Submissions
Submission Preparation Checklist
- The submission has not been previously published, nor is it before another journal for consideration; a preprint posted to arXiv or an institutional repository is not considered prior publication.
- The manuscript is prepared using the official JCoSML template (Word or LaTeX), and the page geometry and type sizes have not been altered.
- References are numbered in order of first citation and include DOIs where available.
- A similarity report from Turnitin or iThenticate is uploaded as a supplementary file, with an overall index below 15%.
- Code and data supporting the article are deposited in a repository with a persistent identifier, or a reason for withholding them is stated in the manuscript.
- All named authors have approved the submission, and all competing interests and funding sources are disclosed.
- Any use of generative AI in preparing the manuscript is disclosed in the manuscript.
Research Articles
Original research articles reporting new methods, analyses, or computational results within the scope of the journal. Submissions to this section are peer-reviewed by at least two independent reviewers under single-anonymised review. Typical length is 15 to 30 pages in the JCoSML template, excluding references and appendices.
Privacy Statement
The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.
Data controller. The data controller is Assoc. Prof. Dr. Salih Berkan Aydemir, publisher of the Journal of Computational Optimization and Scientific Machine Learning, Amasya, Türkiye. Enquiries about personal data may be addressed to admin.jcosml@gmail.com.
What we collect. Registration requires a name, an email address, and an affiliation; authors, reviewers, and editors may additionally provide an ORCID identifier, a postal address, a biography, and areas of expertise. The system also records submissions, correspondence, review reports, and editorial decisions, together with technical log data such as IP address, browser type, and access times.
Why we collect it and on what basis. Personal data are processed in order to operate the peer-review and publication process, to communicate with authors, reviewers, and editors, to attribute authorship, to register articles with Crossref and make metadata available to indexing services, and to preserve the scholarly record. The legal basis is the performance of the publication process requested by the data subject and the legitimate interest of the journal in maintaining an accurate and permanent record of publication.
What becomes public. For published articles, the names, affiliations, ORCID identifiers, and corresponding-author email addresses of the authors appear in the article and in its metadata, which are deposited with Crossref and harvested by indexing services. This is inherent in scholarly publication and cannot be reversed once an article is published. No other registration data are made public.
Confidentiality of peer review. The journal operates single-anonymised review: reviewer identities are not disclosed to authors. Review reports are not published and are not shared beyond the editorial team. Submitted manuscripts are confidential documents and are not shared with third parties, uploaded to external services, or used for any purpose other than assessment.
Retention. Registration accounts and submission records are retained for as long as the journal operates, since they form part of the record of publication. Users may request the deletion of an account that is not linked to a published article. Data associated with published articles are retained permanently.
Sharing. Personal data are not sold, rented, or transferred for commercial purposes. Data are shared only with service providers necessary to operate the journal — the hosting platform, Crossref for DOI registration, and preservation and indexing services — and only to the extent required for those functions.