Bibliographic record
Abstract
There are many open source platforms and software out there that could be better serving our communities if they had a better and smoother interoperability between them. There are commercial vendors that are buying open source platforms to integrate them into locked-in ecosystems. We need open ecosystems, particularly in the research information domain. LYRASIS is the not for profit organization home of a variety of open source programs, among which are DSpace and VIVO. Users and community members around the world have been working on making these two platforms work together. After listening to the global community, the VIVO Governance with the support of LYRASIS, has decided to work on the VIVO-DSpace interoperability: defining a possible roadmap, allocated money, opened a call for participation, identified resources who will work on the 3 Phases project from 3 different countries. The process started in January, the team started meeting in February and by the time of the Conference we will be able to share the preliminary results and possibly to get other platforms interested in building up an open and interoperable ecosystem.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.099 | 0.004 |
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; both teacher heads 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".