Bibliographic record
Abstract
See RECORDING. Open Journal Systems (OJS) was released in 2001 and has since become the most widely used open-source journal publishing platform in existence, with over 25,000 journals using it worldwide. Over the past few years, the Public Knowledge Project (PKP), its creator, has been working on improving accessibility of the platform, including the release of the first accessible Default theme in OJS 3.3. This presentation will go over the accessibility improvements made to day and those planned ahead. Making the platform accessible is only half the battle however as it is often the published content that presents barriers to readers. Creating resources for editors and authors to improve content accessibility – in OJS and beyond – is one of the goals of the PKP Accessibility Interest Group (AIG), a community initiative established in 2020. We will highlight the work of the group and the resources it makes available to the public. This overview is presented on behalf of the PKP AIG.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.023 | 0.016 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.118 | 0.036 |
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".