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 "subsumptive reflection in snomed ct a large description logic based terminology for diagnosis"):
  Abstract: Description logic (DL) based biomedical terminology (SNOMED CT) is used routinely in medical practice. However, diagnostic inference using such terminology is precluded by its complexity. Here we propose a model that simplifies these inferential components. We propose three concepts that classify clinical features and examined their effect on inference using SNOMED CT. We used PAIRS (Physician Assistant Artificial Intelligence Reference System) database (1964 findings for 485 disorders, 18 397 disease feature links) for our analysis. We also use a 50-million medical word corpus for estimating the vectors of disease-feature links. Our major results are 10% of finding-disorder links are concomitant in both assertion and negation where as 90% are either concomitant in assertion or negation. Logical implications of PAIRS data on SNOMED CT include 70% of the links do not share any common system while 18% share organ and 12% share both system and organ. Applications of these principles for inference are discussed and suggestions are made for deriving a diagnostic process using SNOMED CT. Limitations of these processes and suggestions for improvements are also discussed.

Includes members:
  Member "efficient estimation of word representations in vector space":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on contextual embeddings")
  Member "variational probabilistic inference and the qmr dt network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the accuracy vs coverage trade off in patient facing diagnosis models")

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.AI(Artificial Intelligence)