ReviewPatterns (New York, N.Y.)2021
Animal behavior and animal personality from a non-human perspective: Getting help from the machine.
Review in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Integrating Lab- and Field-Based Approaches to Decipher Individuals' Response to Anthropogenic Change.Ecology letters · 2026Article
- Personality Traits of the Territorial Crustacean Chinese Mitten Crab (Animals : an open access journal from MDPI · 2025Article
- Long-term tracking of social structure in groups of rats.Scientific reports · 2024Article
- Neurobiology and systems biology of stress resilience.Physiological reviews · 2024Review
- Observation of Agonistic Behavior in Pacific White Shrimp (Animals : an open access journal from MDPI · 2024Article
- Digitally-enhanced dog behavioral testing.Scientific reports · 2023Article
- Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets.International journal of molecular sciences · 2022Review
- Clustering for Automated Exploratory Pattern Discovery in Animal Behavioral Data.Frontiers in veterinary science · 2022Article
- Unraveling hidden interactions in complex systems with deep learning.Scientific reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We can now track the position of every fly's leg or immerse a tiny fish inside a virtual world by monitoring its gaze in real time. Yet capturing animals' posture or gaze is not like understanding their behavior. Instead, behaviors are still often interpreted by human observers in an anthropomorphic manner. Even newer tools that automatically classify behaviors rely on human observers for the choice of behaviors. In this perspective, we suggest a roadmap toward a "human-free" interpretation of behavior. We present several recent advances, including our recent work on animal personalities. Personality both underlies behavioral differences among individuals and is consistent over time. A mathematical formulation of this idea has allowed us to measure mouse traits objectively, map behaviors across species (humans included), and explore the biological basis of behavior. Our goal is to enable "machine translation" of raw movement data into intelligible human concepts en route to improving our understanding of animals and people.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.