First CiteScore Released: 8.7
We are delighted to announce that the CiteScore 2023 for the Journal of Artificial Intelligence and Technology is 8.7, which ranks it 77 out of 350 journals in the Artificial Intelligence category.
The Journal of Artificial Intelligence and Technology is a formally peer-reviewed journal. All publications in the journal undergo a double-blind peer review process where reviewers don't know the identity of the author and vice versa.
Review Decisions
Editor-in-Chief is permitted to take the following actions in the stage of initial review:
Editor-in-Chief reviews the comments made by reviewers and is allowed to make following decisions:
After submitting revisions to the journal, authors are required to submit a rebuttal to the reviewer's comments. Authors should fully address all reviewer comments; if an author does not agree with the change requested, the author should explain the reason in the rebuttal. If the Editor-in-Chief feels that reviewer comments have been ignored, the Editor-in-Chief may reject the revised article.
The final decision on whether a submission is accepted for publication is made by the Editor-in-Chief, since the Editor-in-Chief is responsible for the content of the entire journal, including all special issues.
Reuse of words must be kept to a minimum, credited, or quoted in the text, and all sources must be cited when they are used.
The Journal of Artificial Intelligence and Technology uses the Similarity Check service provided by Crossref and powered by iThenticate to provide editors with a user-friendly tool to help detect plagiarism. Results returned by the software may be used as a criterion for the analysis of the manuscript by the editorial board and may eventually result in a rejection due to plagiarism and/or duplicate publication.
The CrossRef Similarity Check uses iThenticate originality detection software to identify text similarities which may indicate plagiarism. It does this by comparing manuscripts with both a web repository and the CrossRef database.
Recommended reading
· CrossCheck Plagiarism Screening: Understanding the Similarity Score