Making the Move to Open Journal Systems 3: Recommendations for a (mostly) painless upgrade
Bibliographic record
Abstract
From June 2017 to August 2018, Scholars Portal, a consortial service of the Ontario Council of University Libraries, upgraded 10 different multi-journal instances of the Open Journal Systems (OJS) 3 software, building expertise on the upgrade process along the way. The final and the largest instance to be upgraded was the University of Toronto Libraries, which hosts over 50 journals. In this article, we will discuss the upgrade planning and process, problems encountered along the way, and some best practices in supporting journal teams through the upgrade on a multi-journal instance. We will also include checklists and technical troubleshooting tips to help institutions make their upgrade as smooth and worry-free as possible. Finally, we will go over post-upgrade support strategies and next steps in making the most out of your transition to OJS 3. This article will primarily be useful for institutions hosting instances of OJS 2, but those that have already upgraded, or are considering hosting the software, may find the outlined approach to support and testing helpful.
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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 | 0.135 | 0.377 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.034 | 0.038 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.022 | 0.023 |
| Insufficient payload (model declined to judge) | 0.038 | 0.027 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".