Evidence map›Paper›PMID 39338701›Full record

ArticleSensors (Basel, Switzerland)2024

The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Dogs (

Cushla Redmond, Michelle Smit, Ina Draganova, Rene Corner-Thomas, David Thomas, Christopher Andrews

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Cushla RedmondSchool of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand.
Michelle SmitSchool of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand.ORCID 0000-0003-0554-5125
Ina DraganovaSchool of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand.ORCID 0000-0002-2131-4012
Rene Corner-ThomasSchool of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand.ORCID 0000-0002-7398-2653
David ThomasSchool of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand.ORCID 0000-0001-7460-9351
Christopher AndrewsSchool of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand.ORCID 0000-0003-3049-1835

Funding

Healthy Pets New Zealand N/A
6 · The paper itself

Abstract

Assessing the behaviour and physical attributes of domesticated dogs is critical for predicting the suitability of animals for companionship or specific roles such as hunting, military or service. Common methods of behavioural assessment can be time consuming, labour-intensive, and subject to bias, making large-scale and rapid implementation challenging. Objective, practical and time effective behaviour measures may be facilitated by remote and automated devices such as accelerometers. This study, therefore, aimed to validate the ActiGraph

Indexed as

AccelerometryBehavior, AnimalMachine LearningAlgorithmsAnimalsDogsFemaleLocomotionMalealgorithmbehaviour classificationoverall activityrandom forest

Identifiers

PMID39338701
PMCPMC11435861

What Socratic 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 Socratic graph.