ArticleMarine biology2018
Development and application of a machine learning algorithm for classification of elasmobranch behaviour from accelerometry data.
Article in Marine biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed.
- Six decades of animal accelerometry: trends, applications, and future directions.Movement ecology · 2026Review
- Open wide: Identifying North Atlantic right whale feeding behaviour using camera-validated kinematic data and machine learning.PloS one · 2026Article
- Review
- Use of accelerometry to measure the dynamics of activity patterns of Atlantic bluefin tuna after tagging and release.Movement ecology · 2025Article
- Abiotic drivers of the space use and activity of gray reef sharks Carcharhinus amblyrhynchos in a dynamic tidal environment.Journal of fish biology · 2025Article
- A benchmark for computational analysis of animal behavior, using animal-borne tags.Movement ecology · 2024Article
- Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample duration.Ecology and evolution · 2024Article
- Review
- Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data.Movement ecology · 2022Article
- Short-term behavioural responses of Atlantic bluefin tuna to catch-and-release fishing.Conservation physiology · 2022Article
- Forensic odontology: Assessing bite wounds to determine the role of teeth in piscivorous fishes.Integrative organismal biology (Oxford, England) · 2022Article
- Classifying Goliath Grouper (Sensors (Basel, Switzerland) · 2021Article
- Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data.Journal of animal science · 2021Article
- Using Machine Learning for Remote Behaviour Classification-Verifying Acceleration Data to Infer Feeding Events in Free-Ranging Cheetahs.Sensors (Basel, Switzerland) · 2021Article
- Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2021Article
- Using tri-axial accelerometer loggers to identify spawning behaviours of large pelagic fish.Movement ecology · 2021Article
- Behaviour Classification on Giraffes (Sensors (Basel, Switzerland) · 2021Article
- Assessment of Machine Learning Models to Identify Port Jackson Shark Behaviours Using Tri-Axial Accelerometers.Sensors (Basel, Switzerland) · 2020Article
- Behavioural inference from signal processing using animal-borne multi-sensor loggers: a novel solution to extend the knowledge of sea turtle ecology.Royal Society open science · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Discerning behaviours of free-ranging animals allows for quantification of their activity budget, providing important insight into ecology. Over recent years, accelerometers have been used to unveil the cryptic lives of animals. The increased ability of accelerometers to store large quantities of high resolution data has prompted a need for automated behavioural classification. We assessed the performance of several machine learning (ML) classifiers to discern five behaviours performed by accelerometer-equipped juvenile lemon sharks (
Identifiers
What OpenQuestion holds
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.