Evidence map›Paper›PMID 35342615›Full record

ArticleEcology and evolution2022

BOVIDS: A deep learning-based software package for pose estimation to evaluate nightly behavior and its application to common elands (

Jennifer Gübert, Max Hahn-Klimroth, Paul W Dierkes

Abstract read
In one paragraph

Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Diurnal and Nocturnal Behaviour of Cheetahs (Animals : an open access journal from MDPI · 2022
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jennifer GübertFaculty of Biological Sciences Bioscience Education and Zoo Biology Goethe University Frankfurt Germany.ORCID https://orcid.org/0000-0002-1224-4817
Max Hahn-KlimrothFaculty of Computer Science TU Dortmund University Dortmund Germany.ORCID https://orcid.org/0000-0002-3995-419X
Paul W DierkesFaculty of Biological Sciences Bioscience Education and Zoo Biology Goethe University Frankfurt Germany.ORCID https://orcid.org/0000-0002-6046-6406

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Only a few studies on the nocturnal behavior of African ungulates exist so far, with mostly small sample sizes. For a comprehensive understanding of nocturnal behavior, the data basis needs to be expanded. Results obtained by observing zoo animals can provide clues for the study of wild animals and furthermore contribute to a better understanding of animal welfare and better husbandry conditions in zoos. The current contribution reduces the lack of data in two ways. First, we present a stand-alone open-source software package based on deep learning techniques, named

Indexed as

deep learningnightly behaviorposture estimationREM sleepTragelaphus oryxvideo action classification

Identifiers

PMID35342615
PMCPMC8928879

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.