REPA - Research and Education Promotion Association: Peer Review Policy
Bibliographic record
Abstract
This publication is a peer-reviewed journal aligned with international standards (the Council of Science Editors, Canada; and the Ministry of Education, Culture, Sports, Science and Technology – MEXT, Japan) that publishes high quality, original research contributions. All submissions in any form (original research, review article, letter, report, case study, methodology, lesson-learned, commentary, communication, editorial, technical note, and book review) and under any circumstances are undergoing to initial publication requirement appraisal by the Editorial Office, if a manuscript meets the initial assessment, then handles for peer review (single-blind) by competent reviewers in the field. Transparency of the editorial process ensured by using an online submission management platform that continuously tracked by anonymous (third party and stakeholders) referees. Meantime, the online submission management platform enables authors, reviewers, editors, readers, librarians, and administrations to access and track the process and progress of editorial affairs synchronously.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.313 | 0.472 |
| Meta-epidemiology (narrow) | 0.003 | 0.006 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.015 | 0.026 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.056 | 0.028 |
| Open science | 0.013 | 0.015 |
| Research integrity | 0.038 | 0.022 |
| Insufficient payload (model declined to judge) | 0.313 | 0.588 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".