CITATION.cff

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: ASReview LAB developers
    affiliation: Utrecht University
    email: asreview@uu.nl
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