On this page

Publication terms and privacy — effective 28 October 2026

Read the prospective publication terms and journal privacy and editorial-record retention notice before submitting or providing publication assent. Authors retain copyright; CC BY 4.0 applies to a new article only after the required rights holders and publisher agree. Existing journal articles are not automatically relicensed. AI-processing consent is separate.

The standard APC remains SGD1,500; the recorded full launch-phase waiver remains SGD0 for covered submissions. At least two independent human reviews in the current round are required before acceptance; supplementary LLM council reports never replace them.

Fully agentic editorial workflow with human peer reviewers (at least 2) and Council of LLMs as peer reviewers.

Journal of Learnomics combines an AI-administered editorial workflow, independent human peer review and clearly labelled AI peer-review reports from a Council of LLMs. At least two independent human reports from the current review round are required before acceptance. Council reports are additional and never count toward that minimum.

Pilot status: The author and reviewer portals are available. Automated processing and journal notifications are enabled following configuration and operational checks. The publisher oversees the pilot and handles cases that need intervention.

Open the author portal · Open the reviewer portal

Both portals require a journal account. To request an account or report an access problem, contact editor@mylearnomics.com. Use the author portal for manuscript files.

Fully agentic editorial board and publisher accountability

The editorial board consists of AI agents. The human peer reviewers are external reviewers, not editorial board members. This distinction does not remove the publisher’s responsibilities described below.

Aster Vale and the journal’s other AI editorial personas identify software roles. They are not human scholars and do not hold academic qualifications. Their names do not imply that each persona is a separate model or an independent source of expert judgement.

The implemented automated decision policy is human-consensus-v1. It applies defined rules to the human review record and the supplementary council checks. The language models do not independently select people, send invitations, publish articles or change editorial decisions. The publisher verifies and assigns human reviewers, manages exceptions and appeals, and authorises publication after the required checks.

The Institute of AI in Education, Singapore, remains accountable for the journal’s operation and published record. Editorial enquiries, complaints and appeals are handled through editor@mylearnomics.com.

Submission and independent human review

  1. Submit an anonymised manuscript. Supply the title, abstract, keywords, declarations and PDF through the author portal. Author names, affiliations and other private authorship details are recorded separately. The initial automated checks cover required fields and PDF format; they do not establish scientific validity.
  2. Reviewer verification and assignment. The publisher checks each proposed human reviewer’s identity, expertise, independence and possible conflicts of interest before assigning the reviewer and initiating an invitation. Reviewers must accept confidentiality requirements and declare no conflict before accessing the manuscript.
  3. Double-anonymous human assessment. Reviewer identities are withheld from authors, and reviewers receive an anonymised manuscript. Authors must remove names, affiliations, acknowledgements, identifying links and identifying PDF metadata from review materials. Public preprints or other public information can make identities discoverable; reviewers must disclose any resulting conflict.
  4. Reports and revision. Human reviewers assess the contribution, methods, evidence, interpretation and reproducibility. They provide comments for authors, a recommendation and, where appropriate, confidential comments for the editorial office. Authors receive released anonymous reports and decision letters through the portal. Revisions require a new manuscript version and a point-by-point response.

How automated decisions work

When automated mode is enabled, a manuscript cannot be accepted without at least two completed independent human reviews in its current round. Reports from an earlier round do not satisfy the new round’s minimum. The workflow also waits for outstanding invited or accepted review assignments.

  • Unanimous human recommendations to accept permit an acceptance outcome once the required checks are satisfied.
  • Unanimous recommendations to reject permit a rejection outcome.
  • Recommendations requesting minor or major revision route the manuscript to revision, unless an accept/reject conflict requires arbitration.
  • A mixture of accept and reject recommendations holds the manuscript for publisher assessment. The publisher may seek clarification or additional independent human review.

The automated route also holds when reviewers or reports are missing, the author has not consented to the necessary AI processing, anonymised manuscript text is missing, a council concern remains, or a service or validation check fails. A hold is not a rejection. The publisher can arrange an alternative route when optional AI processing is declined, and can record a reasoned intervention or pause the workflow. No intervention can waive the minimum of two completed independent human reviews required for acceptance.

Acceptance and publication are separate steps. Final proof approval, attribution, publication permissions and production checks are required before a public article is released.

Council of LLMs as peer reviewers

The council provides three clearly labelled AI reports using methods and statistics, learning science, and reproducibility perspectives. Its configured models are Gemini 3.8 Flash, Gemini 3.7 Flash and Gemini 3.5 Flash-Lite, accessed through Google Cloud. These are variants within the same provider and model family. They can share errors and limitations; they are not three independent model families or human experts.

Council findings are supplementary. They may raise questions that require attention, but cannot replace the human reports or independently authorise acceptance. The journal records the model used for each report. Authors receive the supplementary council report with the released review record when applicable.

Author consent: AI processing requires an explicit opt-in. The council request contains the anonymised title, abstract, keywords and manuscript plain text supplied for that purpose. It excludes the uploaded PDF, private author fields and confidential comments to the editor. Authors must remove identifying information from the text itself; excluding the private fields cannot remove identities an author leaves in the title, abstract or manuscript text.

Reviewer consent: Reviewers separately choose whether their anonymous comments for authors may be sent to the journal’s Google Cloud service for AI-assisted synthesis. Confidential comments to the editor are excluded. Reviewers remain responsible for personally assessing the work and must not upload confidential manuscripts or reports to public or unapproved AI services.

Processing location: The configured model endpoint is global. Singapore hosting of the journal’s cloud service and database does not mean model processing is restricted to Singapore. The author’s consent covers this disclosed cloud processing; declining it pauses the automated AI route for publisher attention.

Cloud-result retention: Cloud job results, including council results, are assigned a 30-day expiry in Firestore. Automatic deletion is asynchronous and may occur after that expiry; deletion at exactly 30 days is not guaranteed. This cloud expiry does not delete the manuscript files, editorial records or report copies kept by the journal.

Journal-record retention: The publisher adopted the journal privacy and editorial-record retention policy, version jol-retention-2026-10-28-v1, effective 28 October 2026. Accepted-article editorial files are retained for 7 years after publication or final appeal closure, whichever is later; rejected or withdrawn submissions for 2 years after final decision or appeal closure. The policy also covers reviewer-roster review, 90-day operational logs and backup rotation, necessary rights evidence and documented holds. It does not claim automatic purge of every journal or hosting copy. Contact editor@mylearnomics.com for privacy or retention requests.

Appeals and corrections

To appeal a decision or report a process concern, email editor@mylearnomics.com with the manuscript identifier, the issue and supporting evidence. The publisher reviews the concern and may seek clarification, additional independent human assessment or a fresh review round. Reopening a submission does not allow old reports to satisfy the minimum for a new round.

Concerns about published work are handled through a documented correction or retraction process rather than silently reopening or replacing the published record. An appeal does not guarantee a different outcome.

Standard APC and full launch-phase waiver

Submission is free. The standard article processing charge remains SGD 1,500. To mark the launch of this workflow, the journal offers a full launch-phase APC waiver, including for authors invited under the launch offer. No expiry date has been announced.

The portal displays the current APC and waiver terms before submission and saves those terms with the manuscript. A submission receiving the full launch waiver retains its recorded waiver through review and publication, even if the offer later changes for new submissions. No payment is collected through the portal. Where an APC is payable outside the waiver, it is payable only after acceptance.

Payment and waiver status do not influence editorial decisions. An invitation or waiver does not guarantee acceptance. All research submissions remain subject to the same minimum human-review requirements.

Official editorial correspondence is sent from editor@mylearnomics.com.