AGINFRA PLUS D8.3 - AGINFRA Future Science Recommendations
Bibliographic record
Abstract
This document serves as a white paper, which describes the AGINFRA+ vision of a next-generation community driven web-based research infrastructure, as well as present and future application scenarios that can be envisaged from experiences with the piloted AGINFRA+ user communities and provides recommendations that aim to inform the roadmap for developing AGINFRA+ infrastructure further. The document provides an overview of the involved user communities and their different user profiles, as well as the way to involve each community in the projects’ activities. It describes the objectives and the obstacles that each community had to overcome and provides all the necessary details regarding the special and indispensable aim that has been provided through the use of the AGINFRA+ Virtual Research Environments (VREs). Specific emphasis is provided to risks that the communities might face in the near future and to recommendations regarding how they should address these challenges based on the existing VREs.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.011 | 0.005 |
| Insufficient payload (model declined to judge) | 0.207 | 0.260 |
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".