ArticleEcology and evolution2023
Supervised versus unsupervised approaches to classification of accelerometry data.
Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Practical guidelines for validation of supervised machine learning models in accelerometer-based animal behaviour classification.The Journal of animal ecology · 2025Pooled it
- A Novel Multidisciplinary Approach for Reptile Movement and Behavior Analysis.Integrative zoology · 2026Article
- Six decades of animal accelerometry: trends, applications, and future directions.Movement ecology · 2026Review
- Review
- DISSeCT: An unsupervised framework for high-resolution mapping of rodent behavior using inertial sensors.PLoS biology · 2025Article
- Circadian activity predicts breeding phenology in the Asian burying beetleRoyal Society open science · 2025Article
- Identification and trajectory of multimorbidity patterns among older people in China: a longitudinal study based on the China health and retirement longitudinal study 2011-2020 data.Frontiers in public health · 2025Article
- A benchmark for computational analysis of animal behavior, using animal-borne tags.Movement ecology · 2024Article
- Article
- Supervised versus unsupervised approaches to classification of accelerometry data.Ecology and evolution · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised (
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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.