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: "replication studies considered harmful"
  Abstract: Context: There is growing interest in establishing software engineering as an evidence-based discipline. To that end, replication is often used to gain confidence in empirical findings, as opposed to reproduction where the goal is showing the correctness, or validity of the published results.   Objective: To consider what is required for a replication study to confirm the original experiment and apply this understanding in software engineering.   Method: Simulation is used to demonstrate why the prediction interval for confirmation can be surprisingly wide. This analysis is applied to three recent replications.   Results: It is shown that because the prediction intervals are wide, almost all replications are confirmatory, so in that sense there is no `replication crisis', however, the contributions to knowledge are negligible.   Conclusion: Replicating empirical software engineering experiments, particularly if they are under-powered or under-reported, is a waste of scientific resources. By contrast, meta-analysis is strongly advocated so that all relevant experiments are combined to estimate the population effect.

Connected through hyperedge HE-1 (induced by source paper "cross dataset design discussion mining"):
  with members:
    - "on the feasibility of transfer learning code smells using deep learning"
    - "methodology matters how we study socio technical aspects in software engineering"
    - "sotorrent reconstructing and analyzing the evolution of stack overflow posts"
    - "universal language model fine tuning for text classification"
    - "hyperparameter optimization for effort estimation"
    - "evolution of statistical analysis in empirical software engineering research current state and steps forward"
    - "advances in pre training distributed word representations"
    - "rationale in development chat messages an exploratory study"

Connected through hyperedge HE-2 (induced by source paper "interpreting cloud computer vision pain points a mining study of stack overflow"):
  with members:
    - "losing confidence in quality unspoken evolution of computer vision services"
    - "what should i document a preliminary systematic mapping study into api documentation knowledge"

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.SE(Software Engineering)