Bibliographic record
Abstract
The NEANIAS Open Event was planned for the last quarter of the project to present the objectives of the project, its motivations, the challenges undertaken, the results obtained and the innovative digital solutions available on the EOSC platform, offering a practical knowledge of NEANIAS from all perspectives (technological, functional, commercial, strategic), as well as the access to the project team. The event was aimed both to NEANIAS stakeholders and general audience. It was organized from the WP 10 “Communication, Dissemination and Outreach”, led by RICOH and had the support of the NEANIAS partners.<br> This document reports the activities and results in the context of the organization of the NEANIAS Open Event, carried on September 22nd and 23rd, 2022, in Sant Cugat del Vallès (Barcelona, Spain).<br> The document presents the work carried out considering throughout the process: the initial planning, including the strategic and organizational aspects, the details of the event developed, the results and impacts and finally a general description of the management and coordination model.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".