Bibliographic record
Abstract
A database of over 97,000 research institutes with persistent identifiers.<br>Release notes:<br>Institutes added from the following sources: - Various sources including Germany, Spain, Norway, China, Canada, Slovakia, USA, and the UK<br>Metadata: - ROR IDs have been added as external identifier<br> - Updated Geonames data to a recent release - Added metadata to GRID records without any url and with type "Education" - Review of HESA IDs - Update of Wikidata IDs and Wikipedia links<br>QA: - Review of the National Physical Laboratory (UK)<br> - Review of the Naval Undersea Warfare Center and Naval Research Laboratory (US) - Review of the Royal Netherlands Academy of Arts and Sciences - Review of the European Space Agency - Review of some German research institutions - Review of "CONICET - the National Scientific and Technical Research Council Argentina" - Review of United Nations organisations - Review of Academia Sinica (Taiwan) - Review of Weill Medical College (US) - Review of US Agricultural Research Service Research Centers - Review of University of Paris-Saclay children<br>
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.848 | 0.531 |
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".