El siguiente paso en el desarrollo de los repositorios: integración con la infraestructura institucional de gestión de la información científica
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dídac Martínez, Director de l'Àrea de Serveis Universitaris de la UPC, va esmentar en la seva introducció una sèrie de 10 prioritats per al \ndesenvolupament dels dipòsits institucionals, de les quals la desena era la integració dels repositoris en la infraestructura institucional de gestió de la informació científica. A més de citar diverses iniciatives de integració en aquest sentit -tant per investigació com per a continguts docents- a la Universitat Politècnica de Catalunya, la presentació va esmentar NARCIS com a model, un sistema CRIS d'àmbit nacional desenvolupat a Holanda per una sèrie d'universitats (que comparteixen Metis com a sistema CRIS institucional), NWO i el KNAW.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it