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 "is saki delicious the food perception gap on instagram and its relation to health"):
  Abstract: Food is an integral part of our life and what and how much we eat crucially affects our health. Our food choices largely depend on how we perceive certain characteristics of food, such as whether it is healthy, delicious or if it qualifies as a salad. But these perceptions differ from person to person and one person's "single lettuce leaf" might be another person's "side salad". Studying how food is perceived in relation to what it actually is typically involves a laboratory setup. Here we propose to use recent advances in image recognition to tackle this problem. Concretely, we use data for 1.9 million images from Instagram from the US to look at systematic differences in how a machine would objectively label an image compared to how a human subjectively does. We show that this difference, which we call the "perception gap", relates to a number of health outcomes observed at the county level. To the best of our knowledge, this is the first time that image recognition is being used to study the "misalignment" of how people describe food images vs. what they actually depict.

Includes members:
  Member "fetishizing food in digital age foodporn around the world":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "everything about you a multimodal approach towards friendship inference in online social networks")
  Member "towards bottom up analysis of social food":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scraping social media photos posted in kenya and elsewhere to detect and analyze food types")
  Member "deepfood deep learning based food image recognition for computer aided dietary assessment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi task self supervised learning for human activity detection")
  Member "crowdsourcing health labels inferring body weight from profile pictures":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "large scale and high resolution analysis of food purchases and health outcomes")
  Member "deep image scaling up image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stochastic optimization of plain convolutional neural networks with simple methods")
  Member "deep residual learning for image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "social media image analysis for public health":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "what twitter profile and posted images reveal about depression and anxiety")
  Member "foodporn obesity patterns in culinary interactions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "foodai food image recognition via deep learning for smart food logging")

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)