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: "better than their reputation on the reliability of relevance assessments with students"
  Abstract: During the last three years we conducted several information retrieval evaluation series with more than 180 LIS students who made relevance assessments on the outcomes of three specific retrieval services. In this study we do not focus on the retrieval performance of our system but on the relevance assessments and the inter-assessor reliability. To quantify the agreement we apply Fleiss' Kappa and Krippendorff's Alpha. When we compare these two statistical measures on average Kappa values were 0.37 and Alpha values 0.15. We use the two agreement measures to drop too unreliable assessments from our data set. When computing the differences between the unfiltered and the filtered data set we see a root mean square error between 0.02 and 0.12. We see this as a clear indicator that disagreement affects the reliability of retrieval evaluations. We suggest not to work with unfiltered results or to clearly document the disagreement rates.

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)