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: "systems theoretic safety assessment of robotic telesurgical systems"
  Abstract: Robotic telesurgical systems are one of the most complex medical cyber-physical systems on the market, and have been used in over 1.75 million procedures during the last decade. Despite significant improvements in design of robotic surgical systems through the years, there have been ongoing occurrences of safety incidents during procedures that negatively impact patients. This paper presents an approach for systems-theoretic safety assessment of robotic telesurgical systems using software-implemented fault-injection. We used a systemstheoretic hazard analysis technique (STPA) to identify the potential safety hazard scenarios and their contributing causes in RAVEN II robot, an open-source robotic surgical platform. We integrated the robot control software with a softwareimplemented fault-injection engine which measures the resilience of the system to the identified safety hazard scenarios by automatically inserting faults into different parts of the robot control software. Representative hazard scenarios from real robotic surgery incidents reported to the U.S. Food and Drug Administration (FDA) MAUDE database were used to demonstrate the feasibility of the proposed approach for safety-based design of robotic telesurgical systems.

Connected through hyperedge HE-1 (induced by source paper "context aware monitoring in robotic surgery"):
  with members:
    - "adverse events in robotic surgery a retrospective study of 14 years of fda data"
    - "to make a robot secure an experimental analysis of cyber security threats against teleoperated surgical robots"

Connected through hyperedge HE-2 (induced by source paper "experimental resilience assessment of an open source driving agent"):
  with members:
    - "robust physical world attacks on deep learning models"
    - "deepxplore automated whitebox testing of deep learning systems"
    - "learning a driving simulator"
    - "a systematic and semi automatic safety based test case generation approach based on systems theoretic process analysis"
    - "real time detection of lane markers in urban streets"

Connected through hyperedge HE-3 (induced by source paper "towards robotic eye surgery marker free online hand eye calibration using optical coherence tomography images"):
  with members:
    - "automatic tool landmark detection for stereo vision in robot assisted retinal surgery"
    - "similarity registration problems for 2d 3d ultrasound calibration"

Connected through hyperedge HE-4 (induced by source paper "on the safety of machine learning cyber physical systems decision sciences and data products"):
  with members:
    - "adverse events in robotic surgery a retrospective study of 14 years of fda data"
    - "debugging machine learning tasks"
    - "causal falling rule lists"
    - "robust binary hypothesis testing under contaminated likelihoods"
    - "machine learning that matters"
    - "domain adaptation for statistical classifiers"

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.RO(Robotics)