Bibliographic record
Abstract
This report outlines the development of the Institutional Publisher Service Providers (IPSP) Guidelines, a deliverable of DIAMAS Task 4.3. The guidelines build on existing resources and previous outputs from the DIAMAS and CRAFT-OA projects, and aim to provide comprehensive instructions to help IPSPs meet current standards for Diamond Open Access (OA) publishing, as defined in the Diamond OA Standard (DOAS) (Consortium of the DIAMAS Project, 2024). Following an extensive analysis of resources, 18 thematic areas were identified, based on their relevance across diverse publishing practices and challenges as well as their potential to enhance the credibility, efficiency, and capacity of IPSPs. These topics align with the seven core components of the DOAS, and correspond to the scope and contents of the forthcoming IPSP Toolsuite (D4.3). The guidelines were collaboratively drafted by DIAMAS and CRAFT-OA partners and reviewed by the Toolsuite Editorial Board. To ensure accessibility for a broader audience, the guidelines have been translated into Spanish, Portuguese, and Croatian and will be integrated into the DIAMAS Common Access Point (CAP) as part of the online IPSP Toolsuite. The guidelines will be regularly updated with new resources and tools to ensure they remain current and continue to support best practices in OA publishing.
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 | 0.064 | 0.133 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.014 | 0.008 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.034 | 0.059 |
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".