Many venues restrict undisclosed AI; audits keep finding secret AI-written reviews anyway. Our answer is to do openly and accountably what others do secretly: this journal uses AI in review, says so plainly, labels its output, and puts a named human's signature on every decision.
For authors
- You may use AI tools in research, analysis and writing. Used well, they improve papers.
- Disclose the use. The submission form asks how AI was used (assistance, editing, content generation, none); generated content requires a short note on what and where. The disclosure appears in the published article.
- A named human is accountable for every part. AI is never an author and cannot be one: authorship means approving the work and answering for it. Whatever a tool drafted, the listed authors have verified it and own it.
- You are responsible for AI failure modes, above all fabricated references. Every reference in every submission is verified against the scholarly record, and submission requires an explicit attestation that the reference list is real and checked. A fabricated reference is treated as an integrity finding, not a typo (see publication ethics).
For the journal: our own AI use, disclosed
- Submissions are assessed by an agentic AI pipeline under named-human sign-off, described step by step in the peer-review policy. AI use in review is never concealed from authors.
- Our AI use is disclosed at policy level, on this page and in the peer-review policy, rather than as a label stamped on each individual document. The reviewer-panel reports you receive are written by synthetic reviewer personas, not by human referees, and they reach you numbered ("Reviewer 1", "Reviewer 2", "Reviewer 3"): no report is ever presented to you under the name of a referee who does not exist.
- No decision is autonomous. A named human editor reads the assessment record and signs every accept, revision request and rejection. Authors can escalate any AI-influenced decision to an independent human through the appeals procedure.
Confidentiality of your manuscript
- Manuscripts under review are processed through a commercial model API under a data processing agreement with EU standard contractual clauses: submissions are not used to train models and are deleted under contractual retention limits. We never run your manuscript through consumer AI apps.
- The public scope check on the journal home sends the text you paste to the same contracted model API, under the same terms. The pasted text is not stored and not logged: the check keeps metadata only (verdict, text length, token counts and a rate-limit hash that is erased within two days). Paste an abstract, not confidential material.
- Manuscript content is not persisted into the review system's configuration or memory; what is stored is the structured assessment record.
- Sensitive data never touch a cloud model. Datasets handled under the journal's privacy-preserving data service are processed in a controlled environment only. See data & code availability.
Why AI at all
The pipeline is what makes the journal's promise affordable and universal: because assessment is fast, transparent and cheap, we can verify references on every submission and re-execute results before publication. Those are checks most journals cannot staff. The AI is the proof behind the reproducibility promise, and the human signature is the accountability behind the AI.