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• W3203984237 abstract "One of the goals in animal socioecology is to understand the functions and dynamics of group living. While observations of free-ranging animals are a crucial source of information, an experimental investigation that manipulates the size or composition, or both, of animal groups in captivity can also bring complementary contributions to the research inquiry. When paired with an automatic data collection by biologging technology, experimental studies on captive animals also allow for big data analyses based on recent machine learning techniques. As an initial exploration of this research paradigm, the present study inquired to what extent isolation of captive Japanese macaques (Macaca fuscata) changed their movement patterns. Using three-dimensional location trajectories of the macaques that were systematically collected via Bluetooth Low Energy beacons and a deep neural network, we estimated the identifiability of whether a macaque was behaving in isolation or in group. We found that the neural network identified the isolation vs. in-group conditions with more than 90% accuracy from a five-minute location trajectory, suggesting that the isolation caused notable changes from the canonical group-living behaviors. In addition, the isolation made each individual more identifiable from one another based on their location trajectories." @default.
• W3203984237 created "2021-10-11" @default.
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• W3203984237 date "2021-12-01" @default.
• W3203984237 modified "2023-10-15" @default.
• W3203984237 title "Effects of short-term isolation on social animals' behavior: An experimental case study of Japanese macaque" @default.
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• W3203984237 doi "https://doi.org/10.1016/j.ecoinf.2021.101435" @default.
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