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 "tackling climate change with machine learning"):
  Abstract: Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.

Includes members:
  Member "pvnet a lrcn architecture for spatio temporal photovoltaic powerforecasting from numerical weather prediction":
    also connected through other hyperedges:
      (none)
  Member "truck traffic monitoring with satellite images":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the morality of artificial intelligence")
  Member "artificial intelligence for social good":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "acceptable planning influencing individual behavior to reduce transportation energy expenditure of a city")
  Member "efficient multi objective optimization through population based parallel surrogate search":
    also connected through other hyperedges:
      (none)
  Member "agriculture commodity arrival prediction using remote sensing data insights and beyond":
    also connected through other hyperedges:
      (none)
  Member "decentralized flood forecasting using deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "realistic river image synthesis using deep generative adversarial networks")
  Member "machine vision for natural gas methane emissions detection using an infrared camera":
    also connected through other hyperedges:
      (none)
  Member "learning optimal solutions for extremely fast ac optimal power flow":
    also connected through other hyperedges:
      (none)

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.CY(Computers and Society)