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J535D165 authored Jan 19, 2023
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cff-version: 1.2.0
title: >-
ASReview Makita: a workflow generator for simulation
studies using the command line interface of ASReview LAB
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Jelle
family-names: Teijema
email: [email protected]
affiliation: Utrecht University
orcid: 'https://orcid.org/0000-0001-9282-4311'
- given-names: Rens
family-names: Van de Schoot
email: [email protected]
affiliation: Utrecht University
orcid: 'https://orcid.org/0000-0001-7736-2091'
- given-names: Gerbrich
family-names: Ferdinands
orcid: 'https://orcid.org/0000-0002-4998-3293'
- given-names: Peter
family-names: Lombaers
affiliation: IDFuse
orcid: 'https://orcid.org/0000-0002-8780-9376'
- given-names: Jonathan
family-names: De Bruin
email: [email protected]
affiliation: Utrecht University
orcid: 'https://orcid.org/0000-0002-4297-0502'
repository-code: 'https://github.com/asreview/asreview-makita'
url: 'https://asreview.ai/'
repository-artifact: 'https://pypi.org/project/asreview-makita/'
abstract: >-
ASReviews' Makita (MAKe IT Automatic) is a workflow
generator for simulation studies using the command line
interface of ASReview LAB. Makita can be used to
effortlessly generate the framework and code for your
simulation study.
A simulation involves mimicking the screening process for
a systematic review of a human in interaction with an
Active learning model (i.e., a combination of a feature
extractor, classifier, balancing method, and query
strategy). The simulation reenacts the screening process
as if a researcher were using active learning. The
performance of one or multiple model(s) can then be
measured by performance metrics, such as the Work Saved
over Sampling, recall at a given point in the screening
process, or the average time to discover a relevant
record.
Using Makita templates, different study structures can be
generated to fit the needs of your very own study. If your
study requires a unique template, you can create a new one
and use it instead.
keywords:
- systematic-review
- simulation
- asreview
- machine-learning
- active-learning
- template
license: MIT

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