assessing grant applications a systematic review"):
  with members:
    - "latent human traits in the language of social media an open vocabulary approach"

Connected through hyperedge HE-2 (induced by source paper "research assessment by percentile based double rank analysis"):
  with members:
    - "citation score normalized by cited references csncr the introduction of a new citation impact indicator"
    - "efficiency of research performance and the glass researcher"
    - "identifying potential breakthrough publications using refined citation analyses three related explorative approaches"
    - "a review of the literature on citation impact indicators"
    - "regression for citation data an evaluation of different methods"
    - "how are excellent highly cited papers defined in bibliometrics a quantitative analysis of the literature"
    - "distributions for cited articles from individual subjects and years"
    - "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers"

Connected through hyperedge HE-3 (induced by source paper "self selected or mandated open access increases citation impact for higher quality research"):
  with members:
    - "use of astronomical literature a report on usage patterns"
    - "a principal component analysis of 39 scientific impact measures"
    - "offloading cognition onto cognitive technology"
    - "does the arxiv lead to higher citations and reduced publisher downloads for mathematics articles"
    - "open access does not increase citations for research articles from the astrophysical journal"
    - "effect of e printing on citation rates in astronomy and physics"
    - "ten year cross disciplinary comparison of the growth of open access and how it increases research citation impact"
    - "the effect of use and access on citations"

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.IR(Information Retrieval)